- Comp-neuro - lists.cnsorg.org

Human Neocortical Neurosolver (HNN) Virtual Workshop
by Gao, Joyce May 27, 2026

May 27, 2026

Dear all, We invite you to join us for a free, virtual Human Neocortical Neurosolver (HNN) Workshop in collaboration with Neuroscience Gateway (NSG)! This workshop will take place on June 22nd from 12 - 3 PM (EDT) on Zoom. HNN is a user-friendly software tool for interpreting the cell and circuit level origin of human MEG and EEG signals (Neymotin et al 2020, https://hnn.brown.edu/) We will go over the basics of HNN, simulating and optimizing ERPs. Attendees will also be introduced to NSG resources and learn how to submit batch HNN simulations on NSG. You can find out more about the workshop and register here: https://forms.gle/DAvnwaBbR6qbNjyM9. Seats are limited, so if you are interested, we recommend signing up today! Our best, Jones Computational Neuroscience Lab Brown University, Carney Institute for Brain Science

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Submit to COMPLEX NETWORKS 2026 (📍Granada, Spain) – 🎤 Keynotes Announced & 📚 2025 Proceedings Free!
by Fabian Braesemann May 27, 2026

May 27, 2026

Dear colleagues, 🚀 COMPLEX NETWORKS 2026 will take place in Granada, Spain 📅 Conference: December 2-4, 2026 📝 Submission Deadline: September 2, 2026 We invite you to submit your work and join one of the most vibrant communities in network science and complex systems. ________________________________ 🎓 Keynote Speakers Hear from global leaders pushing the boundaries of network science: * Alexandra Brintrup - University of Cambridge, UK * Nitesh Chawla - University of Notre Dame, USA * From Ships to Molecules: Higher-Order Graph Learning Across Scales<https://complexnetworks.org/keynotes/#talkkeynote2> * Kimmo Kaski - Aalto University, Finland * Bruno Lepri - Bruno Kessler Foundation, Italy * Eckehard Scholl - TU Berlin, Germany * Synchronization Scenarios in Complex Networks: from Brain Dynamics to Power Grids<https://complexnetworks.org/keynotes/#scholl-abstract> “A must-attend conference" ________________________________ 📚 Free Access to COMPLEX NETWORKS 2025 PROCEEDINGS Until May 31, 2026, download: * 📘 Springer Proceedings (Volumes 1–4) * 📖 Book of Abstracts 👉 Access here<https://complexnetworks.org/proceedings/> https://complexnetworks.org/proceedings/ ________________________________ 📢 Call for Submissions ✅ Full Papers (max 12 pages) → Published in the Springer LNCS Proceedings ✅ Extended Abstracts (max 4 pages) → Included in the Book of Abstracts (with ISBN) 🔗 Submit your work: 👉 https://complexnetworks.org/submission/ Templates and guidelines are available on the site. Don’t miss this opportunity to share your work, meet leading researchers, and explore the future of complex networks. We look forward to your submission! Warm regards, The COMPLEX NETWORKS 2026 Organizing Committee 📧 hocine.cherifi(a)gmail.com | 🌐 https://complexnetworks.org<https://complexnetworks.org/> PS: Welcome to join the group of Complex Networks on LinkedIn (https://www.linkedin.com/groups/17872021) and follow us on X/Twitter (@ComplexNetConf)! --- Dr Fabian Braesemann Departmental Research Lecturer in AI & Work Oxford Internet Institute, University of Oxford Publicity Co-Chair International Conference on Complex Networks and their Applications fabian.braesemann(a)oii.ox.ac.uk<mailto:fabian.braesemann@oii.ox.ac.uk> +44 7731 700 704 Departmental website<https://www.oii.ox.ac.uk/people/profiles/fabian-braesemann/> | Google Scholar<https://scholar.google.at/citations?user=L2AXGNwAAAAJ&hl=en> | LinkedIn<https://uk.linkedin.com/in/fabian-braesemann-210645138>

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Call for Applications: MSc Health Data Science at the University of Plymouth
by Vesna Vuksanovic May 27, 2026

May 27, 2026

Dear All * Apologies for cross-posting* We are pleased to invite applications for our MSc Health Data Science programme at Swansea University, UK. Our MSc programme offers a comprehensive curriculum covering key areas including Machine Learning, Health Data Modelling, Visualisation and Linkage. The programme is designed to provide the knowledge, skills and understanding that can be used across various healthcare areas and focuses on developing practical, healthcare-ready skills alongside strong theoretical foundations. Our students benefit from hands-on projects to gain relevant, transferable technical skills and software proficiency for working with and manipulating health data, and to learn how to use and apply advanced statistical and machine learning methods with real-world data. 🔗 Learn more: MSc Health Data Science - Swansea University<https://www.swansea.ac.uk/postgraduate/taught/medicine/health-data-science-…> 📅 Applications are open for both September and January intakes. For further information or specific queries, please feel free to contact me directly. We look forward to welcoming the next generation of health data scientists! Kind regards Vesna Vuksanovic, PhD, FHEA Programme Director, MSc Health Data Science Senior Lecturer Health Data Science _______________________________________________________________________________________________________________________________________________ Swansea University Medical School Data Science Building Swansea SA2 8PP UK

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2026 NEURON summer course registration deadline soon
by McDougal, Robert May 26, 2026

May 26, 2026

A few seats remain open for the 2026 NEURON Summer Course, but the registration deadline is Monday, June 1 — less than a week away -- so you should act now if you want to join us at Duke University in Durham, NC. This course will provide a thorough introduction to computational modeling of neurons and networks with NEURON, and it is suitable for individuals at all levels of expertise. It will start at 9 AM Wednesday, June 10, and end at 5 PM Monday, June 15, 2026. For more information and the on-line application form, see The 2026 NEURON Summer Course: https://github.com/neuronsimulator/nrn/discussions/3729

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What are the functions of primary visual cortex (V1)?
by Li Zhaoping May 26, 2026

May 26, 2026

Dear colleagues, I am pleased to share Zhaoping, L. (2026) What are the functions of primary visual cortex (V1)? <https://authors.elsevier.com/sd/article/S0959438826000450> in Current Opinions of Neurobiology, 98:103209 the emerging answers have additionally helped to ask "What is vision?", see Zhaoping, L. (2026) Vision as looking and seeing through a bottleneck <https://www.sciencedirect.com/science/article/pii/S0959438826000474> in Current Opinions of Neurobiology, 98:103211 both articles and other relevant information in this website <https://www.lizhaoping.org/Selected-Publications.html>, happy to hear your feedback, to provide more information, and to discuss. best, Li Zhaoping -- Li Zhaoping, Ph.D. Prof. of Cognitive Science, University of Tuebingen Head of Department of Sensory and Sensorimotor Systems, Max Planck Institute for Biological Cybernetics Author of "Understanding vision: theory, models, and data", Oxford University Press, 2014 www.lizhaoping.org

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Cambridge Open Lab Open Science in Practice Course, Aug 3-7 2026
by Mateusz Kostecki May 25, 2026

May 25, 2026

Hello! Cambridge node of Open Lab project is announcing a new summer course - Open Science in Practice! The Open Science in Practice Summer School is a 5-day immersive programme held in Cambridge (UK), bringing together students and early-career researchers interested in integrating open science into their daily work. The summer school is designed for students and early-career researchers who want to explore and implement open science practices in their work. While the content is broadly applicable across disciplines, the programme is oriented towards applications in neuroscience, with hands-on workshops that will resonate especially with those working with experimental setups, behaviour tracking, and data analysis. The course is divided in two parts: *Open Science Principles* The first two days focus on the foundations of open science, including why it matters, how it shapes research culture, and how to implement open and reproducible practices, from data sharing to open access publishing *Hands-on workhops* This is an opportunity for participants to gain practical experience in important experimental skills that can be applied to your research, such as: – Basic electronics for building or improving experimental setups (e.g., closed-loop setups systems, sensors and much more!) – 3D design and printing using open-source software (FreeCAD) – Open-source software for behavioural analysis (e.g. DeepLabCut). Please find more info here - https://cambridgeopenlab.org/ With best wishes, Mateusz Kostecki -- --- Mateusz Kostecki Postdoc Jekely Lab Heidelberg University https://twitter.com/mtkostecki https://evolvingbehavior.blog/

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World wide VVTNS series (6th season): Equilibrium Geometry and Chaotic Dynamics in Large Recurrent Neural Networks | Giancarlo La Camera, Stonybrook University| Wednesday, May 27, 2026, at 11:00 am ET
by David Hansel May 24, 2026

May 24, 2026

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the lecture Giancarlo La Camera Stonybrook University on the topic of Equilibrium Geometry and Chaotic Dynamics in Large Recurrent Neural Networks The lecture will be held on Zoom on May 27, 2026 at *11:00 am ET * > To receive the link: https://www.wwtns.online/register-page > *Abstract: *Large recurrent networks are important models in several fields, including neuroscience, machine learning, physics, and applied mathematics. Yet their dynamics are difficult to study directly, because high-dimensional nonlinear systems can exhibit rich behavior that is hard to summarize in terms of individual trajectories. In this talk, I will discuss an approach that seeks to understand such dynamics through the structure of the network’s equilibria. I will focus on a random balanced network of threshold-linear units that undergoes a transition from a single stable equilibrium to extensive chaos as the disorder strength crosses a critical value. Using a combination of Kac–Rice theory, replica calculations, numerical root-finding, and dynamical mean-field theory, we show that the chaotic regime contains an exponentially large number of equilibria. These equilibria are all saddles, but with only a fractionally small number of unstable directions. Surprisingly, despite the completely random connectivity, the equilibria are not scattered randomly through phase space. Instead, they are strongly correlated and confined to a comparatively small region. The chaotic attractor lies within this same region, suggesting a direct geometric link between the organization of unstable equilibria and the collective structure of the dynamics. This picture helps explain why networks with extensive chaos can nevertheless display dynamics dominated by a relatively small number of collective modes. More broadly, the results suggest that the geometry of equilibria provides a useful complementary perspective to dynamical mean-field theory for understanding high-dimensional neural dynamics. *About VVTNS : Launched as the World Wide Theoretical Neuroscience Seminar (WWTNS) in November 2020 and renamed in homage to Carl van Vreeswijk in Memoriam (April 20, 2022), Speakers have the occasion to talk about theoretical aspects of their work which cannot be discussed in a setting where the majority of the audience consists of experimentalists. The seminars, **held on Wednesdays at 11 am ET,** are 45-50 min long followed by a discussion. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.* ᐧ ᐧ

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9th Summer School in Computational Biology — Coimbra, Sept 1–12, 2026
by Renato Duarte May 22, 2026

May 22, 2026

9th Summer School in Computational Biology — from molecules to tissues ===================================================================== Dates: September 1 – 12, 2026 Venue: University of Coimbra, Portugal Website: https://www.uc.pt/events/computationalbiology/ Apply: https://forms.gle/DGehyz1Mbecu5TnT6 Contact: computational.biology(a)uc.pt The Computational Biology network at the University of Coimbra is pleased to announce the 9th edition of the Summer School in Computational Biology. This year with a dedicated Computational Neuroscience day. The school is an intensive introductory course aimed at students from the M.Sc. to postdoctoral levels, with either biological or quantitative-science backgrounds, who wish to acquire skills in computational biology. Applications from B.Sc. students with outstanding records will also be considered. Structure --------- * Introductory lectures, in parallel tracks: - mathematics and physics for biologists - biology for exact-science students * Specialised courses spanning the molecular to the integrated-physiological scales * Seminars on cutting-edge developments by world-leading scientists * Hands-on research projects, applying acquired skills to real problems Topics ------ * Core principles for modelling biological systems * Molecular dynamics of lipid membranes and proteins * Protein–ligand interactions and drug discovery * Data science and AI in biology and biomedicine * Genomics / transcriptomics for characterising cellular mechanisms * Kinetic modelling of metabolic and signalling processes * Modelling of tissues in health and disease * Computational neuroscience / NeuroAI Illustrative applications emphasise biomedical problems. Application ----------- Apply here: https://forms.gle/DGehyz1Mbecu5TnT6 Deadline: May 31 Registration fee for selected candidates: €150 - decisions announced by June 7 - payment due within one week of acceptance, no later than June 15 Further information: https://www.uc.pt/events/computationalbiology/ Queries: computational.biology(a)uc.pt — The Computational Biology network, University of Coimbra (forwarded by Renato Duarte, CNC-UC)

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On behalf of Davide Carbone: Workshop 'A Scientist's Guide to AI', November 2-5, Paris
by Reinoud Maex May 22, 2026

May 22, 2026

Dear colleagues, We are pleased to announce SGAP 2026 (A Scientist's Guide to AI - Paris), a thematic school for researchers and PhD students in the Île-de-France region who want to get started with machine learning tools in their research. The event will take place November 2–5, 2026, at INRIA Paris (13th arrondissement). The program runs over three days: * two days of tutorials covering ML fundamentals and deep learning. * a third day (Nov 4th) showcasing concrete examples of AI applications across scientific fields. The targeted audience are researchers and students in biology, chemistry, physics and related fields. No prerequisites are needed in machine learning, only core mathematical knowledge and prior python programming will be assumed. Pre-registration are open on the conference website: https://sgap.sciencesconf.org/<https://sgap.sciencesconf.org>, where you can also find the tentative program. Registration is free but mandatory for attendance. See you in November!

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FSL Neuroimaging Course 2026 - Registration
by Rezvan Farahibozorg May 21, 2026

May 21, 2026

Dear all, Registration is still open for FSL Course 2026, which will be held in-person June 22nd – 26th in Bordeaux, France. You can find details and registration info here: https://open.oxcin.ox.ac.uk/pages/fslcourse/website/upcoming.html This comprehensive neuroimaging course will cover basic and more advanced analysis tools, as available in FSL software. The course will cover the theory and practice of functional, structural, diffusion and resting state brain image analysis. Background concepts and the practicalities of analyses are taught in detailed lectures. These lectures are interleaved with hands-on practical sessions, where attendees learn how to carry out analysis for themselves on real data. The contents covered in the course are primarily aimed at applications in basic science and clinical research (not clinical practice). If you have any questions, please feel free to contact: fslcourse(a)ndcn.ox.ac.uk We hope to see you at the course! The FSL Course team

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Two open PhD positions at the Max Planck Institute for Biological Cybernetics
by Roxana Zeraati May 20, 2026

May 20, 2026

Dear all, I recently started my research group at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, and we currently have two open PhD positions. In "Natural Decision Making Group <https://www.kyb.tuebingen.mpg.de/906930/natural-decision-making>", we aim to understand how animals learn the dynamics of their environment across different timescales and adapt their decisions accordingly. We study this in the context of foraging behavior, which allows us to link neural, behavioral, and environmental dynamics in naturalistic settings. Specifically, we develop data-driven, species-specific computational models by integrating methods from reinforcement learning, dynamical systems, and AI. Here you can find more information about the PhD positions and the application process: https://nextcloud.tuebingen.mpg.de/index.php/s/bYwTJibWPXW6NMH I would appreciate it if you could share this call with anyone who might be interested in your academic network. Best wishes, Roxana Zeraati Minerva Fast Track Group Leader Max Planck Institute for Biological Cybernetics

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Call for participation & posters - workshop “Cortex Structure and Function in Monkey, Mouse and Man” (Sep 21-24, 2026)
by von Behren, Christina May 20, 2026

May 20, 2026

Dear all, hereby, we would like to draw your attention to the upcoming workshop “Cortex Structure and Function in Monkey, Mouse and Man”. This workshop aims to bring together researchers from the fields of systems neuroscience, comparative transcriptomics, connectomics, and primate palaeobiology in one place to foster mutual awareness and interdisciplinary discussions as well as identify yet unknown principles in the development, organization and function of the primate brain from computational and experimental points of view. * when: Sep 21-24, 2026 * where: Hanse Wissenschaftskolleg (HWK) Delmenhorst, Germany * pre-registration by May 31, 2026 via https://www.uni-bremen.de/hwk-workshop-2026 workshop outline: Evolution in mammal brains has formed basic building blocks that might superficially look similar, but are organized in different structures and are obviously specialized for distinct computations. Accumulating evidence indicates that, while rodents are close evolutionary relatives to our own primate lineage, fundamental changes on all levels of brain organization occurred at the primate-rodent-split. In addition, subsequent primate evolution appears to be marked by apparently qualitative grade shifts. Recent progress across distinct disciplines provides a springboard to take a fresh perspective on what makes primate brains special. This workshop aims to enhance this comparative cognition perspective by contributions on avians and machines, which, despite having very different “brain” structures, perform functions that are surprisingly similar to those of mammals. Confirmed speakers: Tatjana Engel, Katja Nowick, Marieke Schölvinck, Matthias Kaschube, Henner Koch, Ken Miller, Huib Mansfelder, Wiktor Młynarski, Fabian Sinz, Andreas Neef, Dan Eric Nilsson, Madineh Sedigh-Sarvestani, Ziad Hafed, Fred Wolf, Daniel Huber, Alessandro Treves, David Dahmen, Neda Shahidi, Jonas Rose, Andreas Kreiter and Udo Ernst. For further information and pre-registration visit https://www.uni-bremen.de/hwk-workshop-2026. The workshop is co-funded by the Priority Program SPP 2205 Evolutionary Optimization of Neuronal Processing <https://www.uni-goettingen.de/de/618311.html> and NeuroNex Working Memory <https://www.nxwm.io/> . We are very much looking forward to meeting you in September! Best regards (on behalf of the organizers), Britta **************** Dr. Britta Korkowsky Coordinator Goettingen Campus Institute for Dynamics of Biological Networks (CIDBN) Bernstein Center for Computational Neuroscience Graduate Program in Theoretical and Computational Neuroscience SPP 2205 Evolutionary Optimization of Neuronal Processing University of Goettingen Heinrich-Düker-Weg 12 37073 Göttingen Tel.: +49-551-39-26675

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IMOL Online Seminar – Karl Friston: “The Physics of Motivation” – 17 June 2026
by Nicola Catenacci May 19, 2026

May 19, 2026

[Apologies for multiple posts; please distribute to interested people] Dear colleagues, We are pleased to launch the *Intrinsically Motivated and Open-ended Learning (IMOL) Online Seminar Series*. IMOL research explores how learning systems can autonomously generate goals, acquire skills, and continually adapt through open-ended interactions with the environment. Inspired by mechanisms observed in humans and animals, such as intrinsic motivations and self-motivated behaviour, the field brings together ideas from AI, robotics, neuroscience, developmental psychology, and cognitive science. The series will host leading scientists presenting recent advances and perspectives on IMOL themes and related topics. We are honoured to announce that the first seminar in the series will be delivered by *Professor Karl Friston (UCL, UK), who will present a talk entitled “The Physics of Motivation” the 17th of June 2026*. More information about the talk, together with the online meeting link, is provided below. The seminar series is organised by the IMOL Community, which also coordinates the IMOL workshop series and related initiatives. If you are interested in learning more about IMOL, or getting involved in the community, we encourage you to apply for membership ( http://www.imol-community.org/) and subscribe to the mailing list ( https://groups.google.com/g/imol-community) We look forward to seeing you on June 17th. Best regards, Nicola ************ MEETING DETAILS ************ - TITLE: The physics of motivation - WHEN: 17th of June, 16:30 (UCT+1; BST) - LINK: IMOL seminar - Karl Friston | Meeting-Join | Microsoft Teams <https://teams.microsoft.com/meet/332210692358706?p=W4WlQZzUA9yOALkuK5> - ABSTRACT: This overview of the free energy principle offers an account of embodied exchange with the world that associates neuronal operations with actively inferring the causes of our sensations. Its agenda is to link formal (mathematical) descriptions of dynamical systems to a description of perception in terms of beliefs and goals. The argument has two parts: the first calls on the lawful dynamics of any (weakly mixing) ergodic system – from a single cell organism to a human brain. These lawful dynamics suggest that (internal) states can be interpreted as modelling or predicting the (external) causes of sensory fluctuations. In other words, if a system exists, its internal states must encode probabilistic beliefs about external states. Heuristically, this means that if I exist (am) then I must have beliefs (think). The second part of the argument is that the only tenable beliefs I can entertain about myself are that I exist. This may seem rather obvious; however, it transpires that this is equivalent to believing that the world – and the way it is sampled – will resolve uncertainty about the causes of sensations. We will consider the implications for functional anatomy, in terms of predictive coding and hierarchical architectures, and conclude by looking at the epistemic behaviour that emerges – using simulations of active inference. - SPEAKER: *Karl J. Friston*, MBBS, MA, MRCPsych, MAE, FMedSci, FRBS, FRS. Professor: Queen Square Institute of Neurology, University College London. Honorary Consultant: The National Hospital for Neurology and Neurosurgery. Karl Friston is a theoretical neuroscientist and authority on brain imaging. He invented statistical parametric mapping (SPM), voxel-based morphometry (VBM) and dynamic causal modelling (DCM). These contributions were motivated by schizophrenia research and theoretical studies of value-learning, formulated as the dysconnection hypothesis of schizophrenia. Mathematical contributions include Variational Laplace and generalized filtering for hierarchical Bayesian model inversion. Friston currently works on models of functional integration in the human brain and the principles that underlie neuronal interactions. His main contribution to theoretical neurobiology is a free-energy principle for action and perception (active inference). Friston received the first Young Investigators Award in Human Brain Mapping (1996) and was elected a Fellow of the Academy of Medical Sciences (1999). In 2000 he was President of the international Organization of Human Brain Mapping. In 2003 he was awarded the Minerva Golden Brain Award and was elected a Fellow of the Royal Society in 2006. In 2008 he received a Medal, College de France and an Honorary Doctorate from the University of York in 2011. He became of Fellow of the Royal Society of Biology in 2012, received the Weldon Memorial prize and Medal in 2013 for contributions to mathematical biology and was elected as a member of EMBO (excellence in the life sciences) in 2014 and the Academia Europaea in (2015). He was the 2016 recipient of the Charles Branch Award for unparalleled breakthroughs in Brain Research and the Glass Brain Award, a lifetime achievement award in the field of human brain mapping. He holds Honorary Doctorates from the Universities of York, Zurich and Radboud University. ------------------------------------------------------------------------------------------------------------------------------- Dr. Nicola Catenacci Volpi, PhD Research Fellow in Information Theory for AI & Robotics Adaptive Systems Research Group The University of Hertfordshire School of Computer Science College Lane Hatfield, Hertfordshire AL10 9AB United Kingdom E-mail: n.catenacci-volpi(a)herts.ac.uk

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Open Faculty Position – Department of Computer Engineering, Universidad de Santiago de Chile
by Javier Baladron May 19, 2026

May 19, 2026

Dear colleagues, The Department of Computer Engineering at the Universidad de Santiago de Chile invites applications for an open faculty position. We seek candidates who meet the following requirements: - Undergraduate degree in Computer Engineering, Computer Science, or related fields. - Ph.D. in Informatics, Computer Science, Cybersecurity, Artificial Intelligence, or related areas. - Teaching experience in the relevant area of specialization. - Record of scientific publications indexed in WoS and Scopus, consistent with the candidate’s academic trajectory. - Participation in research projects. - For applicants whose native language is not Spanish, ability to teach in Spanish within the first year of employment. Priority will be given to candidates conducting research in Cybersecurity or Artificial Intelligence. Preferably, candidates should also demonstrate: - Active national and international scientific collaboration networks. - Experience supervising undergraduate and graduate theses. - Proficiency in English. In the event of equal merit between candidates, preference will be given to female applicants. Questions and informal applications may be sent directly to me at javier.baladron(a)usach.cl We would appreciate it if you could share this call with potentially interested candidates and relevant academic networks. Best regards, Javier Baladrón Department of Computer Engineering Universidad de Santiago de Chile

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Open PhD Position at the Institute of Machine Learning and Neural Computation, TU Graz
by Ozan Özdenizci May 18, 2026

May 18, 2026

Dear all, We have an open PhD position in our research group at the Institute of Machine Learning and Neural Computation, Graz University of Technology, Austria. We are offering a 3-year doctoral researcher position focused on reliable and resource-efficient deep learning techniques, with an emphasis on spike-based neural computation in modern learning systems. The doctoral research will address both fundamental and applied algorithmic questions in learning methods and neural architectures. More information on the position and how to apply: https://www.tugraz.at/institute/iml/institute/open-positions#c725665 Best regards, Ozan Özdenizci -- Dr. Ozan Özdenizci Assistant Professor Institute of Machine Learning and Neural Computation Graz University of Technology Inffeldgasse 16b/I, 8010 Graz, Austria

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World wide VVTNS series (6th season): Towards a general model of human reward-based learning | Maria Eckstein Google Deepmind | Wednesday, May 20, 2026, at 11:00 am ET
by David Hansel May 17, 2026

May 17, 2026

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the lecture Maria Eckstein Google Deepmind on the topic of Towards a general model of human reward-based learning The lecture will be held on Zoom on May 20, 2026 at *11:00 am ET * > To receive the link: https://www.wwtns.online/register-page >> > > *Abstract: *Traditional work in the study of human reward-based learning involves designing an experimental task---often inspired by Reinforcement Learning (RL) theory---and fits a small set of computational models---often inspired by RL algorithms---to that dataset. For example, researchers often model human behavior on bandit tasks using variants of Q-learning. While this approach has been highly productive, leading to landmark discoveries such as the dopamine reward prediction error hypothesis, it also has limitations. This talk focuses on the lack of generalizability of such models: Even if they closely fit behavior on the original task, models derived from the one-task-one-model paradigm usually predict behavior on other tasks quite poorly. I argue that this lack of generalizability is a fundamental problem for the cognitive sciences: we intuitively expect our models to be robust to superficial task differences, such as variations in the number of choice options, reward probabilities, or the exact kind of non-stationarity. I will propose potential solutions to this problem along two dimensions: the behavioral dataset and the computational model. Regarding computational models, I will introduce work in which we moved beyond the limitations of hand-crafted one-off models by employing flexible, data-driven methods. These methods allowed us to compare classes of models instead of individual model instances, allowing us to cover the space of possible models more exhaustively, and innovate cognitive mechanisms very efficiently. For the behavioral dataset, we move from using single learning tasks to a comprehensive task space that encompasses most existing paradigms in the literature, while closing the gaps between them in a near-continuous fashion. Our results suggest that more general models in conjunction with broader datasets can pave the road toward increasingly general models of human reward-based learning and decision making, and a persistent departure from many aspects of RL theory. *About VVTNS : Launched as the World Wide Theoretical Neuroscience Seminar (WWTNS) in November 2020 and renamed in homage to Carl van Vreeswijk in Memoriam (April 20, 2022), Speakers have the occasion to talk about theoretical aspects of their work which cannot be discussed in a setting where the majority of the audience consists of experimentalists. The seminars, **held on Wednesdays at 11 am ET,** are 45-50 min long followed by a discussion. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.* ᐧ ᐧ

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Postdoc and PhD student position at EPFL about investigating human locomotion using neuromechanical simulations and humanoid robots
by Auke Ijspeert May 16, 2026

May 16, 2026

*Postdoc and PhD student position for a project investigating and leveraging the neuromechanics of human locomotion using humanoid robots (Fall 2026)* The Biorobotics laboratory (Biorob, https://www.epfl.ch/labs/biorob/) at EPFL (Lausanne, Switzerland) has one Postdoc and one PhD student position for a project aiming at investigating and leveraging the neuromechanics of human locomotion using humanoid robots. See https://www.epfl.ch/labs/biorob/openings/ The objectives of the project are (1) to investigate the principles of healthy and pathological human locomotion using numerical models (neuromechanical simulations), and (2) to use insights from biology to develop bio-inspired locomotion controllers to be used together with reinforcement learning on humanoid robots. *Background:* The versatility of human locomotion is still not well understood from a neuroscience point of view nor well replicated in humanoid robots. In particular, the interactions between higher centers (e.g. the motor cortex), the spinal cord and the musculoskeletal system are poorly understood. The goal of this project is to develop a computational architecture that (i) integrates both spinal cord circuits and supraspinal control; (ii) uses deep reinforcement learning for supraspinal planning and learning, (iii) allows testing hypotheses about human motor control and pathologies at a conceptual level, and (iv) can serve as basis for controlling and learning versatile motor skills in humanoid robots. *Requirements:* The goal would be to hire one researcher with a background in computational neuroscience (idealy with experience in numerical models of human locomotion) and one researcher with a background in robotics (ideally with expertise in the control of legged or humanoid robots). The ideal candidates should also have strong backgrounds in math and programming, and an interest in interdisciplinary research. *Deadline and starting date:* Applications will be considered starting from now on, and then continuously until the position is filled. A good starting date would be *September 2026.* *Application: *See https://www.epfl.ch/labs/biorob/openings/ -- ----------------------------------------------------------------- Prof Auke Jan Ijspeert (he/him) Biorobotics Laboratory EPFL-STI-IBI-BIOROB, ME D1 1226, Station 9 EPFL, Ecole Polytechnique Fédérale de Lausanne CH 1015 Lausanne, Switzerland Office: ME D1 1226 Tel: +41 21 693 2658 Fax: +41 21 693 3705 www:http://biorob.epfl.ch Email:Auke.Ijspeert@epfl.ch -----------------------------------------------------------------

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NeuroAI Research Scientist / Machine Learning Engineer — University of Rome Tor Vergata × Tether.io
by nicola toschi May 15, 2026

May 15, 2026

Dear Comp Neuro community, We are looking for a highly motivated NeuroAI Research Scientist / Machine Learning Engineer to join a collaborative research effort between the University of Rome Tor Vergata and Tether.io<https://Tether.io> The position sits at the intersection of computational neuroscience, machine learning, foundation models, and brain-computer interfaces. The work will focus on developing open, reproducible methods for encoding and decoding brain activity from invasive and non-invasive neural recordings, including fMRI, EEG/MEG, ECoG, iEEG, and related data modalities. The successful candidate will contribute to projects involving neural decoding and encoding, multimodal representation learning, generative reconstruction of images, music, speech and other perceptual content, cross-subject and cross-modality alignment, and the study of how brain activity maps onto the latent spaces of modern vision, language, and audio foundation models. We are particularly interested in candidates with a background in machine learning, computational neuroscience, neuroimaging, signal processing, physics, computer science, engineering, or related quantitative fields. Strong Python and deep-learning experience, especially with PyTorch, JAX, or TensorFlow, is expected. Experience with real neural data and/or modern generative and representation-learning models is highly valued. The role offers the opportunity to contribute to high-impact publications, open-source tools, international collaborations, and ongoing research at the interface of AI, neuroscience, and neural interface technologies. Remote-friendly arrangements may be possible depending on the role and project needs. The LinkedIn announcement is available here: https://www.linkedin.com/feed/update/urn:li:activity:7461095365547741184/ To apply, please send a CV, a brief statement of research interests, and optionally 1–2 representative publications, projects, or GitHub links to: nicola.toschi(a)uniroma2.eu<mailto:nicola.toschi@uniroma2.eu> and matteo.ferrante(a)tether.io<mailto:matteo.ferrante@tether.io> 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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Call for contributed talks: CNS*2026 Information Theory Workshop
by Marilyn Gatica May 14, 2026

May 14, 2026

Dear all, We are pleased to announce that the Workshop on Methods of Information Theory in Computational Neuroscience <https://jlizier.github.io/CNS2026-InfoTheoryWorkshop/> will be held once again as part of the 35th Annual Computational Neuroscience Meeting ( CNS*2026 <https://www.cnsorg.org/cns-2026>), in Halifax, Canada. The full CNS*2026 conference will take place from July 11–15, 2026, with workshops held on July 14–15, 2026. Our confirmed and tentatively confirmed *invited speakers *so far include: - Demian Battaglia, CNRS / University of Strasbourg, France - Marilyn Gatica, Northeastern University London, UK - Jaroslav Hlinka, Czech Academy of Sciences, Czech Republic - Joseph Lizier, The University of Sydney, Australia - Patricio Orio, Universidad de Valparaíso, Chile - Maria Pope, Indiana University, USA - Thomas Varley, University of Vermont, USA - ...more TBA! We would like to *call for contributions* to talks. If you are interested in contributing a talk, please send a title and abstract to Joseph T. Lizier (joseph.lizier(a)sydney.edu.au) and Marilyn Gatica ( marilyn.gatica(a)nulondon.ac.uk) Earlier submissions and submissions from speakers from underrepresented groups will be prioritised. We will review submissions weekly starting May 25, and the call will remain open until all available slots have been filled. Please pay attention to the registration for CNS*2026 deadlines and fees, as workshop registration at least is required for attendance, and see our website <https://jlizier.github.io/CNS2026-InfoTheoryWorkshop/> <https://jlizier.github.io/CNS2026-InfoTheoryWorkshop/>for more details. We hope you will join us there! *Organising Committee:* Joseph T. Lizier, Chair, The University of Sydney, Australia Marilyn Gatica, Co-Chair, Northeastern University London, UK Demian Battaglia, CNRS / University of Strasbourg, France

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Master 2 computational neurosciences, Lyon (France)
by DI VOLO MATTEO May 13, 2026

May 13, 2026

Dear colleagues, Applications for EU students are now open for the Master 2 in Computational Neuroscineces<https://masterneuro.univ-lyon1.fr/m2-cns/> at the University of Lyon (France). The CNS program in Lyon trains students in modern computational and analytical methods to study the brain: from the electrical activity of single neurons to neural networks, interacting brain regions, and animal behavior. Students learn the principles of brain function by applying statistics, signal processing, and computational modeling to real neuroscientific datasets, gaining extensive hands-on experience through practical Python-based work. The main objective of CNS is to equip students with the skills and critical perspective needed to design, conduct, and interpret analyses of electrophysiological and behavioral data from a mechanistic point of view. Applications are done through the e-candidat platform <https://ecandidat.univ-lyon1.fr/#!accueilView> Best regards, Matteo Di Volo ---- Matteo Di Volo Professor, University Claude Bernard Lyon1 Co-Director Master 2 Computational Neurosciences https://masterneuro.univ-lyon1.fr/m2-cns/ Stem Cell and Brain Research institute INSERM, NEF team: https://sbri.fr/teams/neurobiology-of-executive-functions/ Personal website: https://matteodivolo.wordpress.com/

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NITMB Ideathon, August 10-12, 2026: Applications are open
by William L. Kath May 12, 2026

May 12, 2026

The National Institute for Theory and Mathematics MathBio Ideathon will take place August 10–12, 2026 in Chicago! The goal of this workshop is to bring together researchers with interests at the interface of biology and mathematics to tackle unsolved problems through interdisciplinary collaboration. Participants will share their expertise via lightning talks and form vertically integrated teams (PIs and trainees) around the most promising ideas. The teams will tackle these problems and formulate actionable research plans. Teams will have the opportunity to continue their work to solve these problems at a later date through NITMB's Focused Research Award Program. Here is a link to more information: https://www.nitmb.org/nitmb-mathbio-ideathon A application form for the workshop is available on the website. Applications close Monday, June 8th. Participation is limited to approximately 40 people. We are looking for people who know of interesting unsolved problems at the interface between mathematics and biology (or who would like to learn about them) and who will be fully engaged and actively contribute throughout the workshop — starting with initial discussions and team formation to the development of collaborative research plans and beyond. This may be of particular interest to early-career researchers, including postdocs and graduate students, who are looking for new topics to add to their research portfolios. We will cover travel and accommodation for selected participants. We also provide meals while people are engaged at the NITMB (typically breakfast and lunch). We look forward to the possibility of having you join us in Chicago! Best regards, - Bill Kath

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Workshop on Theory of Neuromorphic Computing, Liverpool UK, 9th June 2026
by john.sylvester＠liverpool.ac.uk May 12, 2026

May 12, 2026

Dear All, We invite you to a workshop Theory of Neuromorphic Computing Date: 9 June 2026 with the first talk starting at 11am Location: School of Computer Science and Informatics, Ashton Building, University of Liverpool Website: https://neuromorphic-theory.github.io Cost: Free (but registration required, see webpage) Neuromorphic computing is a computing paradigm inspired by biological neural systems. It is based on spiking, event-driven architectures in which memory and computation are closely integrated. Neuromorphic chips have already shown several promising advantages over conventional von Neumann architectures, particularly in terms of energy efficiency. This workshop will explore the theoretical foundations of neuromorphic computing, with a focus on algorithms and computational complexity. Although the hardware has developed rapidly, the theory has not kept pace. Our aim is to create a forum for discussion on rigorous models of neuromorphic systems, allowing researchers to study their computational power and compare them with classical models of computation. These models must capture not only time and space, but also energy-related resources such as spikes and synaptic operations. Many thanks, John Sylvester & David Purser

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World wide VVTNS series (6th season): Mean-field dynamics in networks with clustered connectivity and dendritic nonlinearities | Gabriel Ocker, Boston University | Wednesday, May 13, 2026, at 11:00 am ET
by David Hansel May 10, 2026

May 10, 2026

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the lecture Gabriel Ocker Boston University on the topic of Mean-field dynamics in networks with clustered connectivity and dendritic nonlinearities The lecture will be held on Zoom on May 13, 2026 at *11:00 am ET * > To receive the link: https://www.wwtns.online/register-page > > *Abstract: *Networks of interconnected neurons display diverse patterns of activity. Relating these patterns to the structure of the network is a central goal of theoretical neuroscience. Classic neural field and rate models have been powerful tools for this purpose due to their analytical tractability. Here, we show that the recently-developed combinatorial threshold-linear network (CTLN) model is a mean-field theory for excitatory-inhibitory Hawkes networks, with clustered connectivity, in an inhibition-stabilized regime. This mapping allows us to leverage powerful analytical results for CTLN networks to predict diverse macroscopic dynamics of clustered Hawkes networks, including metastability between various macroscopic fixed points, limit cycles, and chaotic attractors. We will then examine an extension of this approach to models with nonlinear dendritic dynamics, focusing on dendritic calcium spikes.We uncover a marked point process mean-field theory for these networks and use this to examine how somatic vs dendritic-targeting connectivity shapes the mean-field equilibrium phase diagram. *About VVTNS : Launched as the World Wide Theoretical Neuroscience Seminar (WWTNS) in November 2020 and renamed in homage to Carl van Vreeswijk in Memoriam (April 20, 2022), Speakers have the occasion to talk about theoretical aspects of their work which cannot be discussed in a setting where the majority of the audience consists of experimentalists. The seminars, **held on Wednesdays at 11 am ET,** are 45-50 min long followed by a discussion. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.* ᐧ ᐧ

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Human-AI Workshop at IJCAI 2026
by Guozhang Chen May 7, 2026

May 7, 2026

Dear colleagues, I am pleased to announce that our proposal for the Human-AI Workshop at IJCAI 2026 has been accepted. Workshop website: https://hbai2026.github.io/ Date: One day between August 16–21, 2026 Place: Bremen, Germany Paper submission link: https://openreview.net/group?id=ijcai.org/IJCAI-ECAI/2026/Workshop/HBAI Submission deadline: May 15, 2026 Please share this information within your networks. Thank you for your support. Best regards, Guozhang Chen Assistant Professor School of Computer Science Peking University

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Postdoctoral Position in Human Brain–Computer Interfaces
by João Barbosa May 6, 2026

May 6, 2026

Dear all, The Neuromodulation Institute (Paris) invites applications for a Postdoctoral Researcher position (full-time, 2-year contract with the possibility of extension) to join a human brain–computer interface project led by Philippe Domenech <http://computationalbrainteam.com/en/people> (Neuromodulation Institute, Paris) in direct collaboration with João Barbosa <http://jbarbosa.org/> (Neuromodulation Institute, Paris) and Guillaume Bellec <http://guillaume.bellec.eu/> (Technical University of Vienna). The work will be carried out in the center of Paris and the newly created Neuromodulation Institute. The position is available immediately and will remain open until filled. About the Project This position is part of an interdisciplinary collaboration involving computational neuroscientists, clinicians, and engineers. The goal is to establish model-driven, multi-site stimulation experiments in human patients and move towards novel therapies for psychiatric disorders through the control of human brain dynamics via closed-loop stimulation. As an initial step toward these broader goals, the postdoctoral researcher will work with electrophysiological data collected from epilepsy patients implanted with ~124 intracranial LFP electrodes, enabling simultaneous recording and multi-site stimulation. We already collected several datasets (open-loop) and up to 4 subjects are collected per month through a national network of clinicians. The work carried out by the successful applicant will sit at the intersection of machine learning, computational neuroscience and data analyses of human intracranial electrophysiology. The medium-term ambition is to expand this work to additional patient populations, including individuals with treatment-resistant major depression and obsessive-compulsive disorder, and to incorporate recording techniques such as large-scale multi-unit activity and sub-second neuromodulation (e.g. dopamine, serotonin, noradrenaline, etc) detection using ML-augmented voltammetry. Key responsibilities include developing data-driven state-space models of neural dynamics for optimal control policies for stimulation as well as inference pipelines for predicting network responses of intracranial recordings. The position emphasizes computational modeling, theory, and algorithmic development, rather than hands-on experimental data collection. Candidate Profile We are seeking a highly motivated candidate with strong quantitative and computational skills, and demonstrated research experience in at least one of the following areas: machine learning, simulation-based inference, reinforcement learning, generative/diffusion models and dynamical systems. Required Skills and Experience - Strong scientific programming skills in Python, in particular proficiency in PyTorch, Jax or related - Demonstrated experience in machine learning - Excellent written and spoken English. - Direct experimental experience is not required. However, the successful candidate should be enthusiastic about interacting with clinicians, neurosurgeons, and patients during experimental planning and execution. Preferred but not required - Experience working with time series data, in particular intracranial recordings (LFP, ECoG, depth electrodes) in humans or other animals. We strongly encourage applications from individuals that are underrepresented in academia. What We Offer - Opportunity to contribute to multiple ongoing projects at the forefront of human intracranial research - A highly interdisciplinary research environment spanning computational neuroscience, machine learning and cognitive neuroscience - A collaborative lab culture with close mentorship from senior investigators. - Support for career development, including opportunities to co-supervise students, present at conferences and workshops - Paris has an increasingly tight network of systems and computational neuroscience and offers many possibilities for collaborations How to apply Please send a statement of your past work and future research interests (one page each), CV and at least one manuscript demonstrating required experience to palerma(a)gmail.com with the subject “Postdoctoral Position in Human Brain–Computer Interfaces”. Joao Barbosa

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