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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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