- Comp-neuro - lists.cnsorg.org

Forecasting responsiveness under propofol - ICASSP 2027 Grand Challenge
by Katja Sept. 29, 2026

Sept. 29, 2026

Dear colleagues, We would like to invite participation in the DOSE-I Challenge, an ICASSP 2027 Signal Processing Grand Challenge on forecasting changes in responsiveness during propofol sedation from frontal EEG. Participants predict future MOAA/S approximately 60 s ahead from pre-index physiological data. The challenge is based on the recently released DOSE-I dataset, the first public large-scale EEG-based multimodal dataset of continuous propofol sedation with temporally dense annotation of sedation depth. Challenge / submissions: https://www.codabench.org/competitions/18100/ Open DOSE-I dataset: https://doi.org/10.5281/zenodo.18483291 == Timeline == • Challenge opens: October 1, 2026 • Final submission deadline: December 1, 2026 • Results and invitations: December 8, 2026 • Invited two-page papers due: January 7, 2027 • ICASSP 2027: May 16-21, 2027, Toronto, Canada Best wishes, K. Seeliger on behalf of the DOSE-I Challenge organizers +++++ academic website: https://seelikat.github.io/

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Computational Postdoctoral Position: Uncovering the Mathematics of Predictive Pursuit
by jonathan.whitlock＠ntnu.no Sept. 28, 2026

Sept. 28, 2026

About the position We are seeking an enthusiastic and highly motivated Postdoctoral Fellow with a quantitative PhD and background in machine learning, dynamical systems, physics, engineering or related fields for a 3-4 year project investigating the computational principles of Predictive Pursuit in freely moving rodents. This project is an interdisciplinary collaboration between the labs of Jonathan Whitlock at the Kali Institute for Systems Neuroscience (NTNU, Trondheim, Norway and Alex Cayco-Gajic at the Group of Neural Theory in Ecole Normale Supérieure (ENS-PSL, Paris, France). The candidate will be physically based in Trondheim, with extensive opportunities for research visits to Paris. About the project The project aims to uncover how the brain anticipates and reacts to dynamically fleeing agents and to perceptual mismatch. We will use the head and body of freely moving rodents as physical readouts of internal planning, dynamic decision-making and perceptual processing, combining high-resolution motion capture and high-density neural recordings across a range of behavioral conditions. The successful candidate will lead the data-driven modeling effort, developing state-of-the-art statistical models combining machine learning and dynamical systems to infer changes in strategy from high-dimensional behavioral data. The project is highly collaborative, with modeling developed in partnership with the lab of Alex Cayco-Gajic in Paris, while working closely with behavioral neurophysiologists at the Kavli Institute in Trondheim. Duties of the position • Develop machine-learning and dynamical-systems approaches for analyzing high-dimensional behavioral data. • Model postural, movement and performance dynamics to identify behavioral states and pursuit strategies. • Carry out high-quality, independent research within the project framework. • Publish findings in high-impact academic journals and present at international conferences. • Participate actively in collaborations and in the intellectual life of the research group and Required selection criteria • A PhD in a quantitative field, such as physics, computational neuroscience, computer science, or engineering • Strong expertise in machine learning, dynamical systems, computational modeling or quantitative analysis • Demonstrated experience analyzing large, high-dimensional datasets, preferably including behavioral, video or neurophysiological • Publish findings in high-impact academic journals and present at international conferences. • Participate actively in collaborations and in the intellectual life of the research group and institute. • Documented experience with scientific programming, e.g. Python, MATLAB or related languages. • A strong academic record and documented research productivity. • Excellent oral and written communication skills in English. • Ability to work both independently and collaboratively in an interdisciplinary research environment. Interested? Apply through the job ad portal: nettskjema.no/a/655482 Questions? Jonathan Whitlock: jonathan.whitlock(a)ntnu.no | Alex Cayco-Gajic: natasha.cayco.gajic(a)ens.psl.eu Labs: www.whitlocklab.org | www.caycogajiclab.github.io

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2nd UK Theoretical Neuroscience Workshop – 18 December 2026, London
by Dimitris Pinotsis Sept. 28, 2026

Sept. 28, 2026

We are pleased to announce the *second UK Theoretical Neuroscience Workshop*, taking place at *City St George’s, University of London*, on *Friday, 18 December 2026*. The workshop will bring together researchers and students working in theoretical, mathematical, and computational neuroscience for a day of invited *talks, poster presentations,* and *discussion*. 📍 *Venue:* City St George’s, University of London 📅 *Date:* Friday, 18 December 2026 🕘 *Time:* 09:00–17:30 💡 *Programme:* Invited talks, poster sessions, discussions, and a *poster award* Invited speakers include researchers from UCL, Oxford, Warwick, Nottingham, Birmingham, and Edinburgh, covering topics across neural dynamics, learning, network modelling, motor control, functional connectomics, temporal inference, and related areas. Further information, including the programme and abstracts, is available Here <https://dpinotsis.wixsite.com/uk-theoretical-neuro> Please feel free to circulate this announcement among interested colleagues and students. Best wishes, UK Theoretical Neuroscience Workshop Organisers Professor Steve Coombes Dr Dimitrios Pinotsis

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Open PhD and postdoc positions in computational neuroscience/neuroAI
by Roxana Zeraati Sept. 26, 2026

Sept. 26, 2026

Dear all, We are inviting applications for the following collaborative PhD and postdoc positions in computational neuroscience/neuroAI: - PhD (based at TU Dresden, Germany): https://nextcloud.tuebingen.mpg.de/index.php/s/wbpcYQ5pgMjDJos - Postdoc (based at the Max Planck Institute for Biological Cybernetics, Germany): https://nextcloud.tuebingen.mpg.de/index.php/s/wjKjAHRidF5R4M8 We, the Natural Decision Making Group and the Embodied Decision Making Group, are joining forces within the CMC Unit <http://cmclab.org/> to uncover the computational, biological, and ecological principles underlying adaptive decision-making. We combine computational methods from reinforcement learning, dynamical systems, and AI with analyses of neural and behavioral data to investigate how different species adapt their decisions to the dynamics of their natural environments, while accommodating their embodied constraints. We would appreciate it if you could share these calls with anyone who might be interested in your network. Best wishes, Roxana and Shervin

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postdoc or staff scientist
by Canavier, Carmen C. Sept. 25, 2026

Sept. 25, 2026

Carmen Canavier at LSU Health Sciences Center in New Orleans is recruiting a computational neuroscientist(s) at the postdoctoral or staff scientist level. One project involves modeling the local circuit in the medial entorhinal cortex with respect to theta nested gamma and grid cell activity and the other involves modeling the local circuit in hippocampal area CA1 with respect to cholinergic modulation and place field formation. Please email me at ccanav(a)lsuhsc.edu<mailto:ccanav@lsuhsc.edu> for details.

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Postdoctoral position: Computational neuroscience, nonlinear dynamics, and control (University of Arizona)
by drew＠arizona.edu Sept. 24, 2026

Sept. 24, 2026

The Maurer laboratory in the Department of Neuroscience at the University of Arizona is recruiting a postdoctoral researcher interested in theoretical and computational approaches to neural dynamics. A central question is how inhibitory circuitry reshapes the states and transitions available to a recurrent neural network: not simply by reducing excitation, but by dynamically restricting, routing, and stabilizing trajectories through neural state space. We are particularly interested in whether relatively low-dimensional inhibitory or feedback signals can reorganize high-dimensional population activity, alter attractor structure and metastability, regulate transitions among network states, and stabilize circuits that would otherwise be unstable or chaotic. The position sits deliberately between theory and experiment. The researcher will have access to large-scale electrophysiological datasets including neuronal spiking, LFP, EEG, behavior, and circuit perturbations. The goal is to develop mechanistic models that generate discriminating predictions and can be tested against experimental interventions, rather than simply fitting models to neural data. We welcome applicants from computational neuroscience as well as control theory, nonlinear dynamical systems, applied mathematics, engineering, physics, computer science, and related quantitative fields. Prior neuroscience experience is not required. The position is full-time at the University of Arizona in Tucson, with salary according to NIH guidelines and full benefits. Applications are open until the position is filled. University of Arizona posting: req27102 Application materials: CV, cover letter, and statement of research interest. For informal questions, please contact: Andrew P. Maurer, PhD Associate Professor, Neuroscience University of Arizona drew(a)arizona.edu

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Upcoming Open Lab Online seminars and workshops
by Nada El Mahmoudi Sept. 24, 2026

Sept. 24, 2026

Dear all, We are happy to share several upcoming Open Lab Online events on open tools, training, and methods in neuroscience and behavior. Open Lab Online is an international initiative that organizes accessible online seminars and workshops around open-source tools, experimental methods, and training across neuroscience and behavior. Animal Training Methods Across Species From Experimental Design to Naturalistic Behavior This seminar series will explore how animals are trained to interact with experimental tasks, touchscreens, vehicles, virtual environments, and naturalistic paradigms. First confirmed speakers include Kelly Lambert, Jennifer Taylor-O’Connor, Rainer Friedrich, Matthew Isaacson, and Marieke Schölvinck & Martha Nari Havenith, with additional seminars to be announced. Dates: 14 October, 4 November, 25 November, 20 January, 10 February Time: 16:00 CEST / 10:00 EDT for 14 October; 16:00 CET / 10:00 EST from November Full program and registration: https://nenckiopenlab.org/animal-training-methods-across-species/ Neural Data Analysis with Open-Source Tools From Raw Signals to Behavior-Linked Activity This hands-on workshop series will introduce an open-source workflow for neural data analysis, taught directly by the developers of the tools. The series will cover: SpikeInterface → Bombcell → Pynapple → NeMoS Part 1: Spike Sorting and Curation 19–20 October, 15:00–18:00 CEST / 09:00–12:00 EDT each day Modules: SpikeInterface + Bombcell Part 2: Behavior-Linked Analysis and Modeling 26–27 October, 14:00–15:30 CET / 09:00–10:30 EDT each day Modules: Pynapple + NeMoS Full program and registration: https://nenckiopenlab.org/neuraldata/ Bonsai Module I Workshops We will also host two Bonsai Module I workshops for participants interested in behavioral experiments, video tracking, closed-loop systems, and real-time data acquisition. 29 September, 16:00 CEST / 10:00 EDT https://nenckiopenlab.org/event/2200/ 13 October, 16:00 CEST / 10:00 EDT https://nenckiopenlab.org/event/bonsai-module-i-2/ Please feel free to share these events with anyone who may be interested. To receive future Open Lab Online announcements, you can subscribe to the mailing list here<https://5584ba20.sibforms.com/serve/MUIFADA4d4FHqdFYLj0P-heCkOQ5zMtIUiggjmg…>. You can also join the Open Lab Online Discord here<https://discord.gg/z7gvyj9yrV>. Best wishes, The Open Lab Online Team Dr. Nada El Mahmoudi Post-doctoral researcher, Peyrache lab The Neuro (Montreal Neurological Institute) McGill University, Canada

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Announcement: daftar 1.0 — recording what produced each computational result
by Aslan Satary Dizaji Sept. 24, 2026

Sept. 24, 2026

Dear all, I would like to share an open-source tool that may be useful to people running simulations and model fits. The problem. Experiment trackers such as MLflow and Weights & Biases assume an experiment is a training loop with epochs, losses and checkpoints. A Hodgkin–Huxley simulation, a hierarchical fit across participants, or an EEG preprocessing pipeline has none of those. Months later it is often impossible to say which code version, environment and seed produced a given figure. What it does. One decorator or context manager around existing code records the environment, git state, every parameter, every seed, and content hashes of inputs into a plain-JSON manifest. daftar diff then compares two runs and separates fields that could have caused a difference from fields that merely record one — including the case where results differ and nothing that could have caused it does, which is a finding rather than a glitch. Seeds are applied rather than merely recorded, since noting that a run was irreproducible does not help anyone. Ten adapters record framework-specific state a generic tracker cannot infer: the integration method Brian2 auto-selected (it is stored nowhere), which ICA components were excluded in MNE, which confounds were regressed out in Nilearn, whether a NEURON compiled mechanism is stale relative to its .mod sources. No dependencies, no server, no account, no network access. Apache 2.0. Currently in peer review at pyOpenSci. pip install daftar https://github.com/aslansd/daftar One thing that emerged from building it, which may interest this list: four independent frameworks (MNE, cpm, Brian2, sbi) all report only one of the two reasons an optimiser stops. A fit that hit its iteration limit is indistinguishable from one that converged. I would welcome criticism, particularly from anyone who has previously tried a reproducibility tool and stopped using it. Aslan Satary Dizaji https://turan-cybernetics.com/ https://sites.google.com/a/umich.edu/aslansdizaji

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30 RTAIM Online Seminar - "Assessing the Ethical Risks of AI-Based Tools for Causal Inference from Real-World Evidence (RWE) in Medicines Evaluation"
by steven gouveia Sept. 23, 2026

Sept. 23, 2026

[??] 30 RTAIM Online Seminar [??] 24 September | 14:00 (Porto) [??] Online via Microsoft Teams Tamas Soroncz-Szabo Physician, epidemiologist, visiting lecturer in clinical research methods, and medical project expert for the European Health and Digital Executive Agency (HaDEA). [???] Assessing the Ethical Risks of AI-Based Tools for Causal Inference from Real-World Evidence (RWE) in Medicines Evaluation The talk will examine how AI is increasingly used to analyse real-world health data for medicines evaluation — and the ethical and regulatory risks that arise when AI-supported conclusions can influence efficacy, patient safety, and healthcare decisions. [??] Join: https://teams.microsoft.com/meet/389914877372834...<https://teams.microsoft.com/meet/389914877372834?p=2VyrR9YvPfgVE9glG6&fbcli…> Meeting ID: 389 914 877 372 834 Passcode: Vn95Mb6h More info: https://ifilosofia.up.pt/activities/seminar-30-rtaim

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New PhD & Postdoc Opportunities in Computational Neuroscience & Computational Psychiatry
by Nadja R. Ging Jehli Sept. 23, 2026

Sept. 23, 2026

Dear colleagues, We are building a new computational modeling hub at the University of Arizona - join us and grow with us! Ari Kahn and I are joining forces to build a closely connected computational community across two complementary labs at the intersection of decision science, cognitive neuroscience, and computational psychiatry. Together, the Kahn Lab and the NAIADEL Lab are recruiting multiple PhD students for Fall 2027 as well as postdoctoral researchers. Our groups tackle some shared questions from complementary angles: The Kahn Lab studies how people build predictive models of complex environments, use them to plan, and select among planning strategies. This work draws on reinforcement learning, successor representations, network science, control theory, and neuroimaging. Learn more here: www.kahnlab.org<https://www.linkedin.com/safety/go/?url=http%3A%2F%2Fwww%2Ekahnlab%2Eorg&ur…> The NAIADEL Lab studies how humans and artificial agents infer whether their actions matter, adapt when control shifts, and decide whether to persist, switch, or disengage after setbacks. This work draws on reinforcement learning, sequential sampling models, neural networks, and economic theory. Learn more here: www.naiadel.com<https://www.linkedin.com/safety/go/?url=http%3A%2F%2Fwww%2Enaiadel%2Ecom&ur…> Where we converge: We are especially excited about the intersection of meta-learning and meta-control. How do adaptive agents, biological or artificial, select among strategies? How do they recognize when a strategy is failing? And how do they revise their internal models under uncertainty and partial control? Trainees will be based primarily in one lab while benefiting from joint research meetings, shared computational infrastructure, and opportunities for cross-lab collaboration and co-mentorship. How to get involved: Prospective PhD students: Drop us a line with your CV and research interests. The Fall 2027 Psychology PhD application window opens October 15: Ph.D. Cognition and Neural Systems | Psychology<https://psychology.arizona.edu/cns> Postdoctoral candidates and other inquiries: Reach out directly with your CV and a brief statement of your research interests. arikahn(a)arizona.edu<mailto:arikahn@arizona.edu> nadjaging(a)arizona.edu<mailto:nadjaging@arizona.edu> We are very grateful for anyone who shares this within their broader network. Best, Nadja Nadja R. Ging-Jehli, PhD Assistant Professor Neurocomputation, Adaptive Intelligence, Agency Dynamics, & Embodied Learning (NAIADEL Lab) | www.naiadel.com<http://www.naiadel.com/> Cognition and Neuroscience Systems, Department of Psychology University of Arizona (614) 736-7755 | nadjaging(a)arizona.edu<mailto:nadjaging@arizona.edu> | nadja(a)gingjehli.com<mailto:nadja@gingjehli.com> | gingjehli.com<https://www.gingjehli.com/> [A button with "Hear my name" text for name playback in email signature]<https://www.name-coach.com/nadja-gingjehli>

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Call for Papers: ACML 2026 (Encore Track)
by Levin Kuhlmann Sept. 22, 2026

Sept. 22, 2026

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

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NeuroData AI Summer School: applications open for July 2027 at HHMI-Janelia
by Ben Dichter Sept. 22, 2026

Sept. 22, 2026

Applications are open for the NeuroData AI Summer School, a one-week residential program on reanalyzing open neurophysiology data, July 19 to 24, 2027 at HHMI's Janelia Research Campus in Ashburn, Virginia (arrive July 18, depart July 24 or 25). The school continues NeuroDataReHack, which ran five times from 2022 to 2026, and is now supported by a five-year NINDS R25 award. Participants learn to find, stream, and analyze NWB datasets on the DANDI Archive with tools such as SpikeInterface, Pynapple, NeMoS and Neurosift, and spend most of the week in small teams on a reanalysis project of their own. New this year is a track on AI methods for neural data, from foundation models to working effectively and responsibly with coding agents. Lectures are given by the people who build the tools, and every lecture is recorded and published. The school is free to attend. Lodging and meals are covered, and funding for travel is available. We welcome PhD students, postdocs, and faculty from all areas of neuroscience with basic Python or MATLAB experience. Preference goes to applicants with a specific reanalysis project in mind. Applications close January 29, 2027 and are reviewed on a rolling basis: https://neurodata-ai.org/apply <https://neurodata-ai.org/apply/?utm_source=SOURCE&utm_medium=email&utm_camp…> Past projects, recorded lectures, and reports from previous years: https://neurodata-ai.org <https://neurodata-ai.org/?utm_source=SOURCE&utm_medium=email&utm_campaign=a…> Questions: ben.dichter(a)catalystneuro.com Ben Dichter Program Director, NeuroData AI Summer School

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Call for applications: Gatsby Unit PhD Programme 2027 entry
by I-Chun Lin Sept. 22, 2026

Sept. 22, 2026

4-Year PhD Programme in Theoretical Neuroscience and Machine Learning Deadline: 17:00 GMT, Monday 9 November 2026 Applications are now open for the 2027 intake of the Gatsby Unit PhD programme at University College London (UCL). Students study toward a PhD in either machine learning or theoretical neuroscience, with minor emphasis in the complementary field. New students will join at the start of the academic year in September. First-year courses provide a solid foundation in machine learning, theoretical neuroscience and systems neuroscience, after which students pursue PhD projects specialising in machine learning, theoretical neuroscience, or both. Students benefit from close interaction with researchers at the Sainsbury Wellcome Centre for Neural Circuits and Behaviour and the ELLIS Unit at UCL, alongside strong links with other research groups across UCL and beyond. Full funding is available regardless of nationality. The studentship covers UCL tuition fees for both home and international students and includes an annual tax-free stipend as well as travel budget for attending conferences and workshops. We also welcome applicants who have secured, or are seeking, funding from other sources. The applicant should have a strong analytical and mathematical background, a keen interest in neuroscience, machine learning or both, and a relevant first degree, for example in Mathematics, Statistics, Computer Science, Engineering, Physics, Neuroscience or Cognitive Psychology. Applications should be submitted directly to us through the Gatsby Recruitment Portal. Please review the information on the programme webpage (www.ucl.ac.uk/life-sciences/gatsby/study-and-work/gatsby-unit-phd-programme<http://www.ucl.ac.uk/life-sciences/gatsby/study-and-work/gatsby-unit-phd-pr…>) carefully before starting your application. About the Unit The Gatsby Computational Neuroscience Unit is a leading research centre focused on theoretical neuroscience and machine learning. Our research focuses on the mathematical principles of learning, perception, cognition and action in brains and machines. We study causality; neural systems; neural representations; neural data analysis; computation and dynamics; learning; theory of deep learning; reinforcement learning; kernel methods; graphical models; Bayesian statistics; network and relational data. For more information on our research, visit www.ucl.ac.uk/life-sciences/gatsby/research<https://www.ucl.ac.uk/life-sciences/gatsby/research>. We are a community of around 50 academic, research and support staff, and students, committed to building an inclusive and supportive research environment. We function as far as possible as a single research group, with strong cohesion fostered via unit-wide activities such as tea hours, external seminars and journal clubs. Many leading researchers in machine learning and theoretical neuroscience have studied or worked in the Unit, including two Nobel Prize winners. Over 40% of our PhD and postdoctoral alumni hold faculty positions, while around 30% work in research development roles at companies such as Google DeepMind (itself founded by two of our alumni), Meta and Anthropic. Find out more about our faculty members and network of alumni at www.ucl.ac.uk/life-sciences/gatsby/people<https://www.ucl.ac.uk/life-sciences/gatsby/people>. -- I-Chun Lin Scientific Programme Manager Gatsby Computational Neuroscience Unit, UCL

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Patagonian School of Science: Application deadline extended to 25 September 2026
by Ines Samengo Sept. 21, 2026

Sept. 21, 2026

The deadline to apply for the Patagonian School of Science "Dynamics of Large-Scale Neural Systems" has been extended to September 25. The school will take place from December 8–19, 2026, at Brazo Huemul, on the northern shore of Lake Nahuel Huapi in Patagonia, Argentina. The school will bring together 20–25 PhD students and postdocs with international researchers to explore how large populations of neurons give rise to behaviour. The faculty includes Edvard Moser (2014 Nobel Laureate), Rafael Yuste, Susanne Schreiber, Carina Curto, Nachum Ulanovsky, Soledad Gonzalo Cogno, Christian Machens, Iván Davidovich, Valeria Della Maggiore, Emilio Kropff and Inés Samengo. The school will combine lectures, student presentations, workshops, discussions, and one-to-one interactions with faculty. It will take place in a remote setting with limited connectivity, creating an environment where participants can focus on scientific discussion and face-to-face interaction. Applications are open until September 25, 2026. The registration fee is USD 1,200 and includes accommodation and meals for the duration of the school. *Financial support may be available for students who do not have sufficient institutional funding.* Full information about the programme, faculty, and application process is available here: https://ib.edu.ar/patagonian_school_sciences2026/ Enquiries: psos(a)ib.edu.ar

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Call for Papers-ICICIP 2027, Vientiane and Luang Prabang, February 8-14, 2027 (Submission deadline: October 1, 2026)
by Nian Ashlee Zhang Sept. 20, 2026

Sept. 20, 2026

*Call for Papers* Conference website: https://conference.cs.cityu.edu.hk/icicip/ The 15th International Conference on Intelligent Control and Information Processing (ICICIP 2027) will be held in Vientiane and Luang Prabang (the present and former capitals of Laos), from February 8-14, 2027. The conference will take place at rich historical and cultural sites, including two on UNESCO's World Heritage List and Tentative List. Building on the successes of previous events, ICICIP 2027 aims to provide a high-level international forum for scientists, engineers, and educators to present state-of-the-art research and applications across related fields. The conference will feature pre-conference, tutorials, plenary speeches given by world-renowned scholars, regular sessions with broad coverage, special sessions focusing on popular topics, and post-conference tutorials/workshops in conjunction with the main event. Authors are invited to contribute high-quality papers to ICICIP 2027. In addition, proposals for special sessions within the conference's technical scope are solicited. Special sessions, organized by internationally recognized experts, aim to bring together researchers on focused topics. Papers submitted for special sessions are to be peer-reviewed using the same criteria as for contributed papers. Researchers interested in organizing special sessions are invited to submit brief proposals to the ICICIP 2027 special sessions chairs. A special session proposal should include the session title, a brief description of the scope and motivation, names, contact information, and brief biographical information on the organizers. Authors are invited to submit full-length papers (the nominal number of pages is 10) by the submission deadline through the online submission system. Special session organizers are also invited to enlist six or more papers with cohesive topics to form special sessions. The submission of a paper implies that the paper is original and has not been submitted under review or is not copyright-protected elsewhere, and will be presented by an author if accepted. All submitted papers will be refereed by experts in the field based on the criteria of originality, significance, quality, and clarity. The authors of accepted papers will have the opportunity to revise their papers and incorporate the referees' comments and suggestions. Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore's scope and quality requirements. Selected high-quality papers may be included in several journal special issues. The paper submission system is now open. Submission link: https://openreview.net/group?id=IEEE.org/ICICIP/2027/Conference *Submission deadline: October 1, 2026*

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Postdoctoral Scholar Neuroimaging
by Ayan Sengupta Sept. 18, 2026

Sept. 18, 2026

*WE ARE HIRING!* The University of Nevada, Las Vegas invites applications for Postdoctoral Scholar in Neuroimaging. Please apply here <https://nshe.wd1.myworkdayjobs.com/en-US/UNLV-external/job/UNLV1-Main-Campu…> . ------------------------------------------------- Ayan Sengupta, Ph.D. Assistant Professor, University of Nevada, Las Vegas

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SNUFA 2026 abstract submission deadline in one week (Sept 25)
by Friedemann Zenke Sept. 18, 2026

Sept. 18, 2026

This is a quick reminder that the abstract submission deadline for SNUFA 2026 is one week away: September 25, 2026 (anywhere on earth). SNUFA 2026 takes place 4-5 November 2026 (online), with invited talks from Giulia D'Angelo (Czech Technical University in Prague), Eugene Izhikevich (Brain Corp and DeepSpike), Mihai Petrovici (University of Bern), and Susanne Schreiber (Humboldt University). If you're planning to submit an abstract on spiking neural networks, learning algorithms, or the analysis of trained spiking circuits, now's the time-submission and registration are open at https://snufa.net/2026. Looking forward to your submissions! SNUFA 2026 is brought to you by Sacha van Albada, Jason Eshraghian, Dan Goodman, and Friedemann Zenke

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2027 NICE Conference in Brighton, UK April 6-8 2027
by Aimone, Brad Sept. 17, 2026

Sept. 17, 2026

NICE 2027 will be held 6th - 9th April in Brighton, United Kingdom. The 2027 Neuro-Inspired Computing Elements (NICE) Conference is the 14th annual meeting of researchers in the neural computing, neuromorphic, and NeuroAI fields. Like previous editions, NICE 2027 will focus on the interplay between neural theory, neural algorithms, neuromorphic architectures and hardware, and applications for neural computing technology. NICE aims to involve diverse participation from all over the world and bring together research communities with universities, government, and industry. For venue details, agenda information and registration please see https://niceworkshop.org/nice-2027/ Submission Guidelines Regular papers (4-8 pages, not including references, no supplemental material) will be due 11th November via https://easychair.org/cfp/nice2027. Papers will be reviewed by the program committee on the basis of quality and clarity of the work (not length). Papers should cover unpublished work and emphasize the novel aspects and potential impact on the neural computing community. From these submissions we will invite several full talks (25 minutes), lightning talks (10 minutes), with the option to be published as an online proceedings volume (details below). An additional set of submissions will be invited for poster presentations, but may not be included in the proceedings. The 2027 NICE proceedings will be published and indexed through IEEE Conference Proceedings this year. Important Dates * Regular Paper Due Date: 11th November 2026, Anywhere on Earth (AoE) * Regular Paper/ Abstracts Decision Notification: 20th December 2026 * Late Breaking News Abstracts Due: 1st February 2027, AoE * Late Breaking News Abstracts Decision Notification: 16th February 2027 * Camera Ready Papers Due: 9th March 2027 AoE * Conference (Talks): 6th - 8th April 2027 * Conference (Tutorials): 9th April 2027 List of Topics A full list of topics is in the Call for Papers (https://easychair.org/cfp/nice2027) NICE focus areas span the whole field of neuromorphic computing and theoretical neuroscience, including algorithm development, neurally inspired frameworks, hardware architectures, sensing technologies, software frameworks, and applications. During submission, please indicate which of the following topics your paper impacts.

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PhD position in computational neuroscience at University of South Carolina
by Z S Sept. 16, 2026

Sept. 16, 2026

Dear all, Dr. Sha’s lab (https://shazhiqiang.wixsite.com/sha-lab) at the University of South Carolina is seeking *PhD students in computational neuroscience *in the Department of Psychology. 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, 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 computational modeling (e.g., deep learning models) 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 machine learning models and neuroimaging, supported by the brand-new Brain Imaging Center (with 3T and 7T MRI scanners) and the Biobehavioral Research Center at the University of South Carolina. This position provides an excellent opportunity for a self-motivated student to gain hands-on experience with neuroimaging (e.g., MRI) and biomedical research techniques. The candidate will have full access to rich in-house and public datasets, and advanced neuroimaging platforms. Our lab fosters a collaborative and productive environment, and we actively support PhD students in generating high-quality research publications, applying for fellowships and securing their future career paths. Key roles: · Data analysis; present results and publish papers under the PI’s supervision · Keep up-to-date on relevant studies and methods, and actively discuss them with the PI · Present your work at national and international conferences Requirements: · Bachelor’s or Master’s degree in a relevant field (e.g., computational neuroscience, math, data science, biostatistics, biomedical engineering) · Experience with neuroimaging MRI data analysis is preferred. · 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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NITMB Fellowships Call for Applications
by William L. Kath Sept. 16, 2026

Sept. 16, 2026

*NITMB Fellowships Call for Applications* NITMB is seeking early-career researchers who have an interest in transforming biological research and inspiring new mathematical discoveries. This opportunity is open to researchers who want to develop mathematical, theoretical, and computational approaches to study any area of biology. This position is open to individuals less than seven years post-attainment of their Ph.D. degree. Applicants will need to have completed a doctoral degree by September 1, 2027 in one of the following fields: * Mathematical and Physical Sciences * Biological Sciences * Computer Science * Engineering * or related fields For full consideration, applications must be submitted by *November 15, 2026.* See here for more information: https://www.nitmb.org/nitmb-fellows-program/ Apply here: https://www.mathjobs.org/jobs/list/28792

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Late-breaking poster abstract submission for the 32nd Annual Computational Neuroscience Meeting ends on June 15
by Rubchinsky, Leonid L Sept. 16, 2026

Sept. 16, 2026

Dear Colleagues, We would like to remind that the late-breaking poster abstracts submission at CNS*2023 ends on June 15. CNS*2023, 32nd Annual Computational Neuroscience Meeting, will be in Leipzig, Germany, on July 15-19, 2023. The information about the meeting and abstract submission can be found here: Registration: https://ocns.memberclicks.net/cns-2023-registration Abstract submission: https://www.cnsorg.org/cns-2023-abstract-submission CNS*2023 information: https://www.cnsorg.org/cns-2023 With kind regards, Leonid Rubchinsky OCNS Vice President *********************** Leonid Rubchinsky, PhD Professor Department of Mathematical Sciences, Indiana University Purdue University Indianapolis Stark Neurosciences Research Institute, Indiana University School of Medicine 402 N. Blackford St Indianapolis, IN 46202-3216 lrubchin(a)iupui.edu http://www.math.iupui.edu/~lrubchin ***********************

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Postdoctoral positions in sensory coding and memory - University of Sheffield
by Andrew Lin Sept. 15, 2026

Sept. 15, 2026

Why are brains the way they are? Do neural circuits function in an “optimal” way, and if so, in what sense are they optimal? How does the brain encode sensory information and form associative memories? Andrew Lin’s lab at the University of Sheffield is seeking up to two Research Associates to study these questions in the fruit fly Drosophila. We study memory using a range of methods, such as in vivo two-photon calcium imaging, electrophysiology, fly genetics, behavioural experiments, computational modelling and building custom equipment. You will design, develop and perform experiments and data analysis (tailoring the project to your own interests and expertise), write papers, and present your work at conferences and seminars. We seek self-motivated, innovative and creative candidates with a PhD (or be close to completion / have equivalent postdoctoral level experience) in a relevant field, expertise in at least some of the above techniques, excellent communication skills, and an ability to work independently and in a team. We encourage applications from diverse academic backgrounds, such as biology, neuroscience, experimental psychology, computer science, physics and engineering. Closing date: 5 October 2026 Apply at this link: https://tinyurl.com/LinPostdoc2026 or https://jobsite.sheffield.ac.uk/job/Research-Associate-Neuroscience-%282-Po… More about the lab: https://www.aclinlab.org/ Start date is flexible - happy to discuss We welcome international applicants and the university will reimburse the post-holder for many visa expenses: https://www.sheffield.ac.uk/jobs/induction/before/international/visas For informal enquiries, contact Andrew: andrew.lin(a)sheffield.ac.uk -- Andrew Lin School of Biosciences University of Sheffield Firth Court Western Bank Sheffield S10 2TN +44 (0) 114 222 3643 http://www.aclinlab.org

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[DEALINE EXTENDED] Workshop on Whole-Brain Models and High-Order Interactions for Brain Health, Palma de Mallorca, Spain
by Rubén Herzog Sept. 15, 2026

Sept. 15, 2026

Dear colleagues, We are pleased to announce the Workshop on Whole-Brain Models and High-Order Interactions for Brain Health, which will take place at the University of the Balearic Islands (UIB), Palma de Mallorca, Spain, from 17 to 20 November 2026. EXTENDED Application deadline September 25th 2026 The workshop will bring together PhD students, postdoctoral researchers and early-career scientists interested in understanding how cognition, ageing and disease emerge from large-scale brain dynamics. Participants will be introduced to a range of theoretical and computational frameworks currently shaping systems neuroscience, including whole-brain modelling, machine learning, complex systems approaches and high-order information-theoretic methods. Through lectures, tutorials and interactive discussions, participants will learn how these tools can be used to bridge neural activity, cognition and brain health. Scientific topics include: • Whole-brain computational modelling • High-order interactions and multivariate information theory • Complex systems and network neuroscience • Machine learning in brain ageing and brain health • Neuroimaging and electrophysiology • Mechanistic approaches to cognition and disease A distinctive feature of the workshop is the close interaction between participants and faculty. Throughout the programme, attendees will work in interdisciplinary teams to develop original research proposals and receive direct feedback from internationally recognized researchers. The workshop is designed not only as a training opportunity but also as a platform for building future collaborations across disciplines and institutions. Further information, programme details and application instructions can be found at: https://rubenherzog.github.io/workshop-wbm-hoi-2026/ We would greatly appreciate your help in circulating this announcement among interested students, postdoctoral researchers and colleagues. Kind regards, Workshop Organizing Committee Workshop on Whole-Brain Models and High-Order Interactions for Brain Health University of the Balearic Islands (UIB)

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NeuroAI Assistant Professor Position at Carnegie Mellon University
by Aran Nayebi Sept. 14, 2026

Sept. 14, 2026

Dear colleagues, *TL;DR: CMU is hiring for an Assistant Professor in NeuroAI. Apply here: https://apply.interfolio.com/189268 <https://apply.interfolio.com/189268>* *Details below:* Carnegie Mellon University (CMU) invites applications for a tenure-track Assistant Professor in the Neuroscience Institute from scholars working broadly at the intersection of Neuroscience and Artificial Intelligence. We welcome a wide range of research programs, provided they maintain a substantive connection to neuroscience through data, theory, or modeling. Examples of relevant research topics include but are not restricted to: generative models of brain data, AI-based analysis tools for neural activity or connectivity, explainable AI grounded in cognitive/neuroscience principles, human-AI alignment, normative agentic models of animal behavior, mechanistic models of memory or learning in neural networks, descriptive models of invariant representations and dynamics, and embodiment in both natural and artificial systems. The successful candidate will join a vibrant, collaborative environment spanning multiple departments at CMU. Our NeuroAI group leverages CMU’s world-class research in machine learning and AI, robotics, cognitive and systems neuroscience, neurotechnology, data science, engineering, and biological sciences. Joint appointments and courtesy appointments across departments are common in the Neuroscience Institute, and may be an opportunity for some candidates. CMU has a well-established structure for interdisciplinary collaboration in this domain, including specialized programs in neural computation and machine learning, and neurorobotics. The NI also encourages collaboration with industry and commercialization of new ideas. Aspiring entrepreneurs can be supported by a variety of business resources at CMU such as the Swartz Center and new entrepreneurship initiatives. Candidate responsibilities include establishing a visible, externally funded research program; teaching and mentoring in NI; recruiting and supervising both masters and Ph.D. students; and contributing to curricular innovation, including emerging initiatives, such as a new masters program in neural technologies. Information about the Neuroscience Institute can be found at https://www.cmu.edu/ni/. For more information on CMU’s NeuroAI group, see CMU Builds on Its Strengths To Advance NeuroAI <https://www.cmu.edu/news/stories/archives/2026/august/cmu-builds-on-its-str…> *Qualifications* Qualifications include a Ph.D. or equivalent in neuroscience, machine learning, robotics, computer science, cognitive science/psychology, electrical engineering, or a related field; evidence of research excellence and potential for leadership; and a commitment to high-quality teaching and mentoring. *Application Instructions* Applicants should submit their materials via Interfolio. Required materials include a one-page cover letter describing fit to NI, CMU, and the collaborative Pittsburgh community in neuroscience, AI, and related disciplines; a research statement (three to four pages); a one- to two-page teaching statement; a curriculum vitae; and three letters of recommendation. Applicants may also submit an optional 1-page Personal and Service statement. Review of applications will begin immediately and all applications received by November 1st, 2026 will be given full consideration. The positions will be open until filled. The position will start July 1, 2027. Best, Aran -- Assistant Professor Machine Learning Department Neuroscience Institute (core faculty), Robotics Institute (by courtesy) Carnegie Mellon University https://cs.cmu.edu/~anayebi

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

Sept. 14, 2026

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

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COSYNE 2027: Meeting announcement, Abstract submission is now open
by Tomas Hromadka Sept. 11, 2026

Sept. 11, 2026

==================================================== Computational and Systems Neuroscience 2027 (Cosyne) MAIN MEETING & WORKSHOPS 11 - 16 March 2027 Montreal, Canada www.cosyne.org ==================================================== ---------------------------------------------------- MEETING ANNOUNCEMENT ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks is selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. All abstract submissions will be reviewed double blind. The deadline for Abstract submission is 18 October 2026. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, neuromodulation, and computation with spiking networks. We would like to foster increased participation from experimental groups as well as computational ones. Please circulate widely and encourage your students and postdocs to apply. IMPORTANT DATES Abstract submission is now open. Abstract submission deadline: 18 October 2026 When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. COSYNE INVITED SPEAKERS Dani Bassett (UPenn) Chand Chandrasekaran (Boston U) Christine Constantinople (NYU) Paul Cisek (U Montreal) Kevin Franks (Duke) Leslie P Kaelbling (MIT) Andy Leifer (Princeton) Scott Linderman (Stanford) Amy Orsborne (U Washington) Cengiz Pehlevan Kempner (Harvard) Kanaka Rajan (Harvard; Kempner Inst) Rebecca Saxe (MIT) Carsen Stringer (Janelia) ORGANIZING COMMITTEE General Chairs: Kimberly Stachenfeld (DeepMind) and Mark Histed (NIH) Program Chairs: Annegret Falkner (Princeton) and Guillaume Lajoie (MILA/U Montreal) Workshop Chairs: N Alex Cayco Gajic (ENS) and Marcelo Mattar (NYU) Tutorial Chairs: Eva Dyer (Georgia Tech) and Alex Williams (NYU) Mentorship and Networking Chairs: Renata Brito (Mount Sinai) and Srikanth Ramaswamy (Newcastle U) Undergraduate Travel Chairs: Lea Duncker (Columbia) and Kevin Miller (DeepMind) Development Chair: Michael Long (NYU) Media Chairs: Roxana Zeraati (MPI Biol Cybernetics) and Claire Sturgill (TU Dresden) Poster Design: Maja Bialon EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Anne-Marie Oswald (U Pittsburgh) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT meeting [at] cosyne.org ----------------------------------------------------- COSYNE MAILING LISTS ----------------------------------------------------- Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> About-> Mailing lists for details.

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NeuralNet 2026, Nov 25th-27th, Paris – Registration and Abstract Submission Now Open
by Arthur Leblois Sept. 11, 2026

Sept. 11, 2026

image.jpeg Dear colleagues, We are pleased to announce the opening of registrations for NeuralNet2026Paris (Nov. 25th-27th, Odéon Campus of Université Paris Cité, 75006 Paris, France) The program will explore four broad themes — Neural Codes & Representations, Perception in Context, Learning, Memory & Adaptation, and Brain States & Network Dynamics— bringing together leading researchers working across systems and computational neuroscience. We also encourage the submission of contributed talks and posters. Participants are invited to join the famous spike sorting mini-schoolbefore the conference (23-25 November). The mini-school is free of charge but registration is required. Info and registration on: https://neuralnet2026.sciencesconf.org/ We look forward to receiving your contributions and to welcoming you to Paris in November for three days of exciting science, discussion, and networking with the Systems and Computational Neuroscience community. Best regards, The NeuralNet 2026 Organizing Committee image.png

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Subject: Postdoc Position: Predicting Epilepsy from iEEG (University of Göttingen)
by Tristan Manfred Stöber Sept. 11, 2026

Sept. 11, 2026

Postdoctoral Position: Predicting epilepsy before it starts - Foundation models and bioplausible circuits on human intracranial EEG. QUICK FACTS - Salary: TV-L E13, 100% (€5,366-5,873/month) - Benefits: annual bonus, additional VBL pension - Duration: 12 months, extension intended - Start: as soon as you can, the data are ready - Place: CIDAS, Göttingen, Germany - Deadline: Applications rolling, first review 24 Sep 2026 In the group of Tristan Manfred Stöber at the Campus Institute Data Science (CIDAS), University of Göttingen. The project is conducted in close collaboration with our clinical and modelling partners in Frankfurt, specifically working directly with Michael Strüber from the Epilepsy Center Frankfurt and Richard Gao from Goethe University Frankfurt. WHAT IS THE POSITION ABOUT? Epilepsy care is reactive: we treat after the first seizure. But the disease starts earlier, after a head injury the brain reorganises for months to years, a window in which it could still be steered, and nobody can tell who is inside it. We have a unique way in. Roughly a quarter of patients with acute subdural hematoma develop post-traumatic epilepsy, and they are monitored with subdural electrodes within days of the injury, long before any seizure. Our Frankfurt partners hold those recordings with confirmed outcomes, plus a rodent dataset spanning the full course of epileptogenesis in over 85 animals. Two steps follow. TWO MODELS, ONE SET OF ACUTE RECORDINGS: WHO IS AT RISK, AND WHY. 1. Predict. Fine-tune an existing intracranial-EEG foundation model on the acute recordings, by self-supervised and contrastive learning, and test whether it separates patients who later develop epilepsy from those who stay resilient. There is a starting point: in our rodent model the aperiodic (1/f) exponent, a proxy for excitation/inhibition balance, tracks early epileptogenesis and predicts which animals become epileptic. Whether it transfers to humans is open, your first question. 2. Model. Then ask why. With AutoMIND, the deep inverse modelling framework of our partner Richard Gao (Goethe University Frankfurt), infer patient-specific parameters of a bioplausible cortical circuit from the same recordings, synaptic balance, adaptation timescales, conductances, turning a risk flag into a mechanism. A PILOT, AND WHY AGILITY IS THE POINT Twelve months will not solve post-traumatic epilepsy, and this position does not pretend to: it is a pilot, find out fast whether the rodent signal has a human counterpart. Nothing here waits on data collection or a method still to be invented, so agility is the operative skill: short cycles, a first result in weeks, a direction dropped once it stops paying off. It is one step in a bigger effort with our Frankfurt partners, the corresponding consortium proposal is under review, aiming eventually at a clinical means of preventing epilepsy instead of managing it. WHO ARE WE LOOKING FOR? - A PhD, or close to completion, in computer science, physics, mathematics, computational neuroscience, biomedical engineering or a related quantitative field. - Fluent programming and a solid command of modern deep learning on time series, self-supervised pretraining, transfer to small labelled sets. - Experience with neural recordings (EEG, iEEG, LFP) is a strong plus, as is simulation-based inference or circuit modelling for step 2. - The discipline clinical data demands: careful validation, no leakage across patients, precision about what you have actually checked. Nobody arrives with all of it. What matters more is the mindset: chasing the question rather than the result, and taking problems apart instead of waiting to be unblocked. Applications from any gender, country and walk of life welcome. WHAT DO WE OFFER? - A question with a clear clinical stake, and the data to attack it now. - Two collaborators you work with directly, both based in Frankfurt: Michael Strüber (Epilepsy Center Frankfurt) clinically, and Richard Gao (Goethe University Frankfurt) on modelling. - Close mentorship, and room to shape the project as it moves. - GWDG's Secure HPC environment for GDPR-relevant clinical data, already in place, plus budget for conferences and open-access publication. - A path beyond the 12 months: extension is intended. WHERE YOU WOULD BE CIDAS at University of Göttingen is a young place and it shows: it gathers machine learning, statistics and data science from across the campus into one institute, and much of it is run by early-career PIs building their groups right now, short paths, few hierarchies, a lot of momentum. Students, postdocs and professors also do things together outside the seminar room; the yearly road-bike tour up the Brocken is the one to train for. And Göttingen's scientific density is out of all proportion to its size, Gauss, Hilbert and Heisenberg worked here, several Max Planck Institutes next door. HOW TO APPLY One PDF motivation letter, CV, two referees to tristan.stoeber(a)posteo.net, subject "Postdoc - Epileptogenesis". Applications by 24 September 2026 receive full consideration; the position stays open until filled and we reply quickly. Unsure whether it is for you? Write to me before you apply. For more information about the group and our work, please visit our webpage at https://tristanstoeber.github.io.

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Postdoctoral and PhD Opportunities in Infant NeuroAI at Trinity College Dublin
by ainetdineen＠gmail.com Sept. 11, 2026

Sept. 11, 2026

Five Ways to Join the InfantNeuroAI Team! Infants are acquiring the brain representations that form the foundations of cognition. These representations are powerful: they let a child go on to master many tasks with remarkable speed. The InfantNeuroAI project aims to measure these developing representations, using awake infant neuroimaging with fMRI and OPM-MEG, and to model the developmental process using computational models from AI. The project has three goals. To better understand infant cognition. To develop neuroimaging methods that can detect disrupted function after neonatal brain injury. And to identify new, more energy-efficient learning algorithms that could reduce the economic and environmental cost of AI. Everyone on the project is involved end to end: setting up the imaging, designing experiments, acquiring data, analysing it, building computational models, presenting the work and writing it up. You will do all of this with Professor Rhodri Cusack and an interdisciplinary team of neuroscientists, cognitive scientists, neuroimagers and AI engineers. Postdoctoral Fellow in Awake Infant OPM-MEG You will lead the establishment of awake infant OPM-MEG in the lab, using our CERCA system, and carry that work through to experiments, analysis, modelling and publication. You will need good coding skills and expertise in at least one of the following, with a willingness to develop the others: • Cognitive neuroscience • OPM-MEG, MEG or EEG • Computational modelling using deep neural networks Full time for two years from November 2026. Salary €47,273–55,399 per annum, with pension contribution, PRSI social insurance and annual leave. Selection will begin on 4 October, 2026. Further details and how to apply: https://cusacklab-web.s3.amazonaws.com/infantneuroai_2026_researchfellow2_o… Postdoctoral Fellow in Awake Infant fMRI and NeuroAI You will lead the establishment of awake infant fMRI on our Siemens 3T Prisma, and use the resulting data to test and develop deep-neural-network models of how infants learn. You will need good coding skills and expertise in at least one of the following, with a willingness to develop the others: • Infant cognitive neuroscience • Neuroimaging with fMRI • Computational modelling using deep neural networks Full time for two years from January 2027. Salary €47,273–55,399 per annum, with pension contribution, PRSI social insurance and annual leave. Closing date: 4 October, 2026. Further details and how to apply: https://cusacklab-web.s3.amazonaws.com/infantneuroai_2026_researchfellow1_f… Three PhD Scholarships in Awake Infant fMRI and NeuroAI These scholarships offer rich training in neuroimaging methods, developmental cognitive neuroscience and computational modelling with deep neural networks. Working with Professor Cusack and the wider team, you will take part in the full research cycle using awake infant fMRI and/or OPM-MEG. You will need a Bachelor's degree in psychology, cognitive science, computer science or a related field, good coding skills, and expertise or strong interest in: • Cognitive neuroscience • Neuroimaging • Infant development • Deep neural networks Full time for four years, starting March or September 2027. Stipend of €25,000 per annum, plus fees and conference travel. Closing date: 4 October, 2026. Further details and how to apply: https://cusacklab-web.s3.amazonaws.com/infantneuroai_2026_phds.pdf About the lab The Cusack Lab is housed in the Trinity College Institute of Neuroscience (TCIN), which brings together 60 groups and 250 scientists to study the brain from molecules to mind to society, and spans fundamental research to clinical translation. TCIN houses a Siemens 3T Prisma MRI scanner, a CERCA OPM-MEG system and an NVIDIA GPU cluster. We are a diverse team and welcome applications from people of all backgrounds, including those under-represented in neuroscience and AI. We support visa applications for international appointees. Informal enquiries to Tamrin Holloway: admin(a)cusacklab.org InfantNeuroAI is funded by ERC Advanced Grant 101265741 and the Research Ireland Frontiers for the Future Award 2022.

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Call For Papers - UniReps Workshop in Paris 🔵🔴
by Organizers Sept. 10, 2026

Sept. 10, 2026

Hi all, We’re excited to announce the Call for Papers <https://unireps.org/2026/call-for-papers> for the 4th edition of the UniReps Workshop, happening in Paris <https://unireps.org/2026/>! The workshop is tentatively planned for mid-December, with a target date between December 11 and December 15, 2026, coinciding with NeurIPS. The exact date will be confirmed once the venue arrangements are finalized. You can indicate your preferred date using this form <https://forms.gle/nfpXEMiTWfoyKiX87>. Our workshop theme focuses on a central question: Why, when, and how do distinct learning processes yield similar representations, and to what extent can these be unified? Neural systems, whether artificial or biological, often converge on structurally similar internal representations when exposed to semantically related inputs. This workshop brings together researchers from Neuroscience, Artificial Intelligence, and Cognitive Science to build a unified understanding of this phenomenon and explore its theoretical and practical implications. We invite contributions addressing the following questions: - When? Under what conditions do similar representations emerge, and how can we measure this? - Why? What mechanisms, biological or computational, drive representational convergence? - What for? How can we harness this understanding for modular deep learning, model merging, transfer learning, and beyond? Topics of Interest Here’s a non-exhaustive list of themes we’re excited to explore, targeting especially their relationship with the questions listed above: - Model merging, stitching, and compositionality - Representational alignment and similarity measures - Identifiability and symmetry in neural models - Learning dynamics and mechanistic interpretability - Multimodal and multiview learning - Disentangled representations - Linear mode connectivity - Representation Similarity Analysis (RSA) - Multi-agent communication - Mechanistic interpretability - Representation universality Submission Tracks Full Paper (Archival) - Up to 9 pages (excluding references and appendix) - Anonymous submission - Published in dedicated workshop proceedings - Poster + spotlight opportunities Extended Abstract (Non-Archival) - Up to 4 pages - Anonymous submission - Poster + spotlight opportunities - Perfect for early-stage work, negative results, or opinion pieces Both tracks are eligible for best papers awards. Submit via OpenReview <https://openreview.net/group?id=UniReps.org/2026/Workshop> Deadline: 4th October 2026 (AoE) Join Our Program Committee We’re looking for dedicated reviewers to help maintain the high standard of our review process. Each reviewer is assigned no more than two submissions, and we’re planning to introduce Reviewer Awards to recognise outstanding contributions. Interested? Sign up here <https://docs.google.com/forms/d/e/1FAIpQLScGnnXH13fNw50Sm09oeXvTup-ZkpmSLq4…> to join the UniReps 2026 Program Committee. We look forward to your submissions and hope to see you at UniReps! Warm regards, The UniReps Organising Team

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Frontier Series 2026 / Translational Neurocognitive Technologies
by Vasiliki Kondyli Sept. 10, 2026

Sept. 10, 2026

Dear all, I would like to invite you to the next talk in the Frontiers Series, featuring Prof. Michael Schöll (University of Gothenburg, Sweden): Molecular Medicine, Neuroimaging and Biomarkers for Neurodegenerative Disease Date: September 16, 2026 Time: 14:00 (Amsterdam, Berlin, Rome, Stockholm, Vienna) For talk details, the full schedule, and registration information, please visit: https://codesign-lab.org/frontier26/ We look forward to seeing you there! Best wishes, Vasiliki ================================================================================================= CoDesign Lab EU is inviting you to a scheduled Zoom meeting. Topic: Frontier series 2026 / Prof. Michael Schöll (Molecular Medicine, Neuroimaging and Biomarkers for Neurodegenerative Disease) Time: Sep 16, 2026 14:00 Copenhagen Join Zoom Meeting https://oru-se.zoom.us/j/67604219242?pwd=tOTCRlSUbHpS2YmtBkvZrgvHrjeYQm.1 Meeting agenda https://docs.zoom.us/agenda/doc/ec726b06-f6ad-4c18-88db-e256e305b607 Meeting ID: 676 0421 9242 Passcode: 578478 ================================================================================================= FRONTIER SERIES 2026 / TRANSLATIONAL NEUROCOGNITIVE TECHNOLOGIES / Cognitive Neuroscience. Responsible AI. Clinical Application. / Örebro University and Lund University (Sweden) present the Frontier 2026 Talk Series centralising the themes of next-generation responsible neurocognitive technologies and translational clinical neuroscience. The series brings together researchers from neuroscience, artificial intelligence, cognitive science, engineering, and data science to explore the mechanisms of brain function in health and disease. The series emphasises interdisciplinary methodologies linking neuroimaging, molecular neuroscience, systems neuroscience, computational cognitive modelling, computer science, and cognitive science to drive innovation and societal impact with ecologically valid diagnosis, monitoring, and intervention in real-world clinical contexts. Participation is free, and all interested are welcome. Special opportunities exist for student participants (refer below). Details / https://codesign-lab.org/frontier26/ SPEAKER PANEL > / Germany (Ernst Strüngmann Institute for Neuroscience. Heinrich-Heine-University. Hertie Institute - University of Tübingen. Research Center Jülich. Freie Universität Berlin) \ Netherlands (Universiteit Leiden) \ Poland (Jagiellonian University in Kraków) \ Singapore (National University of Singapore) \ Sweden (University of Gothenburg. Karolinska Institute. Lund University) \ Taiwan (National Yang Ming Chiao Tung University) \ United States (Columbia University Medical Center. Georgia Institute of Technology) In order of planned schedule during 2026: — Prof. Simon Eickhoff (Heinrich-Heine-University & Research Center Jülich, Germany) “Clinical Brain Medicine 2.0 – The ABCD-J Platform for Digital Biomarker Research and mHealth” — Dr. Sankaraleengam Alagapan (Georgia Institute of Technology, United States) “Interpretability in Neurotechnology: Using Explainable AI to Identify Biomarkers in Deep Brain Stimulation” — Prof. Juan (Helen) Zhou (National University of Singapore, Singapore) “Multimodal Neuroimaging in Neuropsychiatric Disorders” — Prof. Esther Kuehn (Hertie Institute for Clinical Brain Research, Germany) “Translational Applications of Layer-Specific Multimodal MRI for Aging and Neurodegeneration” — Prof. Michael Schöll (University of Gothenburg, Sweden) “Molecular Medicine, Neuroimaging and Biomarkers for Neurodegenerative Disease” — Prof. Joana Braga Pereira (Karolinska Institute, Sweden) “Mapping Brain Connectivity in Aging and Neurodegeneration: From Molecular Markers to Brain Networks” — Prof. Ching-Po Lin (National Yang Ming Chiao Tung University, Taiwan) “MRI, Brain Connectomics, and Neuropsychiatric Disorders” — Prof. Mikael Johansson (Lund University, Sweden) “Decoding Episodic Memory: Neural Reinstatement and Eye Movement Dynamics in the Reconstruction of Past Events” — Prof. Marcin Leszczyński (Columbia University Medical Center, US & Jagiellonian University, Poland) “Neural Oscillations, Memory, and Neural (Dys)Function” — Prof. Ineke van der Ham (Universiteit Leiden, The Netherlands) “The Potential of Virtual Reality for Clinical Neuropsychology” — Prof. Radoslaw Martin Cichy (Freie Universität Berlin, Germany) “Empirical Vision Neuroscience for Next-Generation AI” STUDENTS > OBTAIN EDUCATIONAL CREDITS The Frontier 2026 series will also in parallel run in a seminar mode for those participants desirous of securing educational credits (e.g., as part of an accredited educational programme). Please contact the series co-ordinators (details below) for further information concerning this form of participation, including deadlines, participation process, and expected requirements towards obtaining course credit. COORDINATION — CONTACT Mehul Bhatt -and- Vasiliki Kondyli Örebro University -and- Lund University / Sweden CoDesign Lab EU / Artificial and Human Intelligence https://codesign-lab.org/ (Apologies for redundant distribution; kindly please forward as you see fit) När du skickar e-post till Lunds universitet behandlar vi dina personuppgifter i enlighet med gällande lagstiftning. Mer om hur dina personuppgifter behandlas hittar du på Lunds universitets webbplats<http://www.lu.se/integritet>. When you send emails to Lund University, we process your personal data in accordance with existing legislation. To find out more about the processing of your personal data, visit the Lund University website<https://www.lunduniversity.lu.se/about/contact-us/processing-of-personal-da…>. To unsubscribe from this list please go to https://cognitivesciencesociety.simplelists.com/confirm/?u=lz9fw6gtt3Laj1wp…

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cuttingEEG garden Groningen
by Jelmer Borst Sept. 9, 2026

Sept. 9, 2026

Dear all, From 21-25 September, we will be hosting a so-called garden of the global cuttingEEG conference <https://cuttingeeg.org/cuttinggardens2026/> in Groningen, the Netherlands. Cutting gardens is a multi-hub conference focusing on cutting edge M/EEG analysis methods. In the Groningen garden <https://cuttingeeg.org/cuttinggardens2026/gardens/groningen/>, we will have a morning programme in which we give tutorials on MNE <https://mne.tools/stable/index.html> (basic and ML), Unfold <https://www.unfoldtoolbox.org/> (EEG deconvolution), and HMP <https://github.com/GWeindel/hmp> (single trial EEG event detection), discuss BCI approaches and have a variety talks on recent EEG analysis methods. In the afternoons, we will be watching the global talks together. Please check our website <https://cuttingeeg.org/cuttinggardens2026/gardens/groningen/> for details and registration (125 euro for the whole week!). Hope to see you in Groningen! The organising committee, Andreea Sburlea Lisa-Marie Vortmann Olaf Dimigen Yiyue Zhang Osman Oguz Wouter Kruijne Jelmer Borst

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Postdoctoral Positions at Washington University in St. Louis
by rncao90＠gmail.com Sept. 8, 2026

Sept. 8, 2026

Hi All, The Multimodal Cognitive Neuroscience Lab (MCN Lab; PI: Runnan Cao, PhD) is recruiting two postdoctoral researchers to study visual and social cognition, computational neuroscience, and multimodal brain imaging. Applicants should have a strong background in fMRI and/or electrophysiology. Experience with 7T fMRI, computational modeling, machine learning/agentic AI, or neuroscience data-processing workflows is preferred. More details in https://crn2022.github.io/mmclab-washu.github.io/join.html (official website in progress) The lab is based in the Neuroimaging Labs Research Center at WashU Medicine, offering advanced imaging resources and extensive interdisciplinary collaborations. Please send a CV, brief description of research interests, and representative publications to r.cao(a)wustl.edu. Thanks, Runnan Cao Assistant Professor Radiology, Washington University in St. Louis

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[Jobs] 2 PhD + 1 Postdoc + 2 RA positions: hippocampus, world models, epilepsy (Göttingen)
by Tristan Manfred Stöber Sept. 7, 2026

Sept. 7, 2026

Dear all, I am looking for five people to join my group at the Campus Institute Data Science (CIDAS), University of Göttingen, Germany. We study how the brain builds and uses its internal model of the world, and how those principles can be reengineered in artificial neural networks. In parallel, we run a clinical line of work on epilepsy, applying machine learning tools to intracranial recordings from patients, together with the University Hospital Frankfurt. All positions are based in Göttingen and start as soon as possible. PH.D. STUDENT - HIPPOCAMPAL REPRESENTATIONS IN DYNAMIC ENVIRONMENTS TV-L E13 100%, 3 years Analyse an unpublished, large-scale in-vivo miniscope dataset: CA1 pyramidal cells tracked across 11 tasks and 34 days. Characterise how cognitive maps emerge, drift and are reused, from single cells to the geometry of the population manifold. In close collaboration with Tom McHugh (RIKEN CBS, Japan). PH.D. STUDENT - BRAIN-INSPIRED WORLD MODELS FOR DYNAMIC ENVIRONMENTS TV-L E13 100%, 3 years We distil inductive biases from normative hippocampus models and use these insights to build novel and powerful model-based deep RL agents. The goal: agents that plan over long horizons with interpretable internal representations. POSTDOCTORAL RESEARCHER - MACHINE LEARNING FOR EPILEPSY TV-L E13 100%, ~1 year with potential extension We try to predict epilepsy before it even starts. We use unique intracranial recordings from patients who suffered a bleed on the brain's surface, about one in three of whom go on to develop epilepsy. On these data we fine-tune EEG foundation models. We also build digital twin network models of individual patients, allowing us to simulate personalised prevention and treatment strategies. A collaboration with Michael Strüber and Felix Rosenow (University Hospital Frankfurt), and Richard Gao (Goethe University Frankfurt). RESEARCH ASSISTANTS (2 POSITIONS) Part-time, students welcome Support the projects above with calcium imaging data processing, behavioural tracking, software engineering and simulation experiments. A good entry point for a B.Sc. or M.Sc. thesis in the lab. PREREQUISITES Strong quantitative skills, fluency in Python, experience with machine learning, and genuine curiosity about both brains and machines. WHAT WE OFFER An interdisciplinary group at the interface of neuroscience and AI, a strong national and international network, and a generous ERC travel and publication budget for conferences such as NeurIPS, Cosyne and FENS. HOW TO APPLY Send your CV, a short motivation letter naming the position you are interested in, and contact details of two references to tristan.stoeber(a)posteo.net. Applications received by 24 September 2026 will receive full consideration; the positions remain open until filled. Internships and thesis projects outside these openings are always welcome. If you are unsure which position fits you best, or would like to hear more about a project before applying, write to me at the same address. I am happy to talk first. More about the lab at [1]. Best regards, Tristan [1] https://tristanstoeber.github.io -- Tristan Manfred Stöber, Ph.D. Computational Neuroscientist CIDAS Fellow, Campus Institute Data Science, University of Göttingen Research Fellow, Dept. of Neurology, University Hospital Frankfurt

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Application deadline approaching: Patagonian School of Science
by Ines Samengo Sept. 7, 2026

Sept. 7, 2026

There are still a few days left to apply for a summer school — actually, a late-spring school in the Southern Hemisphere — taking place in mid-December. The Patagonian School of Science “Dynamics of Large-Scale Neural Systems” will take place from December 8–19, 2026, at Brazo Huemul, on the northern shore of Lake Nahuel Huapi in Patagonia, Argentina. The school will bring together 20–25 PhD students and postdocs with international researchers to explore how large populations of neurons give rise to behavior. The faculty includes Edvard Moser (2014 Nobel Laureate), Rafael Yuste, Susanne Schreiber, Carina Curto, Nachum Ulanovsky, Soledad Gonzalo Cogno, Christian Machens, Iván Davidovich, Valeria Della Maggiore, Emilio Kropff and Inés Samengo. The school will combine lectures, student presentations, workshops, discussions, and one-to-one interactions with faculty. It will take place in a remote setting with limited connectivity, creating an environment where participants can focus on scientific discussion and face-to-face interaction. Applications are open until September 15, 2026. The registration fee is USD 1,200 and includes accommodation and meals for the duration of the school. *Financial support may be available for students who do not have sufficient institutional funding.* Full information about the program, faculty, and application process is available here: https://ib.edu.ar/patagonian_school_sciences2026/ Enquiries: psos(a)ib.edu.ar

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Announcing SNUFA 2026: Nov 4-5 (online) - Abstract submission and registration now open!
by Friedemann Zenke Sept. 3, 2026

Sept. 3, 2026

We are happy to announce SNUFA 2026, taking place 4-5 November 2026 (online)---your friendly online focus meeting on spiking neural networks that compute. Abstract submission and registration are now open! See https://snufa.net/2026 for details. This year's invited speakers are Giulia D'Angelo (Czech Technical University in Prague), Eugene Izhikevich (Brain Corp and DeepSpike), Mihai Petrovici (University of Bern), and Susanne Schreiber (Humboldt University). Like every year, the workshop brings together researchers in computational neuroscience, machine learning, and neuromorphic engineering to present their work and discuss how to translate these findings into a better understanding of neural circuits. Topics include artificial and biologically plausible learning algorithms and the dissection of trained spiking circuits toward understanding neural processing. We have a manageable number of talks with ample discussion time. Attendance is free, but registration is required. Abstract submission deadline: September 25, 2026 (anywhere on earth) SNUFA 2026 is brought to you by Sacha van Albada, Jason Eshraghian, Dan Goodman, and Friedemann Zenke ------------------------------------------------------------------------ https://snufa.net/2026

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Postdoctoral and PhD Positions in Computational Neuroscience & Machine Learning at UCLA
by Marcus Triplett Sept. 2, 2026

Sept. 2, 2026

Dear All, The Triplett Lab at UCLA is recruiting for multiple postdoctoral and PhD positions in computational neuroscience and machine learning. Projects will span two broad areas: - Statistical machine learning methods for neural data analysis, such as inference of neural circuit connectivity and plasticity rules from large-scale imaging, electrophysiology, circuit perturbation, and behavioral data. - Computational models of cognition, including how neural systems form representations of causal structure and use them for decision-making or planning. Projects will combine neural circuit models and interpretability techniques (e.g. dynamical systems analysis) with behavioral and/or intracranial data to identify and test candidate mechanisms. Postdoctoral applicants should have (or expect to soon receive) a PhD in a quantitative field such as Computational Neuroscience, Applied Mathematics, Computer Science, or a related area. Prospective PhD students must first be admitted to an appropriate UCLA graduate program, such as Neuroscience, Computer Science, or Bioengineering. Interested applicants are encouraged to contact Marcus Triplett ( marcustriplett(a)ucla.edu) with a CV and brief description of past and future research interests. For more details visit triplett-lab.org. AA/EOE.

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Submit to Collection: Computational and Theoretical Approaches to Multi-Scale Dynamics from Cells to Behavior
by DEPANNEMAECKER Damien Sept. 2, 2026

Sept. 2, 2026

Dear All, We invite you to submit your work to "Discover Mental Health" journal: Computational and Theoretical Approaches to Multi-Scale Dynamics from Cells to Behavior https://link.springer.com/collections/iidiiijebb This Collection aims to bring together experimental, computational, and theoretical studies investigating dynamics across biological, cognitive, behavioral, and clinical scales, from cellular processes and neural circuits to whole-brain activity, behavior, and symptom expression. We welcome contributions developing models, analytical frameworks, and data-driven approaches that advance our understanding of multi-scale organization, emergent phenomena, and the transitions between adaptive and maladaptive dynamics from the cellular level to the symptoms level. Particular interest is given to studies exploring how interactions across scales shape the emergence, evolution, and variability of behaviors and symptoms over time. A central goal of this Collection is to advance our understanding of mental health through a multi-scale perspective. We particularly encourage work examining how biological and neural dynamics give rise to symptom trajectories and behavioral changes in conditions such as depression, psychosis, anxiety disorders, and neurodevelopmental disorders. We welcome studies addressing clinically relevant outcomes, including relapse, treatment response, disease progression, resilience, and functional impairment. The Collection welcomes contributions spanning both theoretical advances and empirical applications. Investigations spanning from cells and neuronal circuits to symptom networks are particularly encouraged, including studies linking cellular and circuit-level mechanisms to cognition, behavior, and symptom dynamics across multiple temporal and spatial scales. We also welcome research on emergent maladaptive states in psychiatric disorders, examining how critical transitions, network reorganization, instability, resilience, and other dynamical processes contribute to the onset, persistence, and progression of psychiatric symptoms and behavioral dysfunction. We encourage submissions using a wide range of experimental and computational approaches, including multimodal neuroimaging (EEG, fMRI, MEG, etc) integrated with longitudinal symptom measurements, computational models constrained or validated by clinical trial data, digital phenotyping combined with dynamical systems analyses, ecological momentary assessment, wearable sensing, and other longitudinal behavioral datasets. We also welcome methodological papers introducing novel analytical frameworks for characterizing multi-scale dynamics in mental health. While theoretical contributions are strongly encouraged, submitted models should ideally be connected to empirical observations or generate clear, testable predictions regarding brain function, behavior, or mental health outcomes. We particularly encourage work that bridges theoretical neuroscience, complex systems, and computational psychiatry by integrating mathematical modeling with experimental or clinical data. Finally, this Collection seeks studies with translational potential that contribute to precision psychiatry and personalized mental health care. Examples include computational approaches for patient stratification, prediction of treatment response or relapse, optimization of neuromodulation strategies, development of adaptive digital therapeutics, and identification of biomarkers that capture dynamic processes across biological and behavioral scales. Keywords * * Multi-scale dynamics * Computational psychiatry * Dynamical systems * Complex systems * Symptom dynamics * Computational modeling * Theoretical neuroscience * Digital phenotyping * Precision psychiatry * Emergence

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2026 INCTN meeting @ Trieste, Italy - 22-24 Sept - abstract submission deadline approaching
by Eugenio Piasini Sept. 1, 2026

Sept. 1, 2026

Dear all, This is a reminder that the abstract submission deadline is approaching for the 2026 meeting of the Italian Network for Computational and Theoretical Neuroscience, which will take place from September 22-24th in Trieste. Submit your abstract by July 10th! We look forward to a great programme with invited and contributed talks on Computational, Theoretical, and Systems Neuroscience, led by keynotes from Máté Lengyel, Sandro Romani, and Fanny Cazettes. We will also have a number of contributed talks and poster sessions to give everybody an opportunity to share their research; and finally, there will be ample time for discussions by the sea side. Please visit our website to see the full lineup of invited speakers and for more information: https://inctn.it/ or register directly here<https://indico.sissa.it/event/190/>. We look forward to seeing you all in Trieste ! The organisers: Francesca Mastrogiuseppe, Eugenio Piasini, and Sebastian Goldt

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Algonauts Project 2027 Challenge
by Alessandro Gifford Aug. 31, 2026

Aug. 31, 2026

Dear colleagues, We are excited to announce the Algonauts Project Challenge 2027 <https://algonautsproject.com/2027/index.html>, organized in collaboration with CNeuroMod <https://www.cneuromod.ca/>: How The Human Brain Makes Sense of Video Games. The goal of this year’s challenge is to predict human brain responses measured with fMRI during a variety of video games. Moving beyond passive stimulus viewing, the challenge brings together perception, decision-making, behavior, and learning, pushing brain modeling toward the complex and dynamic environments in which human cognition naturally unfolds. The challenge will launch at the end of 2026 and run until summer 2027. The top three teams will be invited to present their work at the Algonauts Challenge showcase at CCN 2027 <https://2027.ccneuro.org/> in Edinburgh. More details about the challenge will follow over the coming months. To make sure you do not miss any updates, sign up here <https://algonautsproject.com/2027/index.html#signup>. Website: https://algonautsproject.com/2027/index.html Email: algonauts.mit(a)gmail.com Bluesky: @algonautsproject.bsky.social <https://bsky.app/profile/algonautsproject.bsky.social>X: @AlgonautsProj <https://x.com/AlgonautsProj> We look forward to your participation in the challenge! Best, The Algonauts Project Team Domenic Bersch, Goethe University Frankfurt Alessandro Gifford, Freie Universität Berlin Marie St-Laurent, CRIUGM Basile Pinsard, CRIUGM Yann Harel, Boston College Julie Boyle, Université de Montréal Lune Bellec, Université de Montréal Aude Oliva, Massachusetts Institute of Technology Gemma Roig, Goethe University Frankfurt Radoslaw Cichy, Freie Universität Berlin

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Last Seats Available! International Artificial Intelligence Summer School – IAISS 2026
by ICAS Organizing Committee Aug. 30, 2026

Aug. 30, 2026

Email not displaying correctly? *View it* in your browser. [image: IAISS 2026] <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVojse…> Call for Participation <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVoudv…> International Artificial Intelligence Summer School -IAISS 2026 <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVoizV…> , *Registration: by August 23* <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVoudv…> Register Now <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVoudv…> 5 Days. World-Class Experts. Tuscany. 🧠 A Full-Immersion Experience in Frontier AI Join us for an unforgettable week of cutting-edge lectures on AI and Generative AI, delivered by some of the most renowned researchers in the field — set against the stunning backdrop of the Tuscan coast. 📍 *Riva del Sole Resort & SPA*, Castiglione della Pescaia, Tuscany, Italy 🗓 *September 20–24, 2026* 🔗 2026.iaiss.cc <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVoizV…> ✉️ iaiss(a)icas.cc 🎤 Meet Your Lecturers An extraordinary faculty from leading institutions across the globe — each delivering up to four lectures on the frontiers of AI research: *Stefano V. Albrecht* — Nanyang Technological University, Singapore - Introduction to Multi-Agent Reinforcement Learning - If Multi-Agent Foundation Models is the Answer, What is the Question? - Becoming an AI Researcher: Practical Advice for Graduate Students *Rafal Bogacz* — University of Oxford, UK - Predictive coding: training neural networks with local rules - Predictive coding: advantages over backpropagation - Predictive coding: implementation *Giuseppe De Giacomo* — University of Oxford, UK - Foundations of Guardrailing Agentic AI via Temporal Synthesis (3-part course) *Christoph Feichtenhofer* — Meta Superintelligence Labs, USA - On the impact of data for vision-language learning (parts 1–2) - Building frontier visual segmentation models *Sven Giesselbach* — T-Systems International, Germany - Agentic AI (parts 1–3) *Jamie Hayes* — Google DeepMind, UK - Agentic Security: how to attack and defend against prompt injection (2 parts) *Sumi Helal* — University of Bologna, Italy - Two lectures — titles to be announced *Albert Q. Jiang* — Mistral AI, Paris & University of Cambridge, UK - Machines That Prove: Foundations of AI for Formal Methods and Mathematics - Machines That Reason: Foundation Models and the State of the Art in AI for Mathematics - Machines That Discover: The Future of Automated Mathematics *Marine Le Morvan* — INRIA Saclay, France - The rise of Tabular Foundation Models - TabICL: an open Tabular Foundation Model - Next frontiers for TFMs *Bruno Lepri* — FBK, Italy - Three lectures — titles to be announced *Sebastian Risi* — Sakana AI, Japan & IT University of Copenhagen, Denmark - Three lectures — titles to be announced *George Paliouras* — NCSR "Demokritos", Athens, Greece - Complex Event Recognition/Forecasting and Applications - Large-Scale Probabilistic Complex Event Recognition/Forecasting - Neuro-Symbolic Reasoning and Learning for Complex Event Recognition/Forecasting *Panos Pardalos* — University of Florida, USA - Impact of AI and Optimization on the economics of sustainability 👉 Explore the full lecturer bios <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVopUC…> 👉 Browse the lecture program <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVopUC…> 🏆 Present Your Own Research Want to share your work with a world-class audience? Submit a *research abstract* (max 2 pages, any format) during registration. Our scientific committee will select contributions for *poster presentations* and/or *short talks* — plus a chance to compete for the *IAISS Norbert Wiener Best Presentation Award in Artificial Intelligence*. ⏰ Abstract deadline: *September 6* 🔗 See the Best Presentation Award <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVojsD…> ✅ Why Attend? - *36–40 hours* of intensive lectures from top-tier researchers - Earn *8 ECTS points* (PhD students and highly motivated Master's/BSc students) - Network with peers in a *convivial, professional, and inspiring* setting - A rare opportunity to learn directly from — and mingle with — the people shaping the future of AI *Who should attend:* PhD students, PostDocs, junior academics (up to Assistant Professor level), industry practitioners, and exceptionally motivated Master's/BSc students. *Language:* English 🏨 The Venue *Riva del Sole Resort & SPA* Località Riva del Sole, Castiglione della Pescaia (Grosseto), 58043, Tuscany, Italy 📞 +39 0564 928111 <+39%200564%20928111> | ✉️ booking.events(a)rivadelsole.it 🔗 rivadelsole.it <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVop62…> IAISS is a *fully residential* school — all participants and lecturers stay together at the same resort, creating a truly immersive, community-driven learning experience. No exceptions. *To join us, simply:* 1. *Register* for the school 2. *Book your stay* at Riva del Sole Resort & SPA using the IAISS discounted rates (accommodation form provided at registration) 3. Send your *booking confirmation number* to iaiss(a)icas.cc *Sharing an apartment?* Send the Hotel your co-guest's name, surname, and email — otherwise, book a single-use apartment. IAISS is proudly organized as a *non-profit scientific event*. 🚀 Seats Are Limited — Register Now! 👉 *Register here* <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVoudv…> 📚 Past editions <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVonnw…> | ❓ FAQ <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVol3n…> | 📰 Latest news <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVovGs…> | 💼 LinkedIn group <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVohC1…> *See you this September in Riva del Sole!* — The IAISS 2026 Organizing Committee 🔗 2026.iaiss.cc <https://u9436285.ct.sendgrid.net/ls/click?upn=u001.dsBJlyaSCnb5nD32aHyVoizV…> | ✉️ iaiss(a)icas.cc

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GeMAIHc 2027: early registration September 18
by David Silva - IRDTA Aug. 29, 2026

Aug. 29, 2026

******************************************************** 1st INTERNATIONAL SCHOOL ON GENERATIVE & MULTIMODAL AI FOR HEALTHCARE GeMAIHc 2027 Milan, Italy February 1-5, 2027 https://gemaihc.irdta.eu/2027/ ******************************************************** Co-organized by: Human Technopole IRDTA – Institute for Research Development, Training and Advice ****************************************************** Early registration: September 18, 2026 ****************************************************** SCOPE AI is rapidly redefining biomedical research, clinical decision-making, and healthcare delivery worldwide. GeMAIHc 2027 will provide participants with a comprehensive overview of state-of-the-art AI methodologies. Topics will include generative modelling, multimodal data integration and augmentation, large language models and clinical NLP, medical image synthesis and analysis, as well as evaluation, robustness, validation, ethical considerations, and regulatory aspects of AI systems in healthcare. GeMAIHc 2027 aims to become a leading international forum at the intersection of generative AI, multimodal learning, and healthcare innovation. The program will emphasize both methodological foundations and real-world clinical applications, combining theoretical insights with practical perspectives. This interdisciplinary event will feature 18 monographic three-hour courses, 2 keynote lectures, 3 scientific sessions, 1 symposium, and a hackathon. Leading academics and industry pioneers will share their expertise and perspectives with attendees. In-person interaction and networking will be central components of the event, while full remote participation will also be possible. ADDRESSED TO The program is open to PhD students and postdoctoral researchers in AI, data science, and biomedical disciplines, clinicians and healthcare professionals, industry practitioners and innovators, and policymakers and stakeholders in digital health. There are no formal academic prerequisites for participation. Researchers and professionals at all career stages are welcome. An international audience is expected, with backgrounds spanning computer science, medicine, engineering, mathematics, statistics, physics, and the social sciences. GeMAIHc 2027 will offer a unique opportunity to gain in-depth knowledge of a rapidly evolving field, to interact with experts across disciplines, to establish collaborations and expand professional networks, and to explore how AI is reshaping the future of healthcare. VENUE GeMAIHc 2027 will take place in Milan, one of Europe’s leading international centers for science, industry, fashion, and finance. The venue will be: Human Technopole Viale Rita Levi-Montalcini, 1 20157 Milan, Italy https://humantechnopole.it/en/ STRUCTURE Three parallel courses will run throughout the event. Participants will be free to choose the sessions they wish to attend and may move between courses at any time. A symposium will offer participants and companies the opportunity to present ongoing research or industrial developments through 10-minute oral presentations. The school will include a hackathon, during which participants will work in teams to tackle challenges in generative and multimodal AI for healthcare. 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, the organizers emphasize the importance of in-person interaction and networking in research training events of this kind. KEYNOTE SPEAKERS Deborah Estrin (Cornell University), Transforming Longitudinal Care with Digital Biomarkers and Therapeutics Lyle Palmer (Adelaide University), Deep Learning in Medicine: Some Lessons from Epidemiology and Genomics PROFESSORS AND COURSES Pierre Baldi (University of California Irvine), [introductory/advanced] The AI-driven Healthcare of the Future David Buckeridge (McGill University), [intermediate] Multi-Modal Data Analysis in Population and Public Health Alejandro Frangi (University of Manchester), [intermediate/advanced] Virtual Patient Populations for In Silico Trials Using Generative AI Based on Multimodal Real-World Data Charles Friedman (University of Michigan), [introductory] Synergizing AI and Learning Health Systems to Transform Health Judy Wawira Gichoya (Emory University), [introductory/advanced] Combination in a Hands on Lab for Harmonizing Radiology Datasets Maryellen Giger (University of Chicago), [introductory/intermediate] Role of Data & Algorithms in Trustworthy Medical Imaging AI Casey Greene (University of Colorado), [introductory/advanced] Translating Generative AI into Healthcare from Pharmacogenomics to Foundation Models Tina Hernandez-Boussard (Stanford University), [intermediate/advanced] The AI Lifecycle in Healthcare: Evaluation, Deployment, and Responsible Implementation Jianying Hu (IBM Thomas J. Watson Research Center), [intermediate/advanced] Advanced Computing for Biomedical Research and Discovery Jayashree Kalpathy-Cramer (University of Colorado), [introductory] Toward Digital Twins: Multimodal AI for Imaging and Precision Medicine Alex John London (Carnegie Mellon University), [intermediate/advanced] Ethical and Scientific Challenges to Unlocking the Clinical Value of Artificial Intelligence Asoke Nandi (Brunel University of London), [introductory/advanced] Selected Case Studies of Medical Image Segmentation Tom Pollard (Massachusetts Institute of Technology), [introductory/intermediate] Data: The Foundation, Constraint, and Failure Mode of Deployable Health AI Hoifung Poon (Recursion), [advanced] Toward Virtual Patient: AI for Accelerating Medical Discovery Jian Tang (Mila-Québec AI Institute), [introductory/advanced] Generative AI for Protein Design Peter van Ooijen (University of Groningen), [intermediate] Multimodal AI for Adaptive Radiotherapy: Tumor Segmentation, Uncertainty, and Explainability Karin Verspoor (Royal Melbourne Institute of Technology), [introductory/intermediate] AI Scientists and beyond: Roles for GenAI in Biomedical Research and Discovery Jelmer M. Wolterink (University of Twente), [intermediate/advanced] Data Representations in Health Digital Twinning: From Features to Foundation Models HT RESEARCH PERSPECTIVES Human Technopole will organize 3 scientific sessions: Probabilistic Models for (Medical) Image Analysis, by Jan Funke, Florian Jug, Federico Carrara, and Benjamin Salmon AI Models for Computational Biology, by Andrea Sottoriva, Michele Calabrò, and Manuel Dileo AI in Health Data Science, by Francesca Ieva, Andrea Ganna, Michela Carlotta Massi, Nicole Fontana, and Alessia Mapelli SYMPOSIUM A symposium will feature voluntary 10-minute oral presentations on ongoing research projects and industrial developments. Participants interested in presenting should submit a one-page abstract including title, authors, and summary to david(a)irdta.eu by January 8, 2027. HACKATHON Hands-on team activities will be organized around challenges in generative and multimodal AI for healthcare. The challenges will be released two weeks before the beginning of the school. A jury will evaluate the submissions, and the winners will be announced at the end of February 2027. Winning teams will receive a modest monetary prize, while runners-up will receive certificates of recognition. ORGANIZING COMMITTEE Jan Funke (Milan) Ilaria Guerini (Milan) Francesca Ieva (Milan) Carlos Martín-Vide (Tarragona, program chair) Michela Carlotta Massi (Milan, local chair) Santiago Montes (Tarragona, webpage) Sara Morales (Luxembourg, finances) David Silva (London, organization chair) REGISTRATION Registration is available at: https://gemaihc.irdta.eu/2027/registration/ The selection of six courses requested during registration is tentative and non-binding. This information will help estimate demand for logistical planning purposes. As venue capacity is limited, registrations will be processed on a first-come, first-served basis. Registration will close once capacity has been reached. Early registration is strongly recommended. FEES Registration fees include access to all school activities and lunches. Several early registration deadlines are available, and fees vary depending on the registration period. Fees are identical for on-site and online participation. ACCOMMODATION Accommodation suggestions will be provided in due time at: https://gemaihc.irdta.eu/2027/accommodation/ CERTIFICATE Participants will receive a certificate indicating 40 hours of academic activities. This certificate should be suitable for participants seeking ECTS recognition from their home institutions. SPONSORS Companies, institutions, and organizations interested in sponsoring the event may download the sponsorship leaflet from: https://gemaihc.irdta.eu/2027/sponsors/ QUESTIONS AND FURTHER INFORMATION david(a)irdta.eu ACKNOWLEDGMENTS Human Technopole Universitat Rovira i Virgili IRDTA – Institute for Research Development, Training and Advice

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The NIH BRAIN Theories, Models and Methods Program Application Information
by Mollick, Jessica (NIH/NIDA) [E] Aug. 28, 2026

Aug. 28, 2026

The BRAIN Theories, Models and Methods (TMM) program<https://grants.nih.gov/grants/guide/rfa-files/RFA-DA-27-004.html> (RFA DA 27 004) supports the development and validation of innovative and rigorous theories, models and methods to advance the quantitative and predictive understanding of brain function across scales, including behavior. The program emphasizes tools that develop novel approaches for analyzing, integrating, and interpreting large-scale, complex data emerging from the BRAIN initiative and related efforts, including cell-type specific physiological, anatomical, connectivity, and behavioral data. Applications should focus on one or more of the following: * new or significantly advanced theories of brain function * mechanistic and/or predictive models of neural circuit activity and behavior grounded in empirical data * novel computational or statistical methods for analyzing neural and behavioral datasets.  Tools for analyzing brain activity must: * use data with cellular and sub-second temporal resolution (e.g., single-unit recordings, cellular imaging, connectomics) OR integrate information across multiple, clearly defined temporal scales (e.g., from synaptic events to learning).  * Approaches relying solely on non-invasive, low-resolution signals (e.g., scalp EEG, fMRI BOLD) must be directly integrated with and constrained by cellular/circuit-level data. * Tools for analyzing behavior  must incorporate neural data AND span multiple relevant temporal scales. * Experimental work must be limited to estimating model parameters and/or testing the validity of the TMM tools being delivered.  Theories, models and methods using disease or treatment paradigms are not responsive unless used to understand underlying functional and brain circuits. Important Deadlines: * New submissions: October 6. 2026 * Resubmission/Renewal applications: November 6, 2026 Please send specific aims pages and inquiries to: BRAINTheoriesFOA(a)ninds.nih.gov.<mailto:BRAINTheoriesFOA@ninds.nih.gov> We are happy to consult on fit with the program.

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PhD and Postdoc positions [Neuro-AI lab @ Technion] - Stefano Recanatesi
by Stefano Recanatesi Aug. 28, 2026

Aug. 28, 2026

*PhD and PostDoc Positions Available: Neuro-AI Lab at Technion* *About Us: *Our projects range from developing Brain-Computer Interfaces (BCIs) for both rodents and humans to creating theoretical and computational models of neural activity, and training cutting-edge machine-learning models, including large language models (LLMs). *University Environment: *The Technion offers a world-class research environment with state-of-the-art facilities and a strong international community. The lab is embedded within the Technion’s AI and neuroscience communities and maintains active collaborations with research groups abroad. We strongly encourage international mobility, supporting students in undertaking research visits, internships, and collaborative projects at partner institutions. In light of the current political situation, international students are particularly encouraged to take advantage of these collaborations, including opportunities to spend extended periods working in partner laboratories abroad. *Lab Homepage:* Technion Neuro-AI Lab <https://technionneuroailab.com> *Project Descriptions & Candidate Profiles:* We are seeking candidates with computational/theoretical or experimental expertise in the following areas: - *Computational Projects:* - Focus: Machine learning, artificial intelligence, and training of various network algorithms. - Relevant Backgrounds: Computer Science, Electrical Engineering, Data Science, etc. - *Theoretical Projects:* - Focus: Developing theoretical and computational predictions for neural experiments. - Relevant Backgrounds: Physics, Mathematics, Applied Mathematics, Computer Science, etc. - *Experimental Collaborations:* - Focus: Developing experimental setups with advanced computational tools for BCIs in collaboration with partner labs. - Relevant Backgrounds: Neuroscience, Biology, Medicine, etc., with strong computational skills. *What We Offer:* - A stimulating and supportive research environment. - Access to state-of-the-art equipment and infrastructure. - Opportunities for interdisciplinary scientific development. - An international and collaborative team atmosphere. - Comprehensive training in a wide range of scientific skills. - Opportunities to present your research at international conferences and workshops. - Extensive support for career development beyond your Ph.D. *Application Deadline: *We encourage candidates to apply as soon as possible. Our goal is to fill positions by October 2026. *How to Apply:* Please send your CV and full academic transcript directly to Prof. Stefano Recanatesi (stefano(a)technion.ac.il)

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Postdoctoral Fellow positions available to study spinal mechanisms of motor control
by Levine, Ariel (NIH/NINDS) [E] Aug. 28, 2026

Aug. 28, 2026

Hello Comp-Neuro Community, We have two Postdoctoral Fellow positions available in the lab, where we study how spinal neurons mediate motor control in mice. Next week, our lab will move from NIH to the Krembil Brain Institute at the University Health Network of the University of Toronto. Lab Description We focus on the spinal cord as the final point of neural control over body movement. The spinal cord contains the motoneurons that drive our muscles, the immediate premotor neurons that are the primary regulators of motoneuron activity, and the broader, as-yet-undefined networks of spinal neurons that transform sensory and descending cues into purposeful behavior. We have built extensive atlases of spinal cord cell types and we now want to understand how they act cooperatively to orchestrate movement. Position 1 We are seeking a postdoctoral fellow to investigate whether, and how, cell types shape population activity and mediate specific elements of sensorimotor function. This work will bring together several powerful approaches recently developed and adapted in our lab including in vivo high density electrical recordings from the spinal cords of awake behaving mice, closed-loop optogenetics, spinal cell-type specific manipulation, quantitative behavioral tracking, and computational analysis of neural activity and behavior data (which could involve co-mentorship with an outside collaborator). There is significant opportunity to co-design and lead projects. Position 2 We are seeking a postdoctoral fellow to investigate how specific spinal cord cell types and sensory elements contribute to behavior in mice. This work will also test the links between cell type identify, connectivity, and function by bringing together several powerful approaches including circuit tracing, cell-type specific manipulation, closed-loop optogenetics, and quantitative behavioral tracking. There is significant opportunity to co-design and lead projects. Duties * Development of all stages of research projects) in collaboration with Dr. Levine, members of the laboratory, and outside collaborators * Experimental design, wet-lab procedures, and data analysis * Advise and mentor of students and serve as an active member of laboratory intellectual life * Write and contribute to grant applications * Present research through original research publications, reviews, and talks at scientific conferences Qualifications * Doctoral degree (PhD) must be obtained within the previous 5 years from a recognized * A strong publication record (including pre-prints) * Expertise in one or more of the following areas * Position 1: high density electrophysiology, computational neuroscience, neural circuit tracing and analysis, mouse surgery, and quantitative assessment of sensorimotor behavior * Position 2: viral and anatomical circuit tracing, optogenetics, mouse genetics, mouse surgery, quantitative kinematic analysis, electromyography, and statistical/computational data Applications can be submitted through the UHN SmartRecruiters portal (Position 1<https://jobs.smartrecruiters.com/UniversityHealthNetwork/744000144149159-po…> and 2<https://jobs.smartrecruiters.com/UniversityHealthNetwork/744000144814376-po…>) or through the lab website<http://www.levine-lab.org/>. Thank you for sharing with your students and colleagues. Sincerely, Ariel Ariel Levine, MD, PhD Senior Scientist Peter Gilgan Chair in Neuroregeneration Research Krembil Brain Institute University Health Network University of Toronto www.levine-lab.org<http://www.levine-lab.org>

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Funded PhD Position in NeuroAI and Computational Neuroimaging – University of Rome Tor Vergata
by nicola toschi Aug. 27, 2026

Aug. 27, 2026

Dear Comp-Neuro community, We are recruiting for a three-year funded PhD position in our research group at the University of Rome “Tor Vergata”, within the Italian National PhD Programme in Artificial Intelligence – Health and Life Sciences. We are looking for a highly motivated candidate with a strong quantitative background who is interested in developing advanced AI and computational methods for studying the brain and human health. Depending on the candidate’s interests and expertise, the research may involve one or more of the following areas: * NeuroAI and computational modelling of brain activity * neural foundation models and generative AI * graph machine learning and dynamic brain networks * multimodal neuroimaging, including MRI, PET and CT * EEG, MEG and intracranial electrophysiology * neural decoding and encoding * multimodal representation learning * quantitative biomarkers and personalised prediction * neuromodulation, focused ultrasound and neurotechnology * causal, physical and mathematical modelling of biological systems We particularly welcome candidates with backgrounds in computer science, engineering, physics, mathematics, data science or closely related quantitative disciplines. Strong Python and machine-learning experience is highly valued. Previous work with neuroimaging, electrophysiological signals, graph-based methods, deep learning or modern foundation models would be advantageous. The successful candidate will join an interdisciplinary and international research environment with access to advanced datasets and technologies, as well as collaborations with academic, clinical and industrial partners. Interested candidates should contact us as soon as possible by sending: * an updated CV * a brief letter describing their background and research interests to nicola.toschi(a)uniroma2.eu<mailto:nicola.toschi@uniroma2.eu>, using the subject line: “PhD Expression of Interest – AI 2026” Please note that this preliminary contact does not replace the formal application. Candidates must also apply through the official portal by 7 September 2026 at 12:00 CET. Official call: https://www.unicampus.it/bando/bando-dottorato-di-ricerca-in-intelligenza-a… Application portal: https://pica.cineca.it/unicampus/2026-2027-phd-ai3-it-isessione Host institution: University of Rome “Tor Vergata”, Rome, Italy Duration: three years Application deadline: 7 September 2026, 12:00 CET Remote interview: 23 September 2026 Please feel free to circulate this announcement among potentially interested candidates. Best regards, Nicola Toschi Prof. Nicola Toschi Scholar Profile<https://scholar.google.com/citations?hl=en&user=kyI6AJ8AAAAJ&view_op=list_w…> | Lab Website<https://fismed.uniroma2.it/> | Bookable Time<https://calendar.app.google/vXmx4XiWRvkf23XQ7> | LinkedIn<https://www.linkedin.com/in/nicola-toschi-5680923/> Full Professor of Medical Physics Medical Physics Section - Department of Biomedicine and Prevention University of Rome "Tor Vergata" Via Montpellier 1 - 00133 Rome (IT) Email: toschi(a)med.uniroma2.it<mailto:toschi@med.uniroma2.it> Research Staff, Investigator A.A. Martinos Center for Biomedical Imaging - Harvard Medical School/MGH 149 13th street, 02129 Boston (MA), USA Email: nicola(a)nmr.mgh.harvard.edu<mailto:nicola@nmr.mgh.harvard.edu>

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Academic positions in Artificial Intelligence at the University of Surrey
by roman bauer Aug. 27, 2026

Aug. 27, 2026

Dear all, We are pleased to announce three open academic positions in Artificial Intelligence at the University of Surrey, UK: Professor in Artificial Intelligence (NICE Research Group within the Computer Science Research Centre) https://jobs.surrey.ac.uk/Vacancy.aspx?ref=037526 Senior Lecturer in Artificial Intelligence (NICE Research Group within the Computer Science Research Centre) https://jobs.surrey.ac.uk/Vacancy.aspx?ref=037426 Professor in Artificial Intelligence (Centre for Vision, Speech and Signal Processing) https://jobs.surrey.ac.uk/Vacancy.aspx?ref=037626 Closing date: Sunday 13 September 2026 The School of Computer Science and Electronic Engineering is seeking to recruit internationally recognised researchers to strengthen its research and teaching in Artificial Intelligence. These appointments form part of a wider recruitment campaign and strategic investment across the Faculty: https://www.jobs.ac.uk/enhanced/linking/university-of-surrey-engineering-ph… The Professor and Senior Lecturer positions in Computer Science cover areas including Large Machine Learning Models, Neurosymbolic AI, Trustworthy Machine Learning, Natural Language Processing, and applications of AI and machine learning in automated reasoning, security, and software and systems development. Both posts are aligned with the Nature Inspired Computing and Engineering (NICE) Research Group within the Computer Science Research Centre. The Professor position within the Centre for Vision, Speech and Signal Processing focuses on leading growth in frontier AI, including multimodal foundation models, machine learning, agentic, people-centred and sustainable AI, with applications spanning human and animal health, biosciences, creative industries, sustainability, robotics and autonomous systems. The School is home to two established research centres with substantial expertise in AI and machine learning: the Computer Science Research Centre and the Centre for Vision, Speech and Signal Processing. Surrey has an established international reputation in AI research, ranking first in the UK for computer vision and among the top five for AI, computer vision, machine learning, robotics and natural language processing according to CSRankings.org. The School was also ranked seventh in the UK for Computer Science research outputs in REF2021. Computer Science and CVSSP are central to the Surrey Institute for People-Centred AI, a pan-University initiative bringing together AI research and expertise across health, engineering, social and behavioural sciences, business, law and the creative arts. The Institute leads a portfolio of more than £100 million in grant awards, including major activities in healthcare and the creative industries, and two doctoral training programmes supporting more than 100 PhD researchers. Informal enquiries concerning the Computer Science positions may be directed to Professor Brijesh Dongol at b.dongol(a)surrey.ac.uk. Enquiries concerning the CVSSP position may be directed to Professor Adrian Hilton at a.hilton(a)surrey.ac.uk. Our staff and students come from around the world, and we are proud of our friendly and inclusive culture. The University is committed to building a diverse community, and applications from under-represented groups are particularly encouraged. Please share these opportunities with potentially interested candidates and across your networks. Best regards, Roman *Roman Bauer, Ph.D.* Senior Lecturer | Head of the NICE Research Group BioDynaMo Spokesperson (www.biodynamo.org) *A software suite to enable simulations of large, complex systems for research or policy making* *Computer Science Research Centre* University of Surrey | Guildford, UK r.bauer(a)surrey.ac.uk | ORCID <https://orcid.org/0000-0002-7268-9359> | LinkedIn <https://www.linkedin.com/in/roman-bauer-05176094/> * Watch the **BioDynaMo introduction video* <https://youtu.be/N6Kzc_AadyI?si=zHymOvrlR3wzAbCf>

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Postdoc Positions in Cognitive and Computational Neuroscience at Washington University in St. Louis
by Runnan Cao Aug. 26, 2026

Aug. 26, 2026

The Multimodal Cognitive Neuroscience Laboratory, led by Dr. Runnan Cao at Washington University School of Medicine in St. Louis, invites applications for postdoctoral research associate positions. Our laboratory investigates the neural computations and network-level dynamics underlying visual perception and social cognition in neurotypical individuals and people with neurodevelopmental or psychiatric conditions, including autism and schizophrenia. We combine human intracranial electrophysiology, including iEEG and single-neuron recordings, with high-resolution fMRI, behavioral experiments, and computational modeling to determine how the brain transforms visual input into representations that support social perception and behavior. These positions offer a distinctive opportunity to join a new laboratory at a formative stage. The successful candidates will help shape its scientific direction, analytical infrastructure, collaborative culture, and multimodal research program. Research Projects will be tailored to each postdoctoral researcher’s expertise, interests, and career goals. Potential research areas include: Neural coding of faces and socially relevant visual information Neurocomputational mechanisms underlying visual perception and social cognition Neural coding and network-level dynamics associated with autism and schizophrenia Multimodal integration of iEEG, single-neuron recordings, high-resolution fMRI, and behavioral data Computational models linking neural activity to perception and behavior AI-enabled methods for analyzing complex multimodal neuroscience data Required Qualifications Applicants must have: A PhD or equivalent doctoral degree in neuroscience, cognitive science, psychology, biomedical engineering, computer science, or a related discipline by the appointment start date A strong research background in fMRI and/or electrophysiology Experience analyzing neuroimaging, neural, behavioral, or computational data Proficiency in scientific programming, particularly Python and/or MATLAB Evidence of research productivity appropriate to career stage Strong written and oral communication skills The ability to work both independently and collaboratively in an interdisciplinary environment Preferred Qualifications Experience in one or more of the following areas is desirable: Acquisition or analysis of 7T fMRI data Human intracranial EEG, ECoG, depth-electrode, or single-neuron recordings Advanced statistical methods, neural signal processing, or network neuroscience Machine learning or deep learning applied to neural and behavioral data Multimodal integration of neuroimaging, electrophysiological, and behavioral data Agentic AI or AI-assisted scientific workflows Development of reproducible data-processing pipelines, workflow systems, or reusable computational tools Candidates who have deep expertise in one methodological area and are eager to develop complementary skills are strongly encouraged to apply. Mentoring and Professional Development Each postdoctoral researcher will work with Dr. Cao to develop an individualized research and career-development plan. Training may include advanced fMRI and electrophysiological analysis, computational modeling, machine learning, scientific writing, grant preparation, project leadership, mentoring, and the development of reproducible research tools. Postdoctoral researchers will be encouraged to establish a clear area of scientific ownership, pursue external funding, build an independent scholarly profile, and develop the skills needed for their chosen career path. Why Join Our Laboratory? Postdoctoral researchers will have the opportunity to: Work with distinctive human intracranial and single-neuron datasets Develop expertise across complementary spatial and temporal scales of brain measurement Help establish the methods, workflows, and scientific culture of a growing laboratory Receive individualized mentoring in research strategy, scientific writing, grant development, and career planning Build collaborations spanning cognitive, computational, clinical, and systems neuroscience Pursue independent fellowships and develop a path toward scientific independence Present their work at national and international scientific meetings The laboratory is committed to rigorous and open science, intellectual curiosity, constructive collaboration, and an environment in which researchers with different backgrounds and methodological strengths can thrive. Why WashU and the Neuroimaging Labs? The laboratory is based in the Neuroimaging Labs Research Center <https://www.mir.wustl.edu/research/research-centers/neuroimaging-labs-resea…> at WashU Medicine’s Mallinckrodt Institute of Radiology. The NIL-RC brings together investigators, postdoctoral researchers, students, clinicians, engineers, and research staff from Radiology, Neurology, Psychiatry, and other departments. The center has a longstanding record of innovation in neuroimaging methods and has supported major scientific initiatives, including the Human Connectome Project and the Alzheimer’s Disease Research Center. Its research spans human cognition, functional connectivity, precision neuroimaging, brain development and aging, psychiatric and neurological disorders, brain parcellation, and imaging methodology. The WashU neuroimaging environment includes: A dedicated research MRI facility <https://www.mir.wustl.edu/research/core-resources/mri-facility/> with three Siemens PRISMA 3T scanners and experienced research imaging personnel A Siemens MAGNETOM Terra.X 7T MRI system <https://www.mir.wustl.edu/magazine/magnified-medicine-7t-comes-to-mir/> supporting ultra-high-resolution structural and functional imaging Internationally recognized expertise in functional connectivity, precision neuroimaging, brain mapping, neuroinformatics, and multimodal imaging Strong connections with Psychiatry, Neurology, Neurosurgery, Neuroscience, Psychological & Brain Sciences, Biomedical Engineering, and Computer Science Opportunities for clinical and translational collaboration in autism, schizophrenia, epilepsy, Alzheimer’s disease, and other neurological and psychiatric conditions A broad seminar, training, and professional-development community across WashU Medicine and the university This environment is especially well suited to researchers who want to connect fine-grained neural recordings with whole-brain imaging, behavior, and computational theory. How to Apply Applicants should email the following materials to Dr. Runnan Cao at r.cao(a)wustl.edu <mailto:r.cao@wustl.edu>: A cover letter describing the applicant’s research experience, methodological expertise, scientific interests, career goals, and potential fit with the laboratory A current curriculum vitae Contact information for two professional references; letters are not required with the initial application Please use the subject line: Postdoctoral Application – [Applicant Name].

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Call for Papers: Novel Insights and Approaches in Time-frequency Analysis
by alireza valizadeh Aug. 26, 2026

Aug. 26, 2026

Dear colleagues, I am writing to share a Call for Papers for a new *Nature Collection in Communications Psychology*, *“Novel Insights and Approaches in Time-frequency Analysis,”* which is now open for submissions: https://www.nature.com/collections/ejbgajabei The Collection brings together new methodological and empirical advances in time-frequency analysis, with broad relevance to neuroscience and related fields. We would particularly welcome work introducing novel approaches, methods, or insights into the analysis and interpretation of time-varying neural signals. The Collection is co-edited by *Gabriele Gratton (University of Illinois Urbana-Champaign)* and *Alireza Valizadeh (IASBS)*. If you have research that may be a good fit, we would be very happy to consider your submission. Please see the Collection page for further details on the scope and submission process. Best wishes, Alireza Valizadeh and Gabriele Gratton ------------------------------------------------------Alireza Valizadeh*Professor * Theoretical Neuroscience lab, Institute for Advanced Studies in Basic Sciences (IASBS), Iran *Principal Investigator* Zapata-Briceño Institute of Neuroscience and Human Intelligence, Spain Tel: (+34) 603325584 valizadeh(a)gmail.com valizadeh(a)institutobz.org <valizadeh(a)humanismoyciencis.org> Web: https://www.institutobz.org/ <https://fundacionhumanismoyciencia.org/instituto-zapata-briceno/> http://www.iasbs.ac.ir/~valizade/index.html --------------------------------------------------------

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2 PhD positions for 4 years with focus on "Generative Episodic Memory" with Prof. Laurenz Wiskott, Germany, Bochum
by Laurenz Wiskott Aug. 25, 2026

Aug. 25, 2026

From https://jobs.ruhr-uni-bochum.de/jobposting/854eabcb1786fa8b53af20c255cd9aea… Faculty of Computer Science : Chair: Theory of Neural Systems In order to fill a fixed-term position in part-time (29.87 hours/week = 75%) at the earliest possible date, we are looking for 2 2 Research associates (m/f/x) for 4 years with focus on "Generative Episodic Memory" The Institute for Neural Computation is a central research institute at the Ruhr-University Bochum, see https://www.ini.rub.de/. It focuses on the dynamics and learning of perception and behavior on a functional level but is otherwise very diverse, ranging from neurophysiology and psychophysics over computational neuroscience to machine learning and technical applications. The research focuses on (i) modeling generative episodic memory in close collaboration with experimental partners, with the goal of modeling experimental data and gaining a deeper understanding of memory processes; (ii) developing a hierarchical model of the visual system that supports a generative memory process. The first project will focus primarily on standard machine learning methods, such as Transformers. The second project aims to develop new methods inspired by the brain. Scope: part-time (75%) Duration: fixed-term, 4 Jahre Start: at the earliest possible date Apply by: 2026-09-14 Your tasks: (i) Further development of an existing system model of generative episodic memory in light of various experimental results. (ii) Development of a brain-inspired hierarchical model of the visual system that supports distributed generative memory processes. Modeling of experimental data. Communication with experimental partners. Publication of results. Teaching assistance equivalent to 3 SWS, in particular conducting a Python course and supervising student/Bachelor/Master projects. Your profile: Requirements: Very good Master degree in mathematics, computer science, engineering, or a related field. Interest in interdisciplinary research in the area of neuroscience. Good programming and mathematical skills. Basic knowledge in machine learning. Advantageous: Experience in modeling. Experience in interdisciplinary projects. Programming skills in Python. We offer: Challenging and varied tasks with a high level of independence Collaboration in a committed and appreciative team Extensive training and professional development opportunities An interesting interdisciplinary environment in the field of theoretical brain research / machine learning. Freedom to shape the project yourself. Infrastructure that facilitates close integration into the institute and the research group. Opportunity to pursue a Ph.D. Further information: The position is salaried and based on the collective agreement of the Länder (TV-L). If the personal and collective agreement requirements are met, the employee will receive pay grade E 13 TV-L. Further information can be found at https://oeffentlicher-dienst.info/ (in German). The place of work is Ruhr University Bochum. The load of teaching will be calculated according to § 3 of Lehrverpflichtungsverordnung (state of North Rhine-Westphalia). Applications (CV, transcript of records for MSc and Bsc, letter of motivation) should be sent as a single pdf file. RUB sees itself as a university with an international presence. The campus languages are German and English. Competence in at least one of the two languages and the willingness to learn the other are a prerequisite. RUB provides corresponding free courses for employees. German language courses are offered by the University Language Center (ZFA) in the field of German as a Foreign Language (DaF). https://www.daf.ruhr-uni-bochum.de/daf/mitarbeitende/index.html.en The Staff Council has the right to participate in all selection interviews. At the request of a candidate (m/f/x), it will ensure its participation in the entire procedure. Please contact wpr(a)rub.de. The Ruhr-Universität Bochum is one of Germany’s leading research universities, addressing the whole range of academic disciplines. A highly dynamic setting enables researchers and students to work across the traditional boundaries of academic subjects and faculties. To create knowledge networks within and beyond the university is Ruhr-Universität Bochum’s declared aim. The Ruhr-Universität Bochum stands for diversity and equal opportunities. For this reason, we favour a working environment composed of heterogeneous teams, and seek to promote the careers of individuals who are underrepresented in our respective professional areas. The Ruhr-Universität Bochum expressly requests job applications from women. In areas in which they are underrepresented they will be given preference in the case of equivalent qualifications with male candidates. Applications from individuals with disabilities are most welcome. Contact persons for further information: Prof. Dr. Laurenz Wiskott Tel.: +49 234 32 27997 Kathleen Schmidt Tel.: +49 234 32 27051 Travel costs, accommodation costs and loss of earnings or other application costs for job interviews can unfortunately not be reimbursed. We look forward to receiving your application via our online application portal at https://jobs.ruhr-uni-bochum.de/en/jobposting/854eabcb1786fa8b53af20c255cd9… by 2026-09-14. Please make sure to mention the reference number ANR 6046.

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