- Comp-neuro - lists.cnsorg.org

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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