- Comp-neuro - lists.cnsorg.org

Pynapple & NeMoS workshop on neural data analysis

by Edoardo Balzani

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

Oct. 27, 2026

[Meetings] Call For Applications 2027 Nengo Summer School

by Madeleine Bartlett

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

Oct. 27, 2026

JOB: Faculty Position in Cognitive Psychology, Seoul National University

by Jiook Cha/SNU/Psychology

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

Oct. 27, 2026

[jobs] Research Software Engineer, Nengo Neural Simulation Ecosystem

by Michael Furlong

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.

Oct. 26, 2026

CFP: FLAIRS40, Neural Network Special Track, St. Pete Beach, FL, May 24-27, 2027

by David B

*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)

Oct. 26, 2026

2nd Workshop on Neuro for AI & AI for Neuro: Towards Multi-Modal Natural Intelligence

by Anton Arkhipov

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]

Oct. 25, 2026

2 PhD positions in translational computational neuroscience and NeuroAI at ICNS Hamburg, Germany

by Claus C. Hilgetag

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

Oct. 25, 2026

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

[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.

Oct. 25, 2026

Discussion manuscript: validating pre-attack neural signals and their external EEG correlates

by נתי שטרן

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

Oct. 25, 2026

Postdoctoral Position in Computational/Theoretical Neuroscience at UC San Diego

by Marcus Benna

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

Oct. 23, 2026