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Postdoc Position at Radboud University (Nijmegen) in NeuroAI: Biologically Grounded Neural Networks for Cognition
by Paul Tiesinga Oct. 29, 2026

Oct. 29, 2026

Postdoc Position at Radboud University (Nijmegen) in NeuroAI: Biologically Grounded Neural Networks for Cognition _Can you help designing cognitive architectures to make brain implants smart in an international and interdisciplinary team involving the top neuroscience institutes in the Netherlands and thereby (ultimately) contribute to improve the life of patients?_ Brain implants are, for the most part, fixed-function devices. The EBRAINS-NEUROTECH infrastructure is building a tool chain that changes this: neural networks that perform the perceptual and cognitive processing an implant needs, run on-device, and can be adapted by the experimenter. You will build the core of that tool chain: a set of neural network modules for perception and cognition, grounded in what we know about the brain's own mechanisms. For this position you will develop NeuroAI-in-practice: a set of neural network modules that can be easily used and adapted by an experimental user, while also giving publishable scientific insights in and of themselves. Two use-cases, involving processing for vision implants and implants for cognitive restoration, will guide the work. These networks also have to run on-device. Together with a postdoctoral researcher from the Centre for Mathematics and Computer Science (CWI), you will translate the designs to a neuromorphic architecture. Does this sound like you? * You are a scientific programmer or postdoctoral researcher with excellent programming skills and a strong interest in NeuroAI. * You have a PhD degree in a quantitative field, such as physics, mathematics, computer science, engineering or computational or theoretical neuroscience. * You have experience with programming in Python and C in combination with deep learning tools such as PyTorch, TensorFlow, and JAX. * You have a background in neuroscience, preferably on mechanisms for cognitive processes, or a strong desire to obtain such a background. This position is physically hosted at the Neurophysics department of the Donders Institute at Radboud University. The work is part of the Software Platform of the EBRAINS-NEUROTECH infrastructure, involving teams at the University of Amsterdam (Dr Jorge Mejias), CWI (Prof. Sander Bohte) and Radboud University (Prof. Paul Tiesinga). To apply for this job please consult the Academic Transfer link: https://www.academictransfer.com/en/jobs/365079 For more information contact Paul Tiesinga at p.tiesinga(a)science.ru.nl

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ANNOUNCING the 2025 Best Illusion of the Year Contest Winners AND ACCEPTING SUBMISSIONS for the 2026 CONTEST!
by smart＠neuralcorrelate.com Oct. 29, 2026

Oct. 29, 2026

Dear Illusion Enthusiasts, Voters around the globe chose the Best Illusions of 2025 from the TOP TEN Finalists competing in the 20th edition of the Best Illusion of the Year Contest <https://illusionoftheyear.com/> (hosted by the Neural Correlate Society and supported by the Museum of Illusions <https://www.museumofillusions.com/> ). The TOP THREE winning illusions were revealed on Tuesday, October 27th, 2026. First Prize and a $3,000 award went to "Cogs in a Machine," by Jacky Z. J. Yueh and Joan Danielle K. Ongchoco, Canada. Second Prize and a $2,000 award went to "9 Purple Dots," by Hinnerk Schulz-Hildebrandt, United States. Third Prize and a $1,000 award went to "The Hole Truth," by Matt Pritchard, United Kingdom. This year's illusions are making headlines! Read The Washington Post's article featuring several of the illusions that just competed in the Best Illusion of the Year Contest: <https://www.washingtonpost.com/health/2026/10/27/how-this-years-best-optica l-illusions-trick-your-brain/> How this year's best optical illusions trick your brain. If you enjoyed the spectacular winning and finalist illusions, please consider making a tax-deductible donation <https://www.paypal.com/webapps/shoppingcart?flowlogging_id=d2461f180023b&mf id=1607894519576_d2461f180023b#/checkout/openButton> to the Best Illusion of the Year Contest. We rely on your generous help to continue to share the wonders of illusion with people of all ages and backgrounds, all over the world. We are now accepting submissions for the 21st edition of the Best Illusion of the Year Contest! If you have created a novel, mind-bending illusion, we invite you to share it with the world. Don't miss the opportunity to be part of next year's TOP TEN illusions and compete for international recognition and cash prizes. Contestants are invited to submit 1-minute YouTube videos featuring novel illusions (unpublished or published no earlier than 2025) of all sensory modalities (visual, auditory, etc.) and/or cognitive nature. Novel variants of known illusions are welcome. The content of the 1-minute video presenting your illusion is solely up to you, and the only requirement is that it wows all viewers! Some examples include, but are not limited to: * A slide presentation, or succession of images, with a voice over (and/or written text, if you prefer) * A video of yourself describing your illusion * A video animation/theatrical performance of your illusion An international panel of impartial judges will rate all the videos and narrow them down to the TOP TEN. Then, online voters around the world will choose their favorite illusions from the TOP TEN finalists. The TOP THREE winners will receive cash prizes: $3,000 USD for first place; $2,000 USD for second place, and $1,000 USD for third place. The Judge Panel will rate illusions according to: * Significance to our understanding of the human mind and brain * Simplicity of the description * Sheer beauty * Counterintuitive quality * Spectacularity Submissions will be held in strict confidence by the Judge Panel. Only the TOP TEN illusions will be posted online, to allow worldwide voting. Participation in the Best Illusion of the Year Contest does not preclude you from also presenting or submitting your work for publication elsewhere. By participating in the Best Illusion of the Year Contest you agree to have your illusion posted on the Contest website, if selected among the TOP TEN, and included in press releases and other promotional materials/fundraising initiatives for the Contest. You (and your co-authors, if appropriate) will retain the full copyright of your illusion and receive full credit as illusion creator(s). Illusions submitted to previous editions can be re-submitted to the 2026 Contest, as long as they meet the above requirements and were not among the TOP TEN finalists in previous years. You can send your 1-minute video to Susana Martinez-Conde via email ( <mailto:smart@neuralcorrelate.com> smart(a)neuralcorrelate.com) until December 14th, 2026. On behalf of the Executive Board of the Neural Correlate Society: Jose-Manuel Alonso, Stephen Macknik, Susana Martinez-Conde, Luis Martinez, Xoana Troncoso, Peter Tse ---------------------------------------------------------- Susana Martinez-Conde, PhD Author, <x-msg://2/championsofillusionbook.com> Champions of Illusion and Sleights of Mind Professor of Ophthalmology, Neurology, and Physiology & Pharmacology State University of New York (SUNY) Downstate Health Sciences University 450 Clarkson Ave, Brooklyn NY 11203, USA Email: <mailto:smart@neuralcorrelate.com> smart(a)neuralcorrelate.com Phone: <tel:%2B1%20718-270-4520> +1 718-270-4520 http://smc.neuralcorrelate.com

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Diagnosing inconsistent partial-cue recall in a small recurrent LIF network
by 오성민 Oct. 28, 2026

Oct. 28, 2026

Hello, I’m developing an independent, AI-assisted computational modelling project. My immediate goal is reliable partial-cue recall that depends on learned recurrent connections. I would appreciate advice on the first diagnostic to prioritize, or a published working model suitable for comparison. The network has 24 input channels, 96 expansion neurons, 48 excitatory recurrent memory neurons, and a fixed 32-neuron LIF readout. Input-to-expansion connections learn normalized input/spike coactivity during storage. Recurrent memory weights also learn; all weights are frozen during evaluation. The protocol presents a six-channel pattern P for 1,000 ms, then zero input for 500 ms, followed by three of P’s channels continuously for 200 ms. The current endpoint is cosine similarity between readout spike counts and a full-P reference recorded before learning. A paired control restores the same post-storage checkpoint and resets only recurrent weights to their initial values. Input-pathway weights, neural state, retained traces, and initial RNG state are preserved. A separate recurrent-learning-off condition still permits input-pathway learning during storage. Across three seeds, learned-minus-reset cosine differences were +0.003414, +0.003999, and −0.037353. This did not meet the specified robustness criteria. In the negative case, learned and reset branches had identical per-neuron memory spike counts, but different spike timings. Five readout spikes were absent in the learned branch; its score was 0.842399 versus 0.879752 after reset. Also, naïve readout responses to two overlapping full patterns were very similar in two seeds, with P/Q cosines of 0.97846 and 0.99618; the third was 0.77380. These observations do not establish successful recall hidden by the readout. Some implementation details: - Current-based LIF, dt=1 ms, tau=20 ms, rest/reset=−65, threshold=−50, refractory period=2 ms. - Recurrent connections are directed, excitatory-only, approximately 60% dense, with no self-connections and a one-step delay. Weights start at 0.6 and are clipped to [0,8]. - The learning rule examined here is dW[j,i]=0.06*spike[j]*pre_trace[i]−0.025*post_trace[j]*spike[i]. Both traces decay with a 20-ms time constant; updates use decayed traces before adding current spikes. - Expansion-to-memory and memory-to-readout projections each supply 12 inputs per postsynaptic neuron, weighted 180 and 120 respectively. Which diagnostic would you prioritize to localize the bottleneck between learned recurrent completion and its measurement through the fixed readout, while accounting for the learned input pathway? What contrasting outcomes would make that diagnostic informative? A published LIF associative-memory model with a comparable partial-cue test would be particularly helpful. I am seeking a practical next step toward a working circuit, while keeping the existing endpoint and negative findings unchanged. Thank you. 오성민 Independent researcher Unaffiliated

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Postdoc Fellowships at WashU
by Goodhill, Geoffrey Oct. 28, 2026

Oct. 28, 2026

POSTDOCTORAL FELLOWSHIPS AVAILABLE AT WASHINGTON UNIVERSITY IN ST LOUIS The Center for Theoretical and Computational Neuroscience (ctcn.wustl.edu) at Washington University in St Louis invites applications from outstanding Postdoctoral Fellows to work at the interface between theoretical and experimental neuroscience labs at WashU. Deadline for applications is Dec 1st 2026. The CTCN is a joint initiative between the Schools of Medicine, Engineering, and Arts and Sciences at WashU, and provides a hub for neuroscientists to collaborate with mathematicians, physicists and engineers to find creative solutions to some of the most difficult problems currently facing neuroscience and artificial intelligence. Each CTCN Postdoctoral Fellow is based in at least two labs, but also has the opportunity to seek out new collaborations which help build new connections within the WashU community. We are looking for people with drive, independence and outstanding prior achievement, who are committed to leveraging interdisciplinary collaboration to drive forward the field of theoretical and computational neuroscience. Washington University in St Louis is ranked =6 worldwide for Neuroscience and Behavior by USNews. Salary for CTCN Fellows is $80,000 plus $10,000 for research costs and travel. In addition, WashU offers excellent benefits and comprehensive access to career development, professional and personal support. The St Louis metropolitan area has a population of almost 3M and is rich in culture, green spaces and thriving music and arts scenes, with a highly accessible cost of living. For more details, including how to apply, please see https://ctcn.wustl.edu/postdoc-fellows Professor Geoffrey J Goodhill CTCN Director Departments of Developmental Biology and Neuroscience Affiliate appointments: Physics, Biomedical Engineering, Computer Science and Engineering, and Electrical and Systems Engineering Washington University School of Medicine 660 S. Euclid Avenue St. Louis, MO 63110 g.goodhill(a)wustl.edu https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd

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[Jobs] two 4 years PhD positions with Prof. Laurenz Wiskott at Ruhr University Bochum, Germany, for modeling episodic memory in humans
by Laurenz Wiskott Oct. 28, 2026

Oct. 28, 2026

Germany : Ruhr University Bochum : Faculty of Computer Science : Institute of Neuroinformatics : Theory of Neural Systems Application platform: https://jobs.ruhr-uni-bochum.de/en/jobposting/b03ed1dd010514c25ed288e12387d… In order to fill a fixed-term position in part-time (29.87 hours/week = 75%) 01.01.2027 pending funding approval, we are looking for candidates (m/f/x) for two Doctoral Positions. The Institute of Neuroinformatics is a research institute of the Faculty of Computer Science at the Ruhr University Bochum, see https://www.ini.rub.de/. It focuses on the dynamics and learning of perception and behavior on a functional level but is otherwise very diverse, ranging from neurophysiology and psychophysics over computational neuroscience to machine learning and technical applications. Bochum is one of the centers of episodic memory research with a coherent framework developed within the DFG Research Unit 2812 "Constructing Scenarios of the Past" (https://for2812.rub.de/) combining psychology, neuroscience, philosophy, and computational neuroscience. In order to fill two fixed-term positions in part-time (29.87 hours/week = 75%) from the 1st of January 2027, pending funding approval, we are looking for 2 doctoral students in the research group of Professor Laurenz Wiskott. The research focuses on modeling generative episodic memory within a large, highly interdisciplinary research consortium in close collaboration with experimental partners. The methods used draw from neural network theory and machine learning. Your tasks: * Contributing to the development of an integrated systems level model of generative episodic memory. * Integrating this model with other aspects of cognition, such as planing and reasoning. * Modeling experimental data. * Communication with experimental partners. * Publication of results. Your profile: * Very good Master degree in physics, mathematics, computer science, engineering, or a related field. * Interest in interdisciplinary research in the area of neuroscience. * Good programming and mathematical skills. * Basic knowledge in machine learning. Advantageous: * Experience in modeling. * Experience in interdisciplinary projects. * Programming skills in Python. We offer: * Challenging and varied tasks with a high level of independence * Collaboration in a committed and appreciative team * Extensive training and professional development opportunities * Options for flexible working (mobile working and teleworking) * An interesting interdisciplinary environment in the field of theoretical brain research / machine learning. * Freedom to shape the project yourself. * Infrastructure that facilitates close integration into the institute and the research group. * Opportunity to pursue a Ph.D. Further information: The position is salaried and based on the collective agreement of the Länder (TV-L). If the personal and collective agreement requirements are met, the employee will receive pay grade E13 TV-L. Further information can be found at https://oeffentlicher-dienst.info/ (in German). The place of work is Ruhr University Bochum. If the position is funded by third-party funds the employee has no teaching obligation. RUB sees itself as a university with an international presence. The campus languages are German and English. Competence in at least one of the two languages and the willingness to learn the other are a prerequisite. RUB provides corresponding free courses for employees. German language courses are offered by the University Language Center (ZFA) in the field of German as a Foreign Language (DaF). https://www.daf.ruhr-uni-bochum.de/daf/mitarbeitende/index.html.en The Staff Council has the right to participate in all selection interviews. At the request of a candidate (m/f/x), it will ensure its participation in the entire procedure. Please contact wpr(a)rub.de. The Ruhr-Universität Bochum is one of Germany’s leading research universities, addressing the whole range of academic disciplines. A highly dynamic setting enables researchers and students to work across the traditional boundaries of academic subjects and faculties. To create knowledge networks within and beyond the university is Ruhr-Universität Bochum’s declared aim. The Ruhr-Universität Bochum stands for diversity and equal opportunities. For this reason, we favour a working environment composed of heterogeneous teams, and seek to promote the careers of individuals who are underrepresented in our respective professional areas. The Ruhr-Universität Bochum expressly requests job applications from women. In areas in which they are underrepresented they will be given preference in the case of equivalent qualifications with male candidates. Applications from individuals with disabilities are most welcome. Contact persons for further information: Laurenz Wiskott , Tel.: +49 234 32 27997 Travel costs, accommodation costs and loss of earnings or other application costs for job interviews can unfortunately not be reimbursed. We look forward to receiving your application via our online application portal by 2026-11-09. Please make sure to mention the reference number ANR 6248: https://jobs.ruhr-uni-bochum.de/en/jobposting/b03ed1dd010514c25ed288e12387d…

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Postdoctoral contract at Instituto de Neurociencias (Alicante, Spain) - up to 2 years
by Encarni Marcos Sanmartin Oct. 28, 2026

Oct. 28, 2026

Dear colleagues, We are looking for a *postdoctoral researche*r to join our lab, the Plasticity of Brain Networks at the Institute for Neurosciences (CSIC–UMH) in Alicante, Spain. Please find the full announcement attached. I would be grateful if you could share it with anyone who might be interested. One of our research lines focuses on studying how different brain regions interact to shape our choices, and how the body, and movement in particular, influences what we decide. We combine behavioral tasks in animal models,* in vivo* electrophysiology, and computational modeling. The postdoc will: • Train animals in decision-making tasks • Perform in vivo electrophysiological recordings • Analyze behavioral and neural data, in close interaction with computational modeling *Requirements*: PhD in Neuroscience, Biology, Psychology, Physics, Engineering, or a related field; demonstrable hands-on experience in electrophysiology; accreditation for animal experimentation; good written and spoken English. *Valued*: experience training animals in behavioral tasks and programming skills (Python/MATLAB). We *offer* a full-time contract for up to 2 years, with salary according to UMH scales, in a Severo Ochoa Center of Excellence a few minutes from the Mediterranean Sea. To apply, please send your CV, a cover letter, and contact information for two references to emarcos(a)umh.es. Applications will be reviewed on a rolling basis until the position is filled. Direct link to the offer: https://in.umh-csic.es/es/ofertas/postdoctoral-position-2-years-neural-mech… Feel free to contact me with any questions. Best regards, Encarni Marcos Plasticity of Brain Networks Lab Institute for Neurosciences (CSIC–UMH) Alicante, Spain emarcos(a)umh.es

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call for Workshops, RLDM
by Becket Ebitz Oct. 27, 2026

Oct. 27, 2026

We invite submissions for workshop proposals for the 7th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM2027), to be held July 6-9, 2027 at Maison de la Chimie, Paris, France. Workshops are a half-day and held during the conference. The submission deadline for workshop proposals is Friday, December 11, 2026, with notification by January 15, 2027. Proposals should be submitted via the google form linked below. What are RLDM Workshops? The goal of the RLDM workshops is to encourage interdisciplinary discussion and to provide an informal forum for researchers to discuss important questions and challenges focused on a specific topic. Workshop topics may include anything from important current/controversial issues, open problems, and comparisons of competing approaches. You are free to choose a format that suits the topic, and in the past have included invited oral presentations,’blitz’ talks, panel discussions, data modeling challenges, hackathons, debates, and symposia aimed at improving communication between researchers from different fields rather than presenting novel research. Or a combination of any of those! Workshop organizers propose the workshop content, coordinate speakers, and provide the program for the workshop in a timely manner (a rough suggested timeline will be posted in the FAQ soon). Organising a workshop is your chance to shape the conference or kickstart a new community, so we encourage researchers at all stages of their career to consider getting involved in a workshop proposal. For inspiration, have a look here for workshops at RLDM2025: https://rldm.org/past-meetings/rldm2025/workshops/ How to Submit Workshop proposals are due by 23:59 UTC on Friday, December 11, 2026. They can be submitted using the following form: https://docs.google.com/forms/d/e/1FAIpQLSc2ODIMAUncPtVn50Tf_Ulw0pK-fKqLUdH… Notifications will be provided by email on or before January 15, 2027. Proposals will be asked to respond to the following questions: -- Workshop title and acronym (if available) -- A brief description of the workshop focus (max 2000 characters) -- A brief justification of how this workshop engages the multidisciplinary RLDM community. If a similar theme has been explored in recent years or at other venues, please highlight the new developments that warrant revisiting this topic (max 1000 characters) -- A short description of the format of planned activities (talks, panels, invited speakers, activities, etc.) (max 1500 characters) -- A list of invited speakers, and indicate who has confirmed their willingness to participate. Note that it is not necessary at this stage to have established confirmation from all participants in the workshop and that the workshops are 1/2 day. -- A list of workshop organizers with web page URLs if available. -- A brief mention of any past event or workshop organizing experience. We encourage at least one organizer to have past event organizing experience. (max 500 characters) -- The email addresses of all workshop co-organisers. FAQ Q: Is there any travel funding available for workshop speakers? RLDM will not be able to provide travel funding for workshop speakers. In previous years, some workshops have sought and received funding from external sources to bring in outside speakers and RLDM is open to that model. Organizers should list all funding sources in the proposal. Q: Who should I contact with questions? Please feel free to contact us at rebitz(a)gmail.com and giorgia.ramponi(a)uzh.ch if you have any questions! For the quickest response please use “RLDM2027 Workshops” in your subject line. Q: How will proposals be evaluated? Workshop proposals will be evaluated and selected by the RLDM Workshop Chairs based on the following metrics, in no particular order: 1. Relevance to the RLDM community 2. Interdisciplinary scope of the proposal 3. Current interest in the topic within the community 4. Diversity and equity in the proposed presenters/speakers/organizers 5. Potential for new research directions and interactions to emerge Q: What if I want to get involved with a workshop proposal, but I don’t have co-organizers? Please get in touch with us over email; we might be able to pair you with other possible co-organizers. Q: How many workshops will there be? Around six. Sincerely, Becket Ebitz and Giorgia Ramponi RLDM2027 Workshop Chairs

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Pynapple & NeMoS workshop on neural data analysis
by Edoardo Balzani Oct. 27, 2026

Oct. 27, 2026

Dear colleagues, We are running an hands-on workshop on two open-source Python packages for systems neuroscience, held at the Flatiron Institute in New York City from January 26 to January 28, 2027: - *Pynapple*, for loading, manipulating, and analyzing neural and behavioral time series. - *NeMoS*, for statistical modeling of neural activity, including generalized linear models (GLMs) and GLM-HMMs. *Application Deadline: *November 22, 2026 The workshop combines lectures with hands-on coding sessions on real datasets. Details and registration: https://www.simonsfoundation.org/events/ccn-software-workshop-2027/ *Workshops at your institution* Next year we also plan to teach shorter, more focused versions of the workshop at host universities. The host takes care of the logistics (room, recruiting and coordinating attendees), and members of our team teach the material. If you would like us to teach at your department or PhD program, or want more information, please reply to this email. Please forward this message to anyone who may be interested. Best regards, The NeuroRSE team

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[Meetings] Call For Applications 2027 Nengo Summer School
by Madeleine Bartlett Oct. 27, 2026

Oct. 27, 2026

Dear colleagues, The Centre for Theoretical Neuroscience at the University of Waterloo is excited to announce our 12th annual Nengo summer school on large-scale brain modelling and neuromorphic computing. This two-week school will teach participants to use the Nengo simulation package to build state-of-the-art cognitive and neural models to run both in simulation and on neuromorphic hardware. Summer school participants will be given on-site access to neuromorphic hardware and will learn to run high-level applications using Nengo! More generally, Nengo provides users with a versatile and powerful environment for designing cognitive and neural systems and has been used to build what is currently the world's largest functional brain model, Spaun, which includes spiking deep learning, reinforcement learning, adaptive motor control, and cognitive control networks. For a look at the last summer school, check out this short video: https://youtu.be/hHwIryt053M?si=N70eVlC3Sm_2sDy5 We welcome applications from all interested graduate students, postdocs, professors, and industry professionals with a relevant background. ***Application Deadline: December 21st, 2026*** Format: A combination of tutorials and project-based work. Participants are encouraged to bring their own ideas for projects, which may focus on testing hypotheses, creating models to account for neural or cognitive data, implementing specific behavioural functions with neurons, expanding past models, or providing a proof-of-concept of various neural mechanisms. Hands-on tutorials, individual or group projects, and talks from invited faculty members will make up the bulk of day-to-day activities. A project demonstration event will be held on the last day of the school, with prizes for strong projects! Participants will have the opportunity to learn how to: * interface Nengo with various kinds of neuromorphic hardware (e.g. BrainDrop, SpiNNaker) * build perceptual, motor, and sophisticated cognitive models using spiking neurons * build models to account for anatomical, electrophysiological, cognitive, and behavioural data * use a variety of single cell models within a large-scale model  * integrate machine learning methods into biologically oriented models * interface Nengo with cameras and robotic systems * implement modern nonlinear control methods in neural models * neurally implement vector symbolic architecture algorithms * and much more… Date and Location: May 30th to June 11th, 2027 at the University of Waterloo, Ontario, Canada. Applications: Please visit http://www.nengo.ai/summer-school, where you can find more information regarding costs, travel, lodging, along with an application form listing required materials. If you have any questions about the school or the application process, please contact: Madeleine Bartlett: madeleine.bartlett(a)uwaterloo.ca<mailto:madeleine.bartlett@uwaterloo.ca> Kathryn Simone: kpsimone(a)uwaterloo.ca<mailto:kpsimone@uwaterloo.ca> The school is partly supported by ABR, Inc. We look forward to hearing from you! Best, Maddy she/her/elle Associate Research Officer / Agent de recherche associé National Research Council Canada / Conseil national de recherches Canada Adjunct Professor / Professeur adjoint Psychology Department at the University of Waterloo / Département de psychologie de l'Université de Waterloo Email NRC: maddy.bartlett(a)nrc-cnrc.gc.ca Email UW: madeleine.bartlett(a)uwaterloo.ca

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JOB: Faculty Position in Cognitive Psychology, Seoul National University
by Jiook Cha/SNU/Psychology Oct. 27, 2026

Oct. 27, 2026

Dear comp-neuro list members, The Department of Psychology at Seoul National University is recruiting a full-time faculty member in Cognitive Psychology. The position is open to all subfields. I would be grateful if you could circulate the announcement below to the list. Faculty Position in Cognitive Psychology, Seoul National University The Department of Psychology in the College of Social Sciences at Seoul National University (SNU) invites applications for a full-time, tenure-track or tenured faculty position in Cognitive Psychology, with an anticipated start date of September 1, 2027. We welcome applications from all subfields of cognitive psychology. Applications will be accepted from December 1, 2026, until 16:00 KST on December 30, 2026. What we seek We seek a pioneering scholar who is advancing an independent research program that addresses important, unresolved questions about human cognition. We welcome researchers who formulate new theoretical accounts and test them through rigorous experimental and behavioral research, extending the explanatory reach of cognitive psychology. We encourage applications from scholars who are open to new approaches, lead research collaborations in Korea and abroad, and help shape the direction of the field through their contributions to international scholarly debate. Teaching and mentoring The successful candidate will teach undergraduate and graduate courses, including laboratory courses in cognitive and behavioral experimentation, and mentor student research. We aim to strengthen training in experimental approaches to psychological science and develop research training that incorporates generative models. Academic environment The Department of Psychology at SNU runs the Institute of Psychological Science, and its faculty participate in interdisciplinary research within and beyond the university. SNU's Interdisciplinary Programs in Neuroscience and in Cognitive Science, along with the Graduate School of Artificial Intelligence, provide opportunities to engage with researchers in neuroscience, linguistics, philosophy, and artificial intelligence. The Department also leads Brain-Mind-Behavior, an undergraduate interdisciplinary program with participation from Economics, Philosophy, Biological Sciences, Computer Science and Engineering, and other departments. Application information Field: Cognitive Psychology Anticipated start date: Wednesday, September 1, 2027 Eligibility, appointment terms, and required documents: Applicants must hold a doctoral degree and meet SNU's faculty appointment eligibility requirements. Please see the official announcement below for appointment terms and detailed document requirements. Letters of recommendation: At least two letters from specialists in the same field are required after Stage 1 (interview candidates and the letter deadline will be notified individually). Referee information must be entered at the time of application; letters may also be submitted during the application period. Requests to referees through the application system must be sent before the application deadline. Application period: Tuesday, December 1, 2026, 11:00 to Wednesday, December 30, 2026, 16:00, Korea Standard Time (KST, UTC+9) How to apply: Submit your application and upload the required documents through the SNU faculty recruitment system: https://www.google.com/url?q=https://shine.snu.ac.kr/adm/adm/hura/wrct/main… Anticipated review schedule: Stage 1 review, January 12 to February 4, 2027. Stage 2 review, February 15 to March 26, 2027. Official announcement: https://www.google.com/url?q=https://social.snu.ac.kr/%25EA%25B3%25B5%25EC%…. If this advertisement differs from the official announcement, the official Korean announcement prevails. Inquiries: For application procedures, contact the Office of Academic Affairs, College of Social Sciences (+82-2-880-6309 <02-880-6309>, yeojin(a)snu.ac.kr) For the field and the department, contact Professor Jiook Cha, PhD (connectome(a)snu.ac.kr) Best, Jiook Cha, PhD Associate Professor and Chair Department of Psychology Seoul National University

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[jobs] Research Software Engineer, Nengo Neural Simulation Ecosystem
by Michael Furlong Oct. 26, 2026

Oct. 26, 2026

Research Associate — Research Software Engineer, Nengo Neural Simulation Ecosystem Centre for Theoretical Neuroscience, University of Waterloo · Posted 23 October 2026 Position summary The Centre for Theoretical Neuroscience is hiring a research software engineer on an 11-month term to modernize Nengo, our open-source neural simulation ecosystem. Nengo is a widely used spiking neural network simulator. The post is funded by a Research Software Maintenance Fund award from the Digital Research Alliance of Canada. The work is focussed on rebuilding continuous integration and test coverage, modernizing the OpenCL and deep-learning backends, returning the project to automated signed releases, and leaving documentation good enough for maintainers who did not write the code. About the project and team Nengo is a Python framework for building large-scale functional brain models, in continuous development since 2013. It has shipped 21 stable releases, records more than 270,000 downloads, and runs models across CPUs, GPUs and neuromorphic hardware including Intel Loihi and SpiNNaker. The ecosystem has outgrown its maintenance capacity. Several packages lag current Python, NumPy and GPU runtimes, continuous integration has gaps across the platform matrix, and one release sits unshipped behind completed dependency fixes. This post exists to solve these problems. You would report to Professor Chris Eliasmith and work alongside Terry Stewart and Michael Furlong of the National Research Council of Canada, who contribute code review and continuity. All work happens in public repositories through reviewed pull requests. Key responsibilities The funded work plan has seven packages. You would lead the technical work in all of them. * Testing and continuous integration. Rebuild CI across the supported platform matrix, raise automated test coverage, and add property-based tests for the numerical solvers. Establish performance and regression baselines so later improvements are measured rather than asserted. * Release engineering. Restore automated signed releases to PyPI and conda. Refresh packaging, dependency pinning and Python version support. Harden the build pipeline around credential handling and artefact signing. * GPU and accelerator backends. Update NengoOCL for current OpenCL runtimes, GPU drivers and Python versions. * Deep learning integration. Modernize NengoDL against current deep-learning runtimes. * Interactive interface. Broaden NengoGUI compatibility across current browsers, since it is the main entry point for new users. * Models and examples. Update the NengoZoo model and example collections. * Documentation. Consolidate user and maintainer documentation, update the maintainer handbook and contributor guide, record architecture decision records for the core abstractions, and publish machine-readable citation metadata with a versioned DOI per release. Alongside these, you would integrate software composition analysis and static analysis into CI, enable dependency vulnerability monitoring, and help publish a documented vulnerability disclosure procedure. Required qualifications * Training in computer science, engineering, neuroscience, physics, mathematics or a related field. PhD preferred. * Strong Python, with demonstrated fluency in the scientific stack, particularly NumPy and SciPy. * Demonstrated experience maintaining a non-trivial open-source project or research codebase: continuous integration, packaging, releases, issue triage and code review. * Working knowledge of at least one accelerator or deep-learning runtime, such as OpenCL, CUDA, PyTorch, TensorFlow or JAX. * Comfort working in public repositories through reviewed pull requests, with the code and the discussion visible. We are interested in evidence of what you have built and maintained. Preferred qualifications Prior use of Nengo or the Neural Engineering Framework, including through the Nengo Summer School. * Experience with neuromorphic hardware: Intel Loihi, SpiNNaker, BrainScaleS or FPGA targets. * Background in computational neuroscience, cognitive modelling or spiking neural networks. * Supply-chain and software security practice: dependency scanning, static analysis, artefact signing, vulnerability disclosure. * Full stack web development, for the NengoGUI work. * Technical writing for a developer audience, including API and architecture documentation. Terms of appointment Item Detail Classification Research Associate, University of Waterloo Term 11 months, non-renewable under this award Salary $110,000 for the full term Start date December 1, 2026, or as soon as possible thereafter Hours Full time, 1.0 FTE Location Waterloo, Ontario. Hybrid, with a strong preference for candidates who can work from campus regularly. Fully remote within Canada will be considered for an exceptional candidate. Unit Centre for Theoretical Neuroscience, University of Waterloo Supervisor Professor Chris Eliasmith The term is 11 months, which is a condition of the award. The appointment does not include pension participation or insured health benefits, which Waterloo extends to research appointments of one year or more; statutory benefits and vacation pay apply. We are reviewing applications as they arrive. How to apply Send the following to celiasmith(a)uwaterloo.ca, with the subject line "Nengo Research Associate Application": 1. A CV. 2. A link to code you have written or maintained, with one or two sentences on what your contribution was. A public repository, a package you maintain, or merged pull requests to someone else's project all work. 3. A short note, no more than a page, on how you meet the job requirements, and what you would tackle first and why. Applications are reviewed as they arrive and the posting closes when the position is filled. Required disclosures * Compensation. $110,000 for the 11-month term. There is no bonus, commission or other variable compensation attached to this position. * Vacancy status. This posting is for an existing vacancy, newly created by external research funding. * Artificial intelligence. Artificial intelligence is not used to screen, assess or select applicants for this position. * Canadian experience. Canadian work experience is not required. Applicants must be legally entitled to work in Canada by the start date. Applicants will be notified of the outcome within 45 days of their final interview. The University of Waterloo is committed to achieving barrier-free accessibility for persons with disabilities. Applicants who require accommodation during the recruitment process should contact the address above. The University regards equity and diversity as integral to academic excellence and encourages applications from all qualified candidates.

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CFP: FLAIRS40, Neural Network Special Track, St. Pete Beach, FL, May 24-27, 2027
by David B Oct. 26, 2026

Oct. 26, 2026

*Deadlines* Abstract Submission: January 22, 2027 Paper Submission: February 1, 2027 Paper Acceptance Notification: March 9, 2027 Camera Ready Version: April 5, 2027 *Call for Papers* The Florida Artificial Intelligence Research Symposium (FLAIRS) is a medium-sized interdisciplinary AI conference which is noted for its double- blind reviewing, free tutorials, and beautiful venues. This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Papers and contributions are encouraged for any work related to neural networks, data mining, or the intersection thereof. *Topics of interest may include (but are not limited to):* Applications such as Pattern Recognition, Applications, Generative AI methods and applications, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cybersecurity, remote sensing, earth sciences, bioinformatics, and astronomy. Neural networks such as new developments in Deep Learning, Back Propagation, RBF, SVM, Ensemble Methods, Kernel Approaches; Hybrid approaches such as Neural Networks/Genetic Algorithms, Causal Nets trained with Backpropagation, Neural Network/Fuzzy Logic and Acceleration of neural network models via software or hardware. Other modeling algorithms such as hidden Markov models, decision trees, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches; graph modeling, pattern discovery, and anomaly detection; feature extraction and selection; post-processing techniques such as visualization, summarization, or trending; preprocessing and data reduction;and knowledge engineering or warehousing. *Submission Guidelines* Papers must follow the FLAIRS template guidelines ( https://www.flairs-40.info/call-for-papers) and be submitted as a PDF through the EasyChair conference system. (Do NOT use a fake name for your EasyChair login; your EasyChair account information is hidden from reviewers.) FLAIRS will not accept any paper which, at the time of submission, is under review for or has already been published or accepted for publication in a journal or another conference. Authors are also required not to submit their papers elsewhere during FLAIRS's review period. These restrictions apply only to journals and conferences, not to workshops and similar specialized presentations with a limited audience and without archival proceedings. Authors will be required to confirm that their submissions conform to these requirements at the time of submission. *Conference Proceedings* Papers will be refereed and all accepted papers will appear in the conference proceedings. *Track Co-chairs:* David Bisant, Central Security Svcs, bisant(a)umbc.edu Steven Gutstein, Booz Allen Hamilton, s.m.gutstein(a)gmail.com Lenin Mookiah, eBay, lenin.world(a)gmail.com *Program Committee Members:* Martin Atzmueller(University of Kassel, Germany) Lori Bogren (SomaLogic, USA) Ramesh Paudel (Sysco Corporation) Olac Fuentes (University of Texas at El Paso) Masoud Badiei Khuzani (eBay, USA) Tomasz Palczewski (SAP, USA) Chi Weng Cheong (PGIM, USA) Sergei Dolenko (M.V.Lomonosov Moscow State University, Russian Federation) Sheikh Rabiul Islam (University of Hartford, USA) Lawrence Holder (Washington State University, USA) Diane Cook (Washington State University, USA) Jacek Kukluk (Dana-Farber/Harvard Cancer Center, USA) Roberto Santana (University of Basque Country, Spain)

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2nd Workshop on Neuro for AI & AI for Neuro: Towards Multi-Modal Natural Intelligence
by Anton Arkhipov Oct. 25, 2026

Oct. 25, 2026

Dear Colleagues, Join us at the 2nd Workshop on Neuro for AI & AI for Neuro: Towards Multi-Modal Natural Intelligence! The Workshop will be held on February 22-23, 2027, alongside AAAI 2027 in Montreal, Canada. Call for Papers: https://neuroai-multimodal-workshop.github.io/. * Paper submission deadline: November 20, 2026 * Decision notification: December 5, 2026 * Short papers: Up to 4 pages (non-archival, excluding references) * Long papers: Up to 8 pages (archival, excluding references) * References and Supplementary: No page limit Building on the success of our first workshop at AAAI 2026 in Singapore, this edition will bring together researchers in AI, computational neuroscience, and neuromorphic engineering to explore how brain insights can inspire more adaptive, efficient, and robust AI systems, and how AI can deepen our understanding of neural computation. This year, we’ll place a special emphasis on context-dependent learning, continual adaptation in foundation models, and open-source benchmarks bridging neuroscience and AI. We look forward to bringing the community together again! Organizing team: Asim Iqbal, Shinya Ito, Reza Abbasi-Asl, Sophia Sanborn, Anton Arkhipov Anton Arkhipov Investigator [cid:2B7F5AD4-00BE-422F-8184-42BF1C16DEE3]

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2 PhD positions in translational computational neuroscience and NeuroAI at ICNS Hamburg, Germany
by Claus C. Hilgetag Oct. 25, 2026

Oct. 25, 2026

Dear colleagues, We invite applications for two PhD positions at the Institute of Computational Neuroscience (ICNS), University Medical Center Hamburg-Eppendorf (UKE), Germany: Translational computational neuroscience: Combining game theory, network neuroscience and computational modelling to investigate how brain regions and their interactions contribute to behaviour, impairment and recovery after stroke. The project will develop and validate approaches based on Multiperturbation Shapley value Analysis, in collaboration with project partners in Ghent, Paris and Amiens. Supervision by Claus Hilgetag. Details and application: UKE vacancy J000007015 <https://uke.jobs/index.php?ac=jobad&id=7015> Computational neuroscience and NeuroAI: Investigating how biological connectivity principles shape computation in recurrent neural networks and reservoir computing models. The project will explore characteristic bio-inspired network architectures for temporal and multimodal learning. Joint supervision by Fatemeh Hadaeghi and Claus Hilgetag. Details and application: UKE vacancy J000007013 <https://uke.jobs/index.php?ac=jobad&id=7013> We welcome applicants with a Master’s degree in computational neuroscience, computer science, physics, mathematics, biomedical engineering or related fields. Strong quantitative and programming skills, proficiency in Python, scientific initiative and fluent English are expected. Demonstrations of prior independent scientific achievements are an advantage. Both positions offer opportunities for independent research within an international, interdisciplinary group, with access to high-performance computing and support for conferences and training. Application deadline: 2 November 2026. Please apply through the respective UKE recruitment pages, which provide full requirements and application instructions. Please feel free to share this announcement with interested candidates. Best wishes, Claus C. Hilgetag Institute of Computational Neuroscience University Medical Center Hamburg-Eppendorf, Germany

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World wide VVTNS series (7th season): October 28 2026 | Circuit Mechanisms of Sensorimotor Learning in the Cortico-Basal Ganglia-Thalamocortical Network | Arthur Leblois CNRS, IMN Bordeaux, France
by David Hansel Oct. 25, 2026

Oct. 25, 2026

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the lecture Arthur Leblois CNRS, IMN Bordeaux, France on the topic of *Circuit Mechanisms of Sensorimotor Learning in the Cortico-Basal Ganglia-Thalamocortical Network* The lecture will be held on Zoom on October 28, 2026 at *11:00 am ET * > To receive the link: https://www.wwtns.online/register-page > *Please pay attention to the time change!* Europe has switched to winter > time whereas the United States will switch on November 1. > > As a result, the seminar will begin at *11:00 a.m. EDT, which corresponds > to 4:00 p.m. CET*, rather than the usual 5:00 p.m. in Europe. > *Abstract: * The basal ganglia (BG) are essential for learning and adapting movements, yet their output is often unnecessary for executing well-learned actions. This paradox challenges existing models of BG function. I will present a biologically grounded model of the cortico-BG-thalamocortical loop, showing how this closed-loop network supports efficient motor adaptation and early movement acquisition. In our model, dopamine-driven plasticity, recurrent cortical dynamics, and feedback from the BG together shape motor output, even when BG output is not directly required for execution. This work provides a unified framework explaining how the BG-cortical circuit contributes to both learning and refinement of goal-directed actions. One important assumption of the model is that parallel feedback loops in the BG-cortical circuits form functional channels driving specific motor output, and I will show recent analysis of neuronal activity in the song-related circuit of zebra finch supporting this assumption.

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Discussion manuscript: validating pre-attack neural signals and their external EEG correlates
by נתי שטרן Oct. 25, 2026

Oct. 25, 2026

Dear computational neuroscience colleagues, I would welcome methodological feedback on a new discussion manuscript: A framework for validating neural signals before aggressive behavior in animal models relevant to autism and schizophrenia https://github.com/netanelcyber/psi-qeeg-bis/blob/6b79e9c39cd0532202659acbb… The central question is whether activity preceding an observed attack in an awake animal contains information that can be recovered from simultaneous external EEG and used to forecast future attacks beyond behavior, EMG and movement measurements. The proposal considers controls, ASD-relevant, SCZ-relevant and combined experimental conditions. It does not claim that animals have the corresponding human diagnoses; the combined condition requires its own construct validation. The analysis separates baseline differences, ongoing-action correlates and genuine pre-event prediction. Feedback would be particularly valuable on depth-to-surface signal mapping, latent-state models, causal preprocessing, animal-level holdout, calibrated warning probabilities, and false alarms per hour during continuous recording. Relevant existing synchronized depth/EEG/video datasets would also be helpful. This AI-assisted manuscript is a hypothesis and proposed validation framework. It contains no new experimental data, trained predictor or validation results, and has not been peer reviewed or accepted by a preprint server. AI assistance and pending author disclosure fields are stated in the draft. Please send comments privately to nsh531(a)gmail.com. Best regards, Netanel Stern Independent researcher, Israel

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Postdoctoral Position in Computational/Theoretical Neuroscience at UC San Diego
by Marcus Benna Oct. 23, 2026

Oct. 23, 2026

A postdoctoral position in computational neuroscience with flexible start date is available in the lab of Dr. Marcus Benna <https://biology.ucsd.edu/research/faculty/mbenna> at the University of California, San Diego. Our research seeks to understand how neural information processing under noisy and resource-constrained conditions allows the brain to efficiently perform computational tasks and control relevant behaviors. This position <https://biology.ucsd.edu/jobs/postdoc#postdoctoral-position-computationalth…> will involve the analysis of neural activity data (calcium imaging or electrophysiology) collected by our collaborators, as well as theoretical modeling of learning and task performance in neural networks. Our research group <https://bennalab.biosci.ucsd.edu/> is part of the vibrant Department of Neurobiology at UCSD, which is highly collegial, and offers many opportunities for collaborations, both formal and informal. Postdoctoral trainees are encouraged to attend seminars and present their work at departmental events. Our group is located in Tata Hall and shares space with several experimental neuroscience laboratories. We offer a stimulating environment with opportunities to develop new research directions and supportive mentorship for individual career development. The applicant should hold a PhD in computational neuroscience, physics, applied math, computer science, data science, or a related field, preferably with a degree date no more than two years before the start date. Candidates should have a strong quantitative background and programming skills. Experience in computational modeling, machine learning and/or data analysis is necessary for this position. Strong verbal and written communication skills are required. We’re looking for collaborative, motivated individuals who can conduct an independent research project and work as part of a team. To apply, please email Dr. Marcus Benna (mbenna(a)ucsd.edu) with the subject line “Postdoc Application”, and include - A cover letter/research statement that summarizes your experience, contributions to science, as well as research interests and how they align with the lab’s work. - CV with publication list - Names and contact information of 3 references Review of applications will begin on Nov. 13th. Best, Marcus ========================== Marcus K. Benna Assistant Professor Department of Neurobiology School of Biological Sciences University of California, San Diego

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Postdoc position in retina computational modeling applied to psychiatry at LORIA, Nancy, France
by Laure Buhry Oct. 22, 2026

Oct. 22, 2026

A postdoctoral position is available at LORIA (Laboratoire Lorrain de Recherche en Informatique et ses Applications), Nancy, France, in the Neurorhythms (https://neurorhythms.loria.fr/) team on the MERGES ( https://piq.inria.fr/projets/#merges https://piq.inria.fr/en/projets/#merges) project funded by the Inria Quadrant Programme. The work will be conducted in collaboration with experimentalists at Christophe Ribelayga's lab, University of Houston, TX, and clinicians at Steven Silverstein's lab, University of Rochester, NY. The aim of this project is to test pathophysiological hypotheses in schizophrenia spectrum disorders and to identify novel therapeutic targets through physiologically realistic modelling of retinal signalling, used as a peripheral window into brain function. The postdoctoral fellow will contribute to computational modeling of retinal circuits and to hypothesis-driven analyses, including short research stays at our collaborating laboratory in the United States. *Start date* : as soon as possible. *Contract duration* : 2 years, with possible renewal of 1 year contingent on successful annual review of the programme. *Monthly gross salary* : 2948 € (French salary scale) *Qualifications:* Prior experience with computational neuroscience is required, in particular with conductance-based models. Prior knowledge and practice in scientific computing, signal analysis or applied mathematics is preferred. A strong interest in retinal functioning and applications in Psychiatry is mandatory. *Application:* Prospective postdocs can contact laure.buhry(a)loria.fr for more detailed information, or directly send a CV and short statement of interest for application. -- Laure Buhry https://members.loria.fr/LBuhry/

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Fully-funded Research Assistant position in Neuroimaging studies at University of South Carolina
by Z S Oct. 22, 2026

Oct. 22, 2026

Dear all, Description: Dr. Sha’s lab (https://shazhiqiang.wixsite.com/sha-lab) at the University of South Carolina is seeking *a fully-funded Research Assistant*. Our lab is affiliated with the Carolina Autism & Neurodevelopment Center, the Institute for Mind & Brain, and working closely with the McCausland Center for Brain Imaging in Columbia, the center of SC Metropolitan Statistical Area. Our lab explores the mechanisms of atypical brain development and neurodevelopmental disorders (e.g., autism spectrum disorders) by leveraging computation modeling to bridge neural circuitry, exposure (e.g., early life adversity) and psychopathological phenotypes, and treatment outcomes. These innovative projects will leverage state-of-the-art computational models, supported by the Brain Imaging Center (with 3T and high-field 7T MRI scanners) and the Biobehavioral Research Center. This position provides an excellent opportunity for a self-motivated student to gain hands-on experience with neuroimaging (e.g., MRI) and computational modeling, making it ideal preparation for a future graduate or medical career. Research Assistant will be actively involved in the scientific process and are encouraged to contribute meaningfully to publications. We fully support research assistants in leading first-author publications and presenting their work at international conferences. Duties: · Computational modeling; statistical modeling · MRI data collection, processing, analysis; present results and publish papers · Manage daily administrative operations of the lab (e.g., scheduling and communication) Requirements: · Bachelor’s degree in a relevant science (e.g., neuroscience, math, biostatistics, biomedical engineering and etc.) · Experience with clinical and MRI data collection and data analysis. · Candidates with coding experience are preferred. How to apply: Please submit your CV to Dr. Sha (zsha(a)mailbox.sc.edu)

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Fully funded lab manager position on social neuroscience lab
by Speer, Sebastian Oct. 21, 2026

Oct. 21, 2026

We’re hiring a full-time lab manager/research assistant to join the Coupled Minds Lab at Texas A&M University! Our lab, led by PI Sebastian Speer, studies how conversations shape the way people connect, change their minds, and learn. We combine fMRI hyperscanning, natural language processing, and computational modeling to investigate how people explore ideas together and build consensus in interactions with human and AI partners. The lab manager will help lead data collection for fMRI hyperscanning studies, analyze naturalistic fMRI data and conversation transcripts, and apply computational methods to study social interaction. This position offers hands-on research experience for someone considering a PhD in psychology or neuroscience. Qualifications: A bachelor’s degree in psychology, neuroscience, computer science, or a related field is required. Prior research experience is preferred. Salary: $45,000 per yearLocation: College Station, TexasStart date: As soon as possible Applications will be reviewed on a rolling basis until the position is filled. Apply here: https://tamus.wd1.myworkdayjobs.com/TAMU_External/job/College-Station-TX/Re… Learn more about the lab: https://coupled-minds.github.io/ --- Sebastian Speer Assistant Professor Psychological & Brain Sciences Texas A&M University

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PhD and postdoc positions: PDEs + TDA + deep learning for 3D+time microglia morphology (Prague and Warsaw)
by Hahn, Jooyoung Oct. 21, 2026

Oct. 21, 2026

Dear Colleagues, The MIND-MAP project (2027-2029), a collaboration of CTU in Prague, the University of Warsaw and ISTA Austria, is hiring one PhD student and one postdoc in Prague and one PhD student and one postdoc in Warsaw (Pre-announcement). MIND-MAP studies how microglia, the immune cells of the brain, change their branching shape in 3D + time microscopy, and turns these images into a quantitative, geometric and topological readout of brain state. Both groups work closely with Sandra Siegert's lab at ISTA, with access to unique 3D and 3D + time microscopy data. The goal is to develop new mathematics, not merely to apply existing tools. In Prague (CTU in Prague, FNSPE, with Jooyoung Hahn), the work covers dimensionality reduction, hybrid PDE + deep-learning segmentation, scale-aware 3D shape representations, tracking in 3D + time, and geometry-informed TDA. In Warsaw (University of Warsaw, with Pawel Dlotko), it covers topological descriptors of shapes that change in time, shape trajectories, Ball Mapper and interpretable visualization. We are looking for candidates with a strong background in (applied) mathematics, computer science, physics or a related field, and a strong interest in biology. Postdoc candidates should have experience in one of the following areas: numerical PDEs, image segmentation, deep learning, TDA or geometry Prague salary: postdoc 70,000 CZK gross per month, full time, start 1 January 2027 (negotiable); PhD 38,745 CZK gross per month (0.8 FTE) plus a 12,000 CZK tax-free stipend (about 43,000 CZK net), start 1 March 2027. To apply, send a CV and a few lines about your research interests and what you can bring, and say whether you apply for the PhD or the postdoc: * Prague: jooyoung.hahn(a)fjfi.cvut.cz (PhD by 5 December 2026) https://jooyounghahn.github.io/jobs/MIND-MAP_PhD_CTU_Prague.html * Warsaw: p.dlotko(a)uw.edu.pl https://jooyounghahn.github.io/jobs/MIND-MAP_PhD_Postdoc_Warsaw.html This is a pre-announcement; the official calls with formal conditions will be published separately. Feel free to email us with questions. Best, Jooyoung Hahn Assistant Professor Faculty of Nuclear Sciences and Physical Engineering Czech Technical University in Prague jooyoung.hahn(a)fjfi.cvut.cz

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[Job] Research Software Engineer at CatalystNeuro (remote)
by Ben Dichter Oct. 21, 2026

Oct. 21, 2026

Dear colleagues, CatalystNeuro <http://catalystneuro.com> is hiring a Research Software Engineer to help neuroscience labs convert their data to Neurodata Without Borders (NWB) and publish it on the DANDI Archive. Each project starts with a lab's own acquisition systems, file formats, and analysis outputs, and ends with a standardized, well-documented dataset that others can reuse. The work is roughly evenly split between building conversion pipelines for specific labs and improving the open-source tools those pipelines are built on, including NeuroConv, PyNWB, and the NWB Inspector. We rely heavily on agentic LLM-based development in this work. We use coding agents such as Claude Code to read unfamiliar formats, draft conversion code, and run tests, with engineers directing the agents and reviewing what they produce. We are looking for someone with strong Python skills, experience with neuroscience data or a related field, and hands-on experience developing software with coding agents. Prior experience with NWB, DANDI, or SpikeInterface is helpful but not required. The position is remote, and we ask for several hours a day of overlap with European working hours. It can be a contract paid hourly at $60 to $75 per hour depending on experience, at anything from 25 hours per week up to full time. For candidates based in the United States, we are also open to a full-time salaried position with benefits at $95,000 to $120,000 per year. To apply, please email info(a)catalystneuro.com with the subject line "Application: Research Software Engineer" and include your CV, a link to your GitHub profile or another code sample, and a short note answering two questions: describe a dataset you have worked with and what made it difficult to handle, and describe how you have used coding agents in your work, including a time an agent got something wrong and how you caught it. We will begin reviewing applications on November 10, 2026. The full listing is at https://catalystneuro.com/openings/research-software-engineer/. Best regards, Ben Dichter CatalystNeuro

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Tenure-track position in Computational Neuroscience at Yale
by daniel.levenstein＠yale.edu Oct. 21, 2026

Oct. 21, 2026

Dear colleagues, The Department of Neuroscience at Yale is hiring tenure-track faculty in computational or theoretical neuroscience. We’re especially interested in candidates who use computational methods to link models with experimental data, broadly construed: from analysis of neural activity and network modeling to imaging, bioinformatics, and molecular modeling. New faculty join a growing computational community spanning the Department of Neuroscience, the Wu Tsai Institute, the Kavli Institute for Neuroscience, and the Department of Biomedical Informatics and Data Science, with a generous start-up package and ongoing salary support. More information on the position and application can be found at Interfolio: https://apply.interfolio.com/190740. Review is rolling, with priority for applications received by November 30, 2026. Please feel free to reach out to me directly with questions about the department and community here at Yale! Best, Dan ________________________________ Daniel Levenstein, PhD Assistant Professor - Department of Neuroscience Wu Tsai Investigator - WTI Center for Neurocomputation and Machine Intelligence Quantitative Biology Institute (QBio) Yale University 100 College Street, Room 1130 New Haven, CT 06510 www.levensteinlab.org

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Research Assistantship (pre-doctoral route) position in NeuroAI in Coimbra, Portugal
by Jorge Almeida Oct. 21, 2026

Oct. 21, 2026

Dear colleagues, We are recruiting a Research Assistant with a Master’s degree (this is a requisite) to join the newly funded ALIGN project, supported by the CMU Portugal / FCT Initiative. The position will be based at the University of Coimbra, working with Jorge Almeida and in close collaboration with Michael Tarr at Carnegie Mellon University. The project sits at the intersection of NeuroAI, cognitive neuroscience, computer vision, and human-centered AI, and aims to understand how visual representations in AI models align with human behavioral and neural representations. The selected candidate will contribute to behavioral and neuroimaging research, AI model evaluation, and representational analyses involving vision and vision-language models such as CLIP, DINO, ResNet, and ViT. This is an excellent opportunity for someone interested in developing a research profile in NeuroAI and potentially continuing into a PhD in this area. The position is funded through a Master’s research fellowship, with a monthly stipend of €1,359.64, tax-free (as dictated by the Portuguese Government). The contract will be for the duration of the project – expected 1 year - although we expect the candidate to apply together with the team to a PhD fellowship to continue the project. We are looking for candidates with interests in one or more of the following areas: - Cognitive neuroscience or psychology - Artificial intelligence, machine learning, or computer vision - Neuroimaging, especially fMRI - Data analysis, Python programming, or computational modeling - Human perception, categorization, or visual cognition Interested candidates should send a CV, a brief statement of interest, and contact information for references to: jorgecbalmeida(a)gmail.com Please feel free to share this opportunity with anyone who may be interested. Best, Jorge Almeida University of Coimbra ALIGN Project | CMU Portugal / FCT Initiative

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on behalf of Greg Reynolds: position in Music, Science and Health at Knoxville
by Reinoud Maex Oct. 20, 2026

Oct. 20, 2026

Begin forwarded message: From: "Reynolds, Greg" <greynol3(a)utk.edu<mailto:greynol3@utk.edu>> Subject: Request to post job ad to listserv Date: 16 October 2026 at 16:54:30 BST To: "comp-neuro-owner(a)lists.cnsorg.org<mailto:comp-neuro-owner@lists.cnsorg.org>" <comp-neuro-owner(a)lists.cnsorg.org<mailto:comp-neuro-owner@lists.cnsorg.org>> You don't often get email from greynol3(a)utk.edu<mailto:greynol3@utk.edu>. Learn why this is important<https://aka.ms/LearnAboutSenderIdentification> Please post to the listserv this job ad for an open position as Assistant/Associate/Full Professor of Music, Science, and Health, Natalie L. Haslam College of Music at the University of Tennessee, Knoxville. The Natalie L. Haslam College of Music invites applications for a 9-month tenure-track position at the Assistant, Associate, or Full Professor level in Music, Science, and Health. This is a rare and forward-looking appointment designed for a scholar-teacher who believes that a fuller understanding of music — how we hear it, perform it, feel it, analyze it, and create it — is enriched by understanding the human brain, human behavior, and the science behind how we interact with the art of music and human health. The successful candidate will occupy a distinctive role at the intersection of music, medicine and health, neuroscience, psychology, cognitive science, or other theoretical and applied sciences, contributing to both the core curriculum of the College and to an emerging cross-disciplinary research culture. The candidate will work in the Natalie L. Haslam College of Music with potential for collaboration with other colleges, and relevant health organizations. The successful candidate is expected to have either existing or strong potential for obtaining extramural funding. More information and application materials can be found here: https://apply.interfolio.com/194546<https://apply.interfolio.com/194546> ______________________________________ Greg D. Reynolds, Ph.D. Professor Department of Psychology & Neuroscience University of Tennessee, Knoxville http://dcnlab.utk.edu<http://dcnlab.utk.edu>

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Faculty position in Computational Neuroscience at Boston University
by Emily Stephen Oct. 19, 2026

Oct. 19, 2026

The Boston University Department of Mathematics and Statistics is recruiting an Assistant Professor of Computational Neuroscience as part of Boston University’s Advancing Brain and Cognitive Health convergent search—part of a new University-wide approach to convergent research. The convergent search will involve up to 6 tenure-track faculty hires. Going beyond traditional interdisciplinary collaboration, convergent research intentionally brings together different disciplines, methods, and ways of thinking to tackle complex challenges and open new directions for discovery. Faculty joining this cluster will have opportunities to build collaborations across neuroscience, computation, engineering, and health sciences to pursue ambitious questions about the brain and cognitive health. Learn more about the position and the other openings in the convergent search: https://bit.ly/4hP8ya0 Best, Emily Stephen

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PhD and postdoc positions in computational and theoretical neuroscience || University of Texas at Dallas
by Muller, Lyle Oct. 19, 2026

Oct. 19, 2026

PhD and postdoctoral positions are available in a growing cluster of computational neuroscience labs at the University of Texas at Dallas. The Muller Lab (http://mullerlab.io<http://mullerlab.io/>) and the Lakshminarasimhan Lab (https://neuralalgorithms.github.io<https://neuralalgorithms.github.io/>) are recruiting new trainees in computational and theoretical neuroscience. PhD positions start in Fall 2027. Postdoctoral start dates are flexible. Research across the cluster combines computational analysis of neural data, applied mathematics, and machine learning to understand computation in biological and artificial neural networks in close collaboration with experimental groups. Projects in the Muller Lab include traveling waves in neural systems (link<https://www.nature.com/articles/s41467-023-39076-2>) and analyses of spikes in large neural populations (link<https://arxiv.org/abs/2412.03804>). The group has an active collaboration with the Fields Institute through the Lab for Network Computation<https://www.fields.utoronto.ca/activities/fields-lab-network-computation>. The Lakshminarasimhan Lab develops computational theories of learning, memory and decision-making that link synaptic plasticity, neural dynamics and behavior. Ongoing projects in the lab include developing and testing normative theories of dopamine signaling (link<https://www.biorxiv.org/content/10.1101/2025.03.18.643990v2.full>) and representational drift. The two labs are building shared training in computational neuroscience and NeuroAI at UTD. Trainees will join a growing computational neuroscience community in the Dallas area, including connections to UT Southwestern and the Texas Artificial Intelligence Research Institute (TAIRI). Prior experience with scientific computing, signal analysis, applied mathematics, or machine learning is preferred. Prospective PhD students should apply to the Cognition and Neuroscience PhD program at UTD (link<https://bbs.utdallas.edu/departments/neuroscience/graduate-programs/cogniti…>) before December 1, 2026. Prospective postdocs can write to lyle.muller(a)utdallas.edu or kaushik.laksh(a)utdallas.edu with a CV and short statement of interest. -- Lyle Muller http://mullerlab.io

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Faculty position in computational neuroscience || University of Texas at Dallas
by Muller, Lyle Oct. 19, 2026

Oct. 19, 2026

The Department of Neuroscience at the University of Texas at Dallas invites applications for a tenure-system faculty position at the Assistant or Associate Professor rank in computational neuroscience, starting Fall 2027. The position is part of a cluster hiring initiative to build an internationally recognized computational neuroscience research and training program at UT Dallas. We are looking for candidates with expertise in neural coding, computation and dynamics, or working at the intersection of neuroscience and artificial intelligence, including large language models. The ideal candidate would do highly collaborative dry-lab research connected to departmental strengths in learning and memory, decision making, motor control, affective neuroscience, sensory perception and pain, or neurogenomics. The position includes teaching undergraduate and graduate courses. Applicants should have a PhD or equivalent in neuroscience, computer science, mathematics or a related field. The new hire will join a rapidly growing computational neuroscience cluster at UTD, with close ties to the Texas Artificial Intelligence Research Institute (TAIRI), the Texas Biomedical Device Center, and UT Southwestern Medical Center. Full position description and application: https://jobs.utdallas.edu/postings/32729. Priority will be given to applications received by December 31, 2026. -- Lyle Muller http://mullerlab.io

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World wide VVTNS series: Seventh season opening lecture, Wednesday, October 21, 2026, at 11:00 am EDT - Richard Hahnloser, ETH Zurich
by David Hansel Oct. 18, 2026

Oct. 18, 2026

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the seventh season opening lecture of the online VVTNS series. It will be delivered by Richard Hahnloser ETH Zurich on the topic of The Algorithm(s) of Birdsong Learning The lecture will be held on zoom on October 21, 2026, at *11:00 am EDT * To receive the link: https://www.wwtns.online/register-page *Abstract: *How do songbirds acquire and refine their complex vocal repertoires? Learning a song requires both evaluating sensory evidence and determining which changes in behavior improve performance. These challenges have traditionally been studied in separate experimental paradigms: auditory-feedback adaptation, reinforcement learning, and imitation. In this talk, I will examine the behavioral and neural algorithms underlying each and ask how they might fit within a common learning architecture. First, when auditory feedback is shifted in pitch, birds change their vocal pitch in the opposite direction. As in humans, compensation is typically incomplete and becomes proportionally smaller for larger shifts. This pattern is consistent with Bayesian causal inference: birds combine internal predictions of pitch with auditory evidence while discounting feedback that is unlikely to have been self-generated. Second, I will show why classical policy-gradient reinforcement learning falls short in explaining the nonlinear pitch trajectories observed in conditioning experiments. A normative extension accounts for these trajectories and aligns with the modular organization of the brain’s song-control system. In this architecture, a learning component generates exploratory variation and is updated by reward. Other components contribute to motor output but are not updated by reward on every trial. Third, I will turn to imitation learning. Songbirds simplify this computational challenge by acquiring vocal units—syllables—independently of their sequential order. The intrinsic reward guiding the acquisition of this vocal inventory can be characterized by a simple sum–max rule: each target syllable contributes a partial reward determined by its best pitch match among the bird’s developing vocalizations, and these rewards are summed across targets. A light-tailed pitch-similarity function ensures that large mismatches contribute little reward. Together, these findings identify complementary mechanisms for interpreting sensory feedback, assigning credit to motor actions, and matching vocal output to remembered targets. The next challenge is to explain how these mechanisms interact within a unified theory of birdsong learning. I will conclude with initial attempts to use AI to develop this synthesis, with the aim of turning a collection of task-specific algorithms into a coherent framework with testable predictions and potential relevance beyond the avian brain. ᐧ

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AICES 2027: early registration October 27
by David Silva - IRDTA Oct. 17, 2026

Oct. 17, 2026

******************************************************** 2nd INTERNATIONAL SCHOOL ON HUMAN-AI COLLABORATION IN THE ERA OF AGENTIC AI AICES 2027 Bilbao, Spain May 3-6, 2027 https://aices.irdta.eu/2027/ ******************************************************** Co-organized by: University of Deusto IRDTA – Institute for Research Development, Training and Advice ******************************************************** Early registration: October 27, 2026 ******************************************************** SCOPE The rapid emergence of agentic AI systems capable of planning, reasoning, making decisions and acting with increasing autonomy is transforming the relationship between humans and intelligent machines. Understanding how humans and AI agents can collaborate effectively, safely and responsibly has therefore become a major scientific, technological and societal challenge. AICES 2027 will address this challenge from a broad interdisciplinary perspective, bringing together leading researchers and experts from academia and industry. The scientific program will examine the societal, cognitive, ethical, economic and governance dimensions of agentic AI, with particular emphasis on human–AI collaboration, trust, human oversight and control, the future of work, regulation and governance, explainability, responsible AI, education, democracy, media ecosystems, economic transformation, and the wider implications of increasingly autonomous AI systems. The school will feature 13 monographic three-hour courses, 2 keynote lectures, 1 round table and 1 symposium. Leading academics and industry experts will share their knowledge, research and perspectives with participants. Interaction, discussion and networking will be central elements of the event, while full live online participation will also be available. ADDRESSED TO AICES 2027 is intended for graduate students, researchers, academics, industry professionals and policymakers from a wide range of disciplines, including computer science, cognitive science, economics, sociology, philosophy, law, public policy and business. There are no formal academic prerequisites, and researchers and professionals at all career stages are welcome. The school will provide participants with an opportunity to gain in-depth knowledge of one of the most rapidly evolving areas of AI, interact with experts from different disciplines, establish new collaborations, expand their professional networks, and explore the profound changes that agentic AI may bring to work, institutions and society. VENUE AICES 2027 will take place in Bilbao, in northern Spain. Once a major industrial centre, Bilbao has undergone a remarkable urban, cultural and economic transformation over recent decades and is today one of Spain's most dynamic cities. The venue will be: University of Deusto Avenida de las Universidades, 24 48007 Bilbao https://www.deusto.es/ STRUCTURE Two/three courses will run in parallel throughout the event. Participants will be free to select the sessions they wish to attend and may move between courses at any time. In addition to the courses and keynote lectures, the program will include a round table and a symposium devoted to current research and industrial developments. All lectures will be video recorded and made available to participants for 45 days after the event. Full live online participation will be possible. Nevertheless, participants are strongly encouraged to attend in person whenever possible, as direct interaction, discussion and networking are essential components of research training events of this kind. KEYNOTE SPEAKERS Eszter Hargittai (University of Zurich), Myths vs. Measures: Digital Inequality and AI Skills Katia Sycara (Carnegie Mellon University), Human-AI: Collaboration rather than Substitution PROFESSORS AND COURSES Ana Bazzan (University of São Paulo), [introductory/intermediate] Autonomous Agents, Multiagent Systems, Swarm Intelligence and Reinforcement Learning: What Are These and Why They Matter in the Current AI Agenda Justine Cassell (Inria Paris), [introductory/intermediate] Building Agents that Collaborate with People rather than Replacing Them Pierre Dillenbourg (Swiss Federal Institute of Technology Lausanne), [introductory] Productive Noise: The Benefits of Misunderstandings in Collaboration Steven Drucker (Particle Prismatics LLC), [introductory/intermediate] Attention Is All You Have: Human-Centered AI in the Agentic Era Peter Flach (University of Bristol), [introductory/intermediate] Classifier Calibration: A Prerequisite for Trustworthy AI James Hollan (University of California San Diego), [intermediate] The Future of HCI: Generative AI, Negotiated Agency, and Co-Adaptive Systems Andreas Holzinger (University of Natural Resources and Life Sciences), [introductory/intermediate] Trustworthy Agentic AI: Human-AI Collaboration, Explainability, and Verifiable Autonomy Jason Hong (Carnegie Mellon University), [introductory/intermediate] Challenges in Human-AI Interaction Christian Lebiere (Carnegie Mellon University), [intermediate] Metacognition and Theory of Mind in Humans and Machines Sijia Liu (Michigan State University), [introductory/advanced] Safety Alignment for AI Agents: From Centralized to Distributed Solutions Simon Parsons (University of Lincoln), [introductory] Agents and Agentic AI Simone Stumpf (University of Glasgow), [introductory/intermediate] Explainable AI (XAI) and Debugging in the Era of Agentic AI Lyle Ungar (University of Pennsylvania), [introductory] From Tools to Teammates: How AI Changes Human Work and Relationships SYMPOSIUM A symposium will give participants, research groups and companies the opportunity to present ongoing research projects, innovative ideas and industrial developments related to the themes of AICES 2027. Presentations will consist of 15-minute oral contributions. Participants interested in presenting should submit a one-page abstract including the title, authors, and a brief summary to david(a)irdta.eu. Submission deadline: April 19, 2027. ORGANIZING COMMITTEE Pablo García Bringas (Bilbao, Local Chair) Carlos Martín-Vide (Tarragona, Program Chair) Santiago Montes (Tarragona, Webpage) Sara Morales (Luxembourg, Finances) David Silva (London, Organization Chair) REGISTRATION Registration is available at: https://aices.irdta.eu/2027/registration/ During registration, participants will be invited to indicate six courses they are particularly interested in attending. This selection is tentative and non-binding and will be used only to estimate demand and facilitate logistical planning. As the capacity of the venue is limited, registrations will be accepted on a first-come, first-served basis. Registration will close once maximum capacity has been reached. Early registration is therefore strongly recommended. FEES Registration fees include access to all school activities and lunches. Several early-registration deadlines are available, with fees depending on the date of payment. Fees are the same for on-site and for online participation. ACCOMMODATION Accommodation suggestions will be made available in due time at: https://aices.irdta.eu/2027/accommodation/ CERTIFICATE Participants will receive a certificate documenting 40 hours of academic activities. This certificate should be suitable for participants seeking ECTS or equivalent academic recognition from their home institutions. SPONSORS Companies, institutions and organizations interested in supporting AICES 2027 are invited to consult the sponsorship opportunities available for the event. The sponsorship leaflet can be downloaded from: https://aices.irdta.eu/2027/sponsors/ QUESTIONS AND FURTHER INFORMATION david(a)irdta.eu ACKNOWLEDGMENTS University of Deusto IRDTA – Institute for Research Development, Training and Advice

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Göttingen Symposium "Living Networks": Nov 30-Dec 2 2026
by Priesemann, Viola Oct. 17, 2026

Oct. 17, 2026

Dear all, Please spread the word: This symposium is interesting to anyone wanting to understand the similarities and difference in network dynamics across sociology, (animal) group behavior and living neural networks. It is free of charge and we have a great international speakers. Best wishes, Viola Dear colleagues, We are pleased to announce "Living Networks" - an international symposium on self-organization, manipulation, and information flow in neural and social systems. We bring together experts on adaptive networks from societal dynamics, animal groups, living neural networks, and complex systems. Please share this announcement with interested colleagues, students, group members, and collaborators. We warmly welcome you to Göttingen - free of charge. Dates: 30 November–2 December 2026 Venue: Manfred-Eigen-Hörsaal, Am Fassberg 11, 37077 Göttingen, Germany 🔗 More information and registration (free of charge): https://priesemann-group.github.io/living-networks/ The symposium poster is available for download here: https://owncloud.gwdg.de/index.php/s/LCp1TDN87tWHRG6 We look forward to welcoming you to Göttingen. Best wishes, From the organization team: Julia Fischer, Greta Jasser, Thomas Kneib, Piklu Mallick, Viola Priesemann Living Networks: Self-Organization, Manipulation and Information Flow in Neural and Social Systems Abstract Living Networks, including societies, groups and also brains, are continuously reshaping their structure, interactions, and information flow among nodes - yet their large-scale structure and function remain largely invariant. Classic examples are scale-free network properties and robust information processing despite variable neural representation. We want to explore whether these networks are shaped by similar self-organization principles, show similar emergence of robustness and resilience, and are potentially also vulnerable tosimilar manipulation mechanisms. By combining the perspective of complex systems with expertise from sociology and neuroscience, our aim is to identify common principles, but also core differences, that drive the emergence of structure, dynamics, and information flow - from neural networks to societal dynamics. Background: From November 30 to December 2nd, 2026, at the University of Göttingen, we bring together international experts across disciplines - including physics, data science, neuroscience, law, and social and political sciences. With invited and contributed talks, ample time for discussions and poster presentations, we will sharpen our understanding of how self-organization mechanisms drive structure and information flow in social networks, as well as neural networks, with implications for understanding disinformation, polarization, and societal resilience. The symposium is organized by the CIDAS Section "Complexity, Information, Cognition, Society" (CICS), funded by the University of Göttingen, and aims to foster future collaborative research initiatives across disciplines. _____________________ Prof. Dr. Viola Priesemann Max Planck Institute for Dynamics and Self-Organization & Georg-August-University Göttingen Am Fassberg 17, 37077 Göttingen viola.priesemann(a)ds.mpg.de<mailto:viola.priesemann@ds.mpg.de> https://priesemann-group.github.io<https://priesemann-group.github.io/>

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[Invitation] rTAIM Seminar #31 | John Dorsch — Epistemically Trustworthy AI & Collective Accountability | 23 October 2026
by steven gouveia Oct. 16, 2026

Oct. 16, 2026

[??] UPCOMING SEMINAR | rTAIM SEMINAR SERIES #31 [??] Why We Need Epistemically, Not Morally, Trustworthy AI: Decision Support and the Need for Collective Accountability [???] Speaker: John Dorsch (Center for Environmental and Technology Ethics — Prague) [??] Date: 23 October 2026 (Friday) [??] Time: 3:00–4:30 PM (Lisbon Time) [??] Format: Online | Microsoft Teams [??] Free and Open to Everyone! Can artificial intelligence really be trustworthy? And who should be held accountable when AI influences human decisions? The discussion will explore crucial questions concerning AI-assisted decision-making, epistemic trust, institutional accountability, and the implications of the EU AI Act. Join us for the 31st seminar of the Rebuilding Trust in AI Medicine (rTAIM) series, featuring John Dorsch, a researcher specialising in AI Ethics and Philosophy of Cognitive Science. Short bio: John Dorsch is a postdoctoral researcher in AI Ethics and Philosophy of Cognitive Science. Previously, he worked at Ludwig Maximilian University (LMU) Munich in the interdisciplinary institute Munich Interactive Intelligence Initiative (MI3), member of the lab Cognition, Values, and Behavior (CVBE). His research focuses on philosophical and scientific problems surrounding metacognition, as well as AI technology exerting an influence on metacognitive capacities, whether by enhancing or hijacking them. [??] Seminar details and access: https://teams.microsoft.com/meet/348952916094000?p=fPGkR9WtycP2UVboJD ID: 348 952 916 094 000 Password: tp9aU3Ut Everyone interested in the philosophy and ethics of AI, epistemology, technology, and healthcare is warmly invited to attend! Feel free to share this event with colleagues, students, and researchers.

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Postdoctoral positions in Neuromorphic Computing @ The Hotchkiss Brain Institute
by Wilten Nicola Oct. 16, 2026

Oct. 16, 2026

The Hotchkiss Brain Institute in the Cumming School of Medicine at the University of Calgary is accepting applications for a Postdoctoral Scholar in the Neuromorphic Opportunities, Ventures, & Acceleration (NOVA) program. Job Description: The Hotchkiss Brain Institute invites applications for the HBI Neuromorphic Opportunities, Ventures, & Acceleration (NOVA) program. NOVA sits at the interface of neuroscience, AI, and hardware engineering and supports fellows in translating principles of neural computation into new computing architectures. NOVA aims to attract ambitious early career researchers interested in advancing neuromorphic hardware, algorithms, and software development, through novel developments in brain-inspired technologies to create the next-generation of AI accelerators. The ideal candidates will develop an independent research program in one of the following areas: - Energy-efficient analog and mixed-signal neuromorphic computing - Learning algorithms for neuromorphic systems, including on-chip and biologically inspired learning - Large-scale neural-system emulation using FPGAs and existing neuromorphic platforms such as Intel Loihi and SpiNNaker - Next-generation neuromorphic hardware, including emerging approaches such as neurophotonics Scholars are appointed for an initial term of 2 years, with potential to renew up to a total of 5 years contingent on successful annual review. This award pays an annual stipend of $100,000 CAD and a separate research allowance of $25,000 CAD per year. Successful candidates will be supported by a primary mentor as well as a mentoring committee with diverse experience relevant to the project. Potential mentors, and more information about neuromorphic computing and computational neuroscience at the HBI, can be found here: https://hbi.ucalgary.ca/computational-neuroscience/NeuromorphicComputing [ https://hbi.ucalgary.ca/computational-neuroscience/NeuromorphicComputing] *Qualifications:* Applicants must have a PhD or equivalent in a relevant domain (Electrical/Biomedical Engineering, Physics, Computer Science, Mathematics, Applied Mathematics or relevant adjacent fields) and experience relevant to one of the topic areas above. Some prior post-doctoral research is an asset but not required. *Application Details:* Applications should include a cover letter outlining research experience and interests, a CV and names of three potential references. Please email materials to: wilten.nicola(a)ucalgary.ca. Applications will be reviewed as they are received up until the deadline (November 30th 2026). The terms and conditions of employment are covered under the UCalgary and PDAC Collective Agreement. To find out more about postdoctoral scholar program at the University of Calgary visit our Postdocs website <https://research.ucalgary.ca/postdocs>. https://careers.ucalgary.ca/jobs/18230209-postdoctoral-scholar-in-the-neuro…

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Funded PhD Opportunities at the University of Toronto: NeuroAI and Computational Neuroscience
by Helena Liu Oct. 16, 2026

Oct. 16, 2026

Funded PhD Opportunities: NeuroAI and Computational Neuroscience at the University of Toronto I am recruiting PhD students to join my new lab at the University of Toronto for Fall 2027. We study how brains and artificial neural networks learn from experience, form useful representations, assign credit to past events, and generalize to new situations. Our work combines computational neuroscience, machine learning, mathematical modeling, and neural and behavioral data, and has appeared in PNAS, NeurIPS, ICLR, and ICML. Research directions include how biological mechanisms support learning from delayed feedback; how neural circuit structure and learning dynamics shape representations, generalization, and continual learning; and methods for inferring learning processes from neural and behavioral data. As one of the founding students, you can begin with a concrete project in one of these directions, with room to bring your own interests into the work and help shape the lab’s culture. You can learn more about our work at helena-yuhan-liu.github.io<https://helena-yuhan-liu.github.io/>. Who should apply: Students from computer science, engineering, statistics, physics, applied mathematics, neuroscience, psychology, and related fields are encouraged to apply. A strong quantitative background and experience with scientific programming are important; applicants should be comfortable with linear algebra, probability/statistics, and computational problem solving. Prior training in neuroscience or psychology is not required. We especially value students who are intellectually curious, creative, self-motivated, and able to take ownership of a project and carry it through to completion. What we offer: Close, direct mentorship with individualized support for research and career development; interdisciplinary training in computational methods and scientific thinking; and opportunities to present at conferences and publish in machine-learning and neuroscience venues. Students will benefit from U of T’s strengths in AI, neuroscience, and cognitive science, with opportunities to connect and collaborate across disciplines. Toronto combines a vibrant research community with diverse neighborhoods, a lively arts scene, and excellent food. Admission and funding: This is a funded PhD opportunity through U of T’s Psychology graduate program. The program uses direct admission to a supervisor’s lab. Direct entry from a bachelor’s degree is available for eligible applicants; applicants with a master’s degree are also welcome. The application deadline is December 1, 2026. Please see the program’s application page<https://www.psych.utoronto.ca/prospective-graduate-students/application-inf…> for application requirements and instructions. Interested? Please apply through the U of T Psychology PhD program and list me as a prospective supervisor. If you have questions about research fit, feel free to email me with your CV attached. Best, Helena Liu ________________________________________ Y. Helena Liu Postdoctoral Research Associate, Princeton University Incoming Assistant Professor (January 2027), Department of Psychology, University of Toronto Website: https://helena-yuhan-liu.github.io/

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M2 / PhD positions in computational neuroscience / NeuroAI at CERCO, Toulouse, France
by Messagerie CNRS Oct. 15, 2026

Oct. 15, 2026

Hi all, We have two fully funded M2 / PhD positions in computational neuroscience / NeuroAI at CERCO, Toulouse, France: 1) Modeling visual learning in bees with deep neural networks. We are looking for an M2 and/or PhD student. More details here: https://www.dropbox.com/scl/fi/5jnm96coewyiwv9szh6l9/Bees_M2-PhD_2026.pdf?r… 2) From Synaptic Delays to Neural Sequences: Modeling Temporal Neural Coding with Spiking Neural Networks We are looking for an M2 student. More details here: https://www.dropbox.com/scl/fi/v9lvbs02uifz3feofscuz/CerCo_M2_Offer_2027.pd… Please forward, distribute, etc. Cheers, Tim ___________________________________________________________________ Timothée Masquelier - timothee.masquelier(a)cnrs.fr - http://cerco.cnrs.fr/pagesp/tim

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Summit on Open Problems for AI (London, Nov 25-27th)
by Ruairidh Battleday Oct. 14, 2026

Oct. 14, 2026

Dear all, Thinking About Thinking has put together a Summit on Open Problems for AI <https://www.algopreneurship.org/>, to occur in London Nov 25-27th. We believe that this is an extremely important time to discuss frontier breakthroughs, threats, and applications in AI, especially in an open-access manner. *The three days:* - Wednesday 25 November: AI Research Breakthroughs and Infrastructure - Thursday 26 November: AI Safety, Enterprise and Society - Friday 27 November: AI Entrepreneurship and Applications *Our speakers include:* Prof Zoubin Ghahramani (DeepMind), Prof Tim Rocktäschel (Recursive), Dr Raia Hadsell (Google DeepMind), Dr Danyal Akarca (Callosum), Prof Jakob Foerster (Oxford/Meta), Dr Ed Hughes (Inherent), Dr Katja Hofmann (Microsoft), Prof David Barber (UCL), Dr Talfan Evans (Cursive), Dr Jonathan Richard Schwarz (Reuters), Dr Leon Chlon (Hassana Labs & PhysicsX), Dr Vassia Simaiaki (Wayve), Dr Artemis Seaford (formerly ElevenLabs) Dr Phil Lorenz (Basecamp Research) and Dr Hannah Madan (Prima Mente), and many more. We would love to see some of you there. All the best, Ruairidh and the team -- [image: Thinking About Thinking] Dr. Ruairidh McLennan Battleday Chief Executive Officer Thinking About Thinking battleday(a)thinkingaboutthinking.org • thinkingaboutthinking.org <https://www.thinkingaboutthinking.org/> • LinkedIn <https://www.linkedin.com/in/ruairidh-battleday-648a2b65/>

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Subcortical Sensory Circuits Meeting 2027
by Beatriz Mizusaki Oct. 14, 2026

Oct. 14, 2026

We’re happy to advertise the third edition of the *Subcortical Sensory Circuits Meeting at SISSA*! The meeting will take place on the *9-12 February 2027*. *https://www.subcortical2027.com/* <https://www.subcortical2027.com/> Subcortical circuits play a crucial role in perception and the execution of a wide variety of essential behaviours. The number of laboratories focusing on subcortical areas has increased steadily, establishing these regions as key model systems for understanding how defined circuits and computations integrate sensory signals with context and internal state to drive and modulate some of life’s core behaviours. This meeting brings together leading scientists whose research interrogates subcortical circuits from these different viewpoints using a variety of approaches. The program is complemented by a session focusing on modelling-based perspectives and approaches to catalyse discussions between experimental and computational researchers on how established models from other circuits and systems can be adapted to subcortical structures. *The application deadline for a poster/talk abstract is October 31**st* and registration deadline is the 24th of December. Hope to see some of you at this conference! On behalf of the organizing committee: Katja Reinhard, Associate Professor at SISSA, Trieste, Italy Elise Savier, Assistant Professor at Michigan University, USA Karl Farrow, Associate Professor at KU Leuven, Belgium Lukas Ian Schmitt, Team Director at RIKEN, Japan ----- *Beatriz E. P. Mizusaki* *Bridge Postdoctoral Researcher* *Scuola Internazionale Superiore di Studi Avanzati (SISSA)* *Trieste, Italy*

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Reminder: 2 postdoc and 1 phD positions on computational mechanisms of human perception (Alex Hyafil & Chris Summerfield, Barcelona)
by Alexandre Hyafil Oct. 14, 2026

Oct. 14, 2026

The group of Alex Hyafil at the CRM Barcelona (https://ahyafil.github.io/) is looking for two postdoc researchers and a PhD student. One of the postdoc positions will be co-supervised by Chris Summerfield (Universitat Pompeu Fabra Barcelona / Oxford; https://humaninformationprocessing.com/) The selected candidate will investigate the computational operations underlying visual scene perception through a combination of simulation of artificial visual systems (conv nets, visual transformers) and human experiments. The position is for two years. The other postdoc researcher (2-year duration) and the PhD student (4-year) will work jointly on identifying canonical Bayesian operations at play in human visual and auditory perception. The project involves Bayesian modelling, artificial vision network simulations, behavioral and EEG experiments as well as intra-cranial EEG experiments (in collaboration with Benjamin Morillon, AMU Marseille). We will look for complementarity of the two profiles, notably in terms of quantitative and experimental backgrounds. The hired researchers will benefit from the stimulating environment of the Barcelona area in cognitive and computational neuroscience. Our groups form part of a larger interacting network of neuroscience labs in Barcelona ( http://www.barccsyn.org) Financial support is provided by the Spanish National Agency of Investigation (FPI fellowship for the PhD student). *APPLICATION:* Send a curriculum and motivation with a list of two contacts for recommendation letter at https://bit.ly/ChrisAlexPositions. Informal enquiries are welcome. *DEADLINE:* before October 31 for the PhD position; until position is filled for the postdoc positions. *STARTING DATE:* before July 2027 for the PhD position; flexible for the postdoc positions

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PSI correction and new perspective on clinical assessment and EEG validation
by נתי שטרן Oct. 14, 2026

Oct. 14, 2026

Dear Comp-neuro community, I am following up on my earlier PSI announcement with a new perspective that corrects its clinical framing and proposes a staged validation protocol: *Reframing the Psychiatric State Index Through Clinical Assessment and Measurement Validation* Full manuscript with references <https://github.com/netanelcyber/psi-qeeg-bis/blob/18e22b6dd4ddc8747b6c2034c…> The manuscript is not peer reviewed. Psychiatric review has been requested and remains pending. The computational project currently provides numerical signal analyses and exploratory diagnosis-group benchmarks; its available data do not validate future clinical-event prediction. The protocol makes clinical adjudication the reference standard and asks whether EEG adds value over a clinical-only comparator. It separates synchrony/coupling, diagnosis-group differences, movement-associated measurements and future-event prediction. Scalp gamma/PAC is excluded from primary human analyses, with independent artifact measurements required for secondary interpretation; intracranial LFP is treated separately. The accompanying PR #3 <https://github.com/netanelcyber/psi-qeeg-bis/pull/3> corrects PAC surrogate boundaries and configured-count reporting, enforces acquisition/QC compatibility, and balances human training by participant. Synthetic regression tests and public-data benchmarks are documented as computational evidence, not clinical validation. I would welcome criticism of the surrogate/null assumptions, participant-level evaluation and incremental-value study design, particularly from researchers with psychiatric or EEG measurement expertise. Best regards, Netanel Stern On Wed, 07 Oct 2026 22:16:46 -0700, נתי שטרן <nsh531(a)gmail.com> wrote: Dear Comp-Neuro community, I am sharing a perspective article proposing a wearable EEG device, the Psychiatric State Index (PSI), to differentiate autistic meltdowns from psychotic episodes in real time. As an autistic researcher, I combine lived experience with computational neuroscience. The article introduces two composite indices (SOI and RDI), addresses BIS calibration failures in neuropsychiatric populations, and includes worked clinical vignettes. Full article available upon request. Netanel Stern Rosh HaAyin, Israel

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Vote for the Best Illusion of the Year! The 20th Best Illusion of the Year Contest
by smart＠neuralcorrelate.com Oct. 14, 2026

Oct. 14, 2026

Dear Illusion Enthusiasts, Worldwide voting for the 20th Best Illusion of the Year Contest <https://illusionoftheyear.com/> will start on Monday, October 19th, and remain open until Friday, October 24th. The 1st place winner will receive $3,000, the 2nd place winner $2,000, and the 3rd place winner $1,000. We're excited to share the mind-bending illusions from our incredible finalists with you! The Top 10 Finalists, selected from dozens of entries from countries all around the world, will be publicly revealed at voting time. Anybody with an internet connection (that means YOU!) can vote to pick the Top 3 Winners from the Top 10 Finalists. The Neural Correlate Society thanks our 2025 Platinum Sponsor, the Museum of Illusions <https://www.museumofillusions.com/> , for their generous support of the Best Illusion of the Year Contest. On behalf of the Executive Board of the Neural Correlate Society: Jose-Manuel Alonso, Stephen Macknik, Susana Martinez-Conde, Luis Martinez, Xoana Troncoso, Peter Tse --------------------------------------- Susana Martinez-Conde, PhD Author, <x-msg://2/championsofillusionbook.com> Champions of Illusion and Sleights of Mind Professor of Ophthalmology, Neurology, and Physiology & Pharmacology Director, Laboratory of Integrative Neuroscience 2014 Society for Neuroscience's Science Educator Award 2014 Empire Innovator Scholar State University of New York (SUNY) Downstate Health Sciences University 450 Clarkson Ave, Brooklyn NY 11203, USA Email: <mailto:smart@neuralcorrelate.com> smart(a)neuralcorrelate.com Phone: <tel:%2B1%20718-270-4520> +1 718-270-4520 http://smc.neuralcorrelate.com

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NITMB Focused Research Group Awards for Summer 2027 --- please apply by 30 November 2026
by William L. Kath Oct. 13, 2026

Oct. 13, 2026

*Do you have an ongoing group research project at the interface between mathematics and biology that has been on hold because you and your collaborators are scattered in different locations?* *Or would you like to get a new team of people together to brainstorm about and tackle some exciting idea? * *If so, apply for an interdisciplinary research retreat in Chicago!* The National Institute for Theory and Mathematics in Biology (NITMB) invites applications for our *Focused Research Group Awards (FRGA)*. We bring small, multi-institutional teams (e.g., 3–6 researchers) for up to 9 days of intense, distraction-free collaboration in our space on the 35th floor of the iconic Hancock Building. * Funding (subject to NITMB policies): Covers travel, local lodging, subsistence, and dedicated meeting space. * Breaking disciplinary silos: Open to mathematicians exploring biological contexts, biologists employing advanced theoretical frameworks and, especially, groups with interdisciplinary expertise. * High-risk, high-reward: Priority is given to projects developing innovative mathematical approaches inspired by biology. *For visits during Summer 2027 (May through August), please apply by 30 November 2026 for full consideration. Visit our website to view further information, full eligibility criteria, and to submit your 2-page proposal: nitmb.org/research/focused-research-group-awards *

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Doctoral studies in Computational/Theoretical Neuroscience at NYU
by Eero Simoncelli Oct. 13, 2026

Oct. 13, 2026

New York University is home to a thriving interdisciplinary community of researchers using computational and theoretical approaches in neuroscience. We are interested in exceptional PhD candidates with strong quantitative training (e.g., physics, mathematics, engineering) coupled with a clear interest in scientific study of the brain. A listing of faculty, sorted by their primary departmental affiliation, is given below. Doctoral programs are flexible, allowing students to pursue research across departmental boundaries. Nevertheless, admissions are handled separately by each department, and students interested in pursuing graduate studies should submit an application to the program that best fits their goals and interests. Center for Neural Science (CNS), Graduate School of Arts & Sciences (deadline: 1 December) [https://as.nyu.edu/cns/DoctoralProgram.html, https://neuroscience.nyu.edu/program.html] * Andre A. Fenton - Molecular, neural, behavioral, and computational aspects of memory. * David Heeger (also in Psychology) - Computational neuroscience, vision, attention. * Roozbeh Kiani - Vision and decision-making. * Wei Ji Ma (also in Psychology) - Perception, working memory, and decision-making. * Tony Movshon - Vision and visual development. * Alex Reyes - Functional interactions of neurons in a network. * John Pearson - Development, structure and function of sensory systems. * John Rinzel (also in Mathematics) - Biophysical mechanisms and theory of neural computation. * Cristina Savin (also in the Center for Data Science) - Computational models of learning and memory, machine learning. * Robert Shapley - Visual physiology and perception. * Eero Simoncelli (also in the FlatIron Institute) - Computational vision and audition. * Xiao-Jing Wang - Computational neuroscience, decision-making and working memory, neural circuits. * Alex Williams (also in the FlatIron Institute) - Statistical analysis of neural data. Neuroscience Institute, School of Medicine (deadline: 1 December) [https://med.nyu.edu/departments-institutes/neuroscience/, https://neuroscience.nyu.edu/program.html] * Gyorgy Buzsaki - Rhythms in neural networks. * Zhe Chen - Memory and learning, cognitive flexibility and decision making, social behaviors, and pain. * Dmitri Chklovskii (also in the FlatIron Institute) - Neural computation and connectomics. * Paul W. Glimcher - Decision-making in humans and animals. Neuroeconomics. * Biyu He - Large-scale brain dynamics underlying human cognition. * Dima Rinberg - Olfaction, sensory information processing, perception. * Shy Shoham - Methods for controlling, imaging, and analyzing neural systems. * Mario Svirsky - Auditory neural prostheses; experimental/computational studies of speech production/perception. Psychology, Cognition & Perception program (deadline: 1 December) [http://as.nyu.edu/psychology/graduate/phd-cognition-perception.html] * Todd Gureckis - Memory, learning, and decision processes. * Michael Landy - Computational approaches to vision. * Laurence Maloney - Mathematical approaches to psychology and neuroscience. * Marcelo Mattar - Learning and planning in the brain/mind. * Denis Pelli - Visual object recognition. * Jonathan Winawer - Visual perception and memory. Data Science (deadline: 3 December) [https://cds.nyu.edu/phd-program/] * Joan Bruna (also in Computer Science) - Machine learning, signal/image processing. * Kyungyun Cho (also in Computer Science) - Machine learning, natural language processing. * Carlos Fernandez-Granda (also in Mathematics) - Optimization methods for medical imaging, neuroscience, computer vision. * Brenden Lake (also in Psychology) - Computational modeling of cognition, deep learning. * Grace Lindsay (also in Psychology) - Machine learning models of the brain/mind. * Mengye Ren (also in Computer Science) - Brain and cognitively inspired representation learning. Mathematics (deadline: 18 December) [https://gsas.nyu.edu/admissions/arc/programs/mathematics.html] * Aaditya Rangan - Computational neurobiology, numerical analysis. * Charles Peskin - Mathematical biology. * Daniel Tranchina - Information processing in the retina. * Lai-Sang Young - Dynamical systems, statistical physics, computational modeling and theoretical neuroscience. Physics (deadline: 30 December) [https://as.nyu.edu/physics/programs/graduate.html] * Marc Gershow - Perception, decision-making, and learning in neural circuits. * Stefano Martiniani - Fundamental principles governing neural systems. Computer Science (deadline: 12 December) [http://www.cs.nyu.edu/home/phd/] * Davi Geiger - Computational vision and learning. * Yann LeCun - Machine learning, computer vision, robotics, computational neuroscience. Economics (deadline: 18 December) [https://as.nyu.edu/econ/graduate/phd.html] * Andrew Caplin - Economic theory, neurobiology of decision. * Andrew Schotter - Experimental economics, game theory, neurobiology of decision.

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COSYNE 2027: Abstract submission closes soon
by Tomas Hromadka Oct. 12, 2026

Oct. 12, 2026

==================================================== Computational and Systems Neuroscience 2027 (Cosyne) MAIN MEETING & WORKSHOPS 11 - 16 March 2027 Montreal, Canada www.cosyne.org ==================================================== IMPORTANT DATES Abstract submission is now open. Abstract submission deadline: 18 October 2026 Workshop proposal submission is now open. Workshop proposal submission deadline: 01 November 2026 UNDERGRADUATE travel grant applications are now open. UNDERGRADUATE travel grant submission deadline: 30 October 2026 ---------------------------------------------------- COSYNE MEETING & WORKSHOPS ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks is selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, neuromodulation, and computation with spiking networks. We would like to foster increased participation from experimental groups as well as computational ones. Please circulate widely and encourage your students and postdocs to apply. When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. ----------------------------------------------------- COSYNE TRAVEL GRANTS ----------------------------------------------------- The COSYNE community is committed to bringing talented scientists together at our annual meeting, regardless of their ability to afford travel. Thus, a number of travel grants will be awarded to students, postdocs, and PIs for travel to the COSYNE meeting. We currently offer five travel grant programs: Childcare, Presenters, New Attendees, Mentorship, and Undergraduate Travel Grants, see Cosyne.org -> Attend -> Travel Grants for details. Applicants may apply for more than one grant program, but no applicant will receive more than one award. You may apply for a travel grant before receiving notification about the outcome of your submission. You may also apply if you are not submitting anything to the Main Meeting but still wish to attend Cosyne 2027. ---------------------------------------------------- COSYNE 2027 ---------------------------------------------------- COSYNE INVITED SPEAKERS Dani Bassett (UPenn) Chand Chandrasekaran (Boston U) Christine Constantinople (NYU) Paul Cisek (U Montreal) Kevin Franks (Duke) Leslie P Kaelbling (MIT) Andy Leifer (Princeton) Scott Linderman (Stanford) Amy Orsborne (U Washington) Cengiz Pehlevan Kempner (Harvard) Kanaka Rajan (Harvard; Kempner Inst) Rebecca Saxe (MIT) Carsen Stringer (Janelia) ORGANIZING COMMITTEE General Chairs: Kimberly Stachenfeld (DeepMind) and Mark Histed (NIH) Program Chairs: Annegret Falkner (Princeton) and Guillaume Lajoie (MILA/U Montreal) Workshop Chairs: N Alex Cayco Gajic (ENS) and Marcelo Mattar (NYU) Tutorial Chairs: Eva Dyer (Georgia Tech) and Alex Williams (NYU) Mentorship and Networking Chairs: Renata Brito (Mount Sinai) and Srikanth Ramaswamy (Newcastle U) Undergraduate Travel Chairs: Lea Duncker (Columbia) and Kevin Miller (DeepMind) Development Chair: Michael Long (NYU) Media Chairs: Roxana Zeraati (MPI Biol Cybernetics) and Claire Sturgill (TU Dresden) Social Media Chair: Shervin Safavi (TU Dresden) Poster Design: Maja Bialon PROGRAM COMMITTEE Annegret Falkner (Princeton) Guillaume Lajoie (MILA/U Montreal) Thomas Akam (Oxford) Mikio Aoi (UCSD) Shahab Bakhtiari (U Montreal) Arkarup Banerjee (CSHL) Joao Barbosa Pouya Bashivan (McGill) Marcus Benna (UCSD) Colin Bredenberg (U Oregon) Fanny Cazettes (Aix-Marseille U) Angus Chadwick (U Edinburgh) Vincent Costa (Emory) Ben Cowley (CSHL) Emily Dennis (Janelia) Sridhar Devarajan (IISc) Celine Drieu (JHU) Eva Dyer (UPenn) Becket Ebitz (U Montreal) Noemi Elteto (Google) Rainer Engelken (UIUC) Arseny Finkelstein (Tel Aviv University) Juan Gallego (Champalimaud) Erin Grant (U Alberta) Christine Grienberger (Brandeis) Laura Grima (Janelia) Bilal Haider (Georgia Tech) Yu Hu (ION, CAS Shanghai) Michele Insanally (U Pittsburgh) Kishore Kuchibhotla (JHU) Nina Kudryashova (U Edinburgh) Helena Liu (U Toronto) Laureline Logiaco (CU Anschutz) Thomas Zhihao Luo (U Utah) Paul Masset (McGill) Francesca Mastrogiuseppe (Champalimaud) Alexander Mathis (EPFL) Luca Mazzucato (U Oregon) Dan McNamee (Champalimaud) Cory Miller (UCSD) Wilten Nicola (U Calgary) Ramon Nogueira Manas (U Chicago) Gouki Okazawa (ION, CAS Shanghai) Agostina Palmigiano (UCL) Matt Perich (U Montreal) Rui Ponte Costa (Oxford) Lorenzo Posani (Paris Brain Institute) Dean Pospisil (UIUC) Isabeau Premont-Schwarz (U Laval) Carolina Rezaval (U Birmingham) Shreya Saxena (Yale) Evan Schaffer (Sinai) Heike Stein Weinan Sun (Cornell) Roxana Zeraati Chris Zimmerman (U Utah) Petr Znamenskiy (Crick) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Anne-Marie Oswald (U Pittsburgh) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT meeting [at] cosyne.org ----------------------------------------------------- COSYNE MAILING LISTS ----------------------------------------------------- Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> About-> Mailing lists for details.

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University College London NeuroAI Annual Conference - 11th Nov
by Padraig Gleeson Oct. 12, 2026

Oct. 12, 2026

Dear Colleagues, The 7th Annual UCL NeuroAI Conference will take place on Wednesday 11 November 2026 at the Kennedy Lecture Theatre, UCL Great Ormond Street Institute of Child Health, London. The event will feature leading speakers at the cutting edge of machine learning and neuroscience. The UCL NeuroAI initiative aims to be a central hub where researchers working in neuroscience, AI, machine learning, and related fields can interact and stay updated on the latest advancements in these intersecting areas. Our annual conference is an important opportunity for these communities to gather, make new connections, and benefit from insights in one another’s fields. *Keynote speakers* We are privileged to have a distinguished line-up of speakers and experts confirmed to date. Wolfgang Maass, Technische Universität Graz Agostina Palmigiano, Gatsby Computational Neuroscience Unit Bernardo Sabatini, Harvard Medical School Nicolas Skatchkovsky, Francis Crick Institute Eleni Vasilaki, University of Sheffield Ellie Pavlik, Brown University *Registration * Registration is required and the conference ticket is £5 but if the cost is a barrier, please email events(a)ucl.ac.uk for a complimentary ticket. Please register here <https://www.bloomsburytheatre.com/event/2026/11/neuroai-conference-2026>. *Poster and talks - Submissions are now open!* This year we will also be accepting abstract submissions for posters, short lightning presentations (3-4 mins), as well as longer submitted talks (15 mins) as part of the event. The deadline to submit your abstract for these is *Friday 16 October at 12pm*. Please remember to book your conference place as well as completing the abstract registration form if you would like to present. Submit your poster or talk abstract now here <https://forms.cloud.microsoft/Pages/ResponsePage.aspx?id=_oivH5ipW0yTySEKEd…>. *Sponsorship* We are immensely grateful for the support from the Sainsbury Wellcome Centre, Callosum Technologies and Google DeepMind. *About UCL NeuroAI* The last decade has seen phenomenal advances in the fields of machine learning (e.g. deep learning, reinforcement learning, and AI). While these changes have already had considerable impact on most areas of science they hold a particular resonance for neuroscience. Crucially, AI shares a common lineage with neuroscience and, fundamentally, machine learning and the brain employ similar computations to process and compress information. For these reasons AI provides a means to emulate neural functions and the circuits supporting them, providing insights to aid our understanding of the brain and cognition. Equally, AI tools provide a means to discover, segment, and track distinct neural and behavioural states, yielding more efficient experiments and accelerating the pace of discovery. In turn, this understanding feeds back into the design of more effective AI architectures and models. Essentially, AI problems posed in neuroscience both require and inspire further advances in AI. UCL NeuroAI has been set up to provide a forum where researchers in these areas can meet, exchange ideas, and move both fields forward. -- ----------------------------------------------------- Padraig Gleeson http://openneuroai.org Room 321, Anatomy Building Department of Neuroscience, Physiology & Pharmacology University College London Gower Street London WC1E 6BT United Kingdom +44 207 679 3214 p.gleeson(a)ucl.ac.uk -----------------------------------------------------

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Final Call for Papers: ACML 2026 (Encore Track)
by Levin Kuhlmann Oct. 12, 2026

Oct. 12, 2026

ACML 2026 (the 18th Asian Conference on Machine Learning) is being held in Melbourne Australia on 1–4 December, just before NeurIPS in Sydney. The main conference, journal and workshop tracks have closed, but the Encore Track is still accepting submissions. It's a way to present work you've already had published or accepted at a leading venue (including NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, AAAI, JMLR, IEEE TPAMI) since 1 June 2025, through an encore talk in a topic-aligned session. Submission is lightweight: title, abstract, author details, PDF and publication URL (or evidence of acceptance if not yet published). Deadline: 18 October 2026, 11:59 PM AoE For more details visit https://www.acml-conf.org/2026/calls/papers/#encore-track If you have any questions, please contact Levin Kuhlmann ( levin.kuhlmann(a)monash.edu) Kind regards, Levin Kuhlmann Encore Track Chair, ACML 2026

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Two Postdoctoral Positions in Computational Neuroscience - Ruhr University Bochum, Germany
by Sen Cheng Oct. 10, 2026

Oct. 10, 2026

Dear colleagues, We are inviting applications for *two postdoctoral positions in Computational Neuroscience* within the Collaborative Research Center *SFB 1280 "Extinction Learning"* at Ruhr University Bochum, Germany. SFB 1280 is an interdisciplinary research consortium investigating the neural, cognitive, and behavioral mechanisms underlying extinction learning. It brings together researchers from neuroscience, psychology, medicine, and computational modeling. The two positions are based in the Computational Neuroscience group and focus on different aspects of learning and memory: *1. Project Z02 – Computational Modeling of Learning Dynamics* Investigate learning dynamics across individuals, species, learning phases, and experimental paradigms. The successful candidate will develop computational models and analysis methods to characterize learning processes using behavioral, neural, and psychophysiological data collected within SFB 1280. The project involves close interdisciplinary collaboration with experimental researchers. *Application deadline: November 2, 2026* https://jobs.ruhr-uni-bochum.de/jobposting/ccfb73ccd824632cad67e3960105dc6e… *2. Project A14 – Spiking Neural Network Models of Hippocampal Memory Processes* Develop quantitative spiking neural network models to investigate the neural mechanisms of episodic memory and spatial navigation. The project focuses on how hippocampal sequences during sharp-wave ripples are generated and shaped by experience and neuromodulation to support memory consolidation. Computational models will be developed in close collaboration with experimental neuroscientists and validated against electrophysiological and behavioral data from rodents. *Application deadline: October 19, 2026 (will be extended to **November 2, 2026**)* https://jobs.ruhr-uni-bochum.de/jobposting/1a216242df7d11a68fb762a850c9d76a… *General information:* - *Starting date:* As soon as possible - *Duration:* Until June 30, 2029 - *Salary:* TV-L E13, 100% position - *Location:* Ruhr University Bochum, Germany We welcome applications from motivated researchers with a PhD in computational neuroscience, neuroscience, physics, computer science, mathematics, or related disciplines. Strong quantitative and programming skills, experience in computational modeling, and enthusiasm for interdisciplinary collaboration are particularly valued. For details about the positions, qualifications, and application procedures, please consult the respective job advertisements. We would appreciate it if you could forward this announcement to interested candidates. Best regards, Sen Cheng. --- Prof. Dr. Sen Cheng Ruhr-Universität Bochum Fakultät für Informatik Institut für Neuroinformatik Universitätsstr. 150 Postfach 110 44801 Bochum Büro: NB 3/33 | +49-234- 32 29486 <0234%203229486> | FAX: +49-234- 32 14210 <0234%203214210> sen.cheng(a)rub.de | rub.de/cns | for2812.rub.de

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Three PhD Positions in Computational Neuroscience and Episodic Memory – Ruhr University Bochum
by Sen Cheng Oct. 10, 2026

Oct. 10, 2026

Dear colleagues, We are inviting applications for *three PhD positions* within the newly established Collaborative Research Center *CRC 1844 "Episodic Memory"* at Ruhr University Bochum, Germany, pending final funding approval. The CRC brings together researchers from computational neuroscience, psychology, neuroscience, and philosophy to investigate how episodic memories are encoded, reconstructed, and used in cognition and behavior. The three positions focus on different aspects of episodic memory research: *1. Project A07 – Computational Modeling of Episodic Memory Development* Develop computational models to investigate how episodic memory develops in children, using modern artificial neural networks and deep reinforcement learning. The project involves close collaboration with experimental researchers in psychology and neuroscience. https://jobs.ruhr-uni-bochum.de/jobposting/535055f07b13f29c9ad9ecf2809e56ae… *2. Project A10 – Episodic Memory and Spatial Navigation* Investigate the functional role of episodic memory in spatial navigation through computational modeling, including artificial neural networks and deep reinforcement learning. The project combines theoretical modeling with simulations of experimental tasks. https://jobs.ruhr-uni-bochum.de/jobposting/bb916076d7b6b55ac97d7e5b3a9872a0… *3. Project Z02 – Gamified Episodic Memory Research and Citizen Science* Investigate episodic memory using behavioral data collected through a digital serious game developed in collaboration with the Cologne Game Lab. The project focuses on computational and statistical analysis of large-scale memory data, connecting fundamental memory research with citizen science and public engagement. https://jobs.ruhr-uni-bochum.de/jobposting/fec7155cf49f90ef54729f1412129f5b… *General information:* - *Application deadline:* November 2, 2026 - *Starting date:* January 1, 2027 (subject to funding approval) - *Duration:* Until December 31, 2030 - *Salary:* TV-L E13, 75% position - *Location:* Ruhr University Bochum, Germany We welcome applications from motivated candidates with a Master's degree in computational neuroscience, computer science, physics, mathematics, or related disciplines. Strong programming and quantitative skills, an interest in memory research, and enthusiasm for interdisciplinary collaboration are particularly valued. For details about the positions, qualifications, and application procedures, please consult the respective job advertisements. We would appreciate it if you could forward this announcement to interested candidates. Best regards, Sen Cheng. --- Prof. Dr. Sen Cheng Ruhr-Universität Bochum Fakultät für Informatik Institut für Neuroinformatik Universitätsstr. 150 Postfach 110 44801 Bochum Büro: NB 3/33 | +49-234- 32 29486 <0234%203229486> | FAX: +49-234- 32 14210 <0234%203214210> sen.cheng(a)rub.de | rub.de/cns | for2812.rub.de

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Michael H. Goldstein speaking in Developing Minds Lecture Series on October 15
by Jochen Triesch Oct. 10, 2026

Oct. 10, 2026

Dear colleagues, On October 15, the Developing Minds global online lecture series is proud to host Michael H. Goldstein, Cornell University, USA, speaking on „Mechanisms of socially guided vocal learning in human infants and songbirds: Connecting contingency to curiosity-driven learning“. His talk will take place at: 09:00 am EDT (Eastern Daylight Time, USA) 13:00 UTC (Universal Coordinated Time) 15:00 CEST (Central European Summer Time) 22:00 JST (Japan Standard Time) The talk will be hosted via zoom: https://uni-frankfurt.zoom-x.de/j/69608764770?pwd=gOHzVZ5y86Ic0MZFik6khLk0m… Meeting-ID: 696 0876 4770 Code: 401171 Abstract: The ability to learn a vocal repertoire is a rare phenomenon, emerging in only a handful of groups, including humans and songbirds. A key parallel in the vocal development of certain songbirds and human babies is the social function of immature vocalizations. The form and timing of adult-infant interactions facilitate real-time vocal learning and have strong influences on the development of mature birdsong and language. Specifically, contingent responses of adults to the plastic song of birds and the babbling of babies have strong influences on learning. What makes contingency effective? We will examine curiosity-driven learning (CDL) as a framework for a mechanistic understanding of learning from contingent social interactions. In CDL, intrinsic reward is generated by changes in the predictability of social interactions as a function of immature vocal behavior. We will discuss several tests of this idea at the behavioral and neural levels in songbirds and human infants. Taken together, my studies indicate that temporal characteristics of social interaction are rewarding to young songbirds and human infants, and reward pathways may drive learning in social contexts. Short Bio: Michael Goldstein is a Professor of Psychology and a Stephen H. Weiss Presidential Fellow at Cornell University. He received his PhD in developmental psychology and animal behavior from Indiana University. Michael studies the development and evolution of vocal communication and social learning. He takes a comparative approach, investigating vocal communication and social development in human infants and songbirds. His research on the developmental processes by which knowledge of speech and song are acquired has revealed new mechanisms by which the social environment influences the learning of species-typical adaptive skills. By studying social interaction and learning as it occurs in moment-to-moment interactions between infants and social partners, Michael’s research connects our knowledge of social influences on developmental outcomes with specific processes of learning. A major finding from his work is that immature vocal behavior, such as babbling in humans and plastic song in songbirds, has crucial functional significance for learning, but only when studied in a social context. Michael received the David Kucharski Young Investigator Award from the International Society for Developmental Psychobiology and the Distinguished Early Career Contribution Award from the International Society on Infant Studies. His research has been supported by grants from NICHD and NSF. The talk will be recorded and made available for later viewing. For more information on the talk series and recordings of previous events, please visit: https://sites.google.com/view/developing-minds-series/home Best regards, Jochen Triesch -- Prof. Dr. Jochen Triesch Johanna Quandt Chair for Theoretical Life Sciences Frankfurt Institute for Advanced Studies and Goethe University Frankfurt Recent publications: https://www.nature.com/articles/s41467-025-64234-z https://ieeexplore.ieee.org/abstract/document/11204381?casa_token=RBlsm2RTa…

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Scientist I, Theory of neural circuits, Allen Institute
by Ulises Pereira Obilinovic Oct. 10, 2026

Oct. 10, 2026

Dear Colleagues, The Allen Institute, Neural Dynamics (a/ND) in Seattle is hiring a Scientist I to work in my team on data-driven theories of how circuit structure shapes neural dynamics and computation. a/ND produces brain-wide connectivity atlases, simultaneous spike recordings from thousands of neurons across multiple brain regions, and targeted optogenetic perturbations during behavior, from coarse to holographic. The Scientist will build statistical physics theories of recurrent circuit models constrained by these data, use them to explain how connectivity structure organizes neural dynamics and computation, and test their predictions in new perturbation experiments at the Institute. We are looking for candidates with strong expertise in applied mathematics and/or statistical physics, fluency in modern machine learning, and an interest in neuroscience. Salary range: $87,450 - $108,250. Visa sponsorship and relocation assistance are available. To apply: https://alleninstitute.org/careers/jobs?jobId=f4864596-9e85-bbf6-a1f6-9e880… Feel free to email me with questions. Best, Ulises Pereira-Obilinovic Senior Scientist Allen Institute, Neural Dynamics ulises.pereira.o(a)alleninstitute.org

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Postdoctoral position in computational modeling of education data
by Kou Murayama Oct. 9, 2026

Oct. 9, 2026

Dear all, We are seeking a postdoctoral research fellow at the Hector Research Institute of Education Sciences and Psychology at the University of Tübingen, Germany. This is a joint project with Michiko Sakaki (Hector Research Institute) and Peter Dayan (Max Planck Institute for Biological Cybernetics). # Key points - Topic: computational modeling of large-scale digital education data with the focus on motivation, emotion, metacognition, self-control, etc. - Position: full-time (100%) - Duration: 3 years - Profile: Excellent research track record and proven expertise in computational modeling - Application deadline: Oct 30, 2026 Full details and application instructions: https://uni-tuebingen.de/universitaet/karriere/newsfullview-stellenangebote… Please feel free to contact me with informal inquiries, and I would be grateful if you could forward this to anyone who may be interested. Best wishes, Kou Murayama -- / Kou Murayama, Ph. D. / Hector Research Institute of / Education Sciences and Psychology / University of Tübingen / k.murayama(a)uni-tuebingen.de / https://motivationsciencelab.com/

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