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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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