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

Sept. 7, 2026

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 PH.D. STUDENT - HIPPOCAMPAL REPRESENTATIONS IN DYNAMIC ENVIRONMENTS TV-L E13 100%, 3 years Analyse an unpublished, large-scale in-vivo miniscope dataset: CA1 pyramidal cells tracked across 11 tasks and 34 days.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

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

Sept. 7, 2026

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

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

Sept. 3, 2026

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

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

Sept. 2, 2026

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

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

Sept. 2, 2026

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

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

Sept. 1, 2026

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

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

Aug. 31, 2026

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

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

Aug. 30, 2026

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

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

Aug. 29, 2026

******************************************************** 1st INTERNATIONAL SCHOOL ON GENERATIVE & MULTIMODAL AI FOR HEALTHCARE GeMAIHc 2027 Milan, Italy February 1-5, 2027 https://gemaihc.irdta.eu/2027/ ******************************************************** Co-organized by: Human Technopole IRDTA – Institute for Research Development, Training and Advice ****************************************************** Early registration: September 18, 2026 ****************************************************** SCOPE AI is rapidly redefining biomedical research, clinical decision-making, and healthcare delivery worldwide. GeMAIHc 2027 will provide participants with a comprehensive overview of state-of-the-art AI methodologies. Topics will include generative modelling, multimodal data integration and augmentation, large language models and clinical NLP, medical image synthesis and analysis, as well as evaluation, robustness, validation, ethical considerations, and regulatory aspects of AI systems in healthcare. GeMAIHc 2027 aims to become a leading international forum at the intersection of generative AI, multimodal learning, and healthcare innovation. The program will emphasize both methodological foundations and real-world clinical applications, combining theoretical insights with practical perspectives. This interdisciplinary event will feature 18 monographic three-hour courses, 2 keynote lectures, 3 scientific sessions, 1 symposium, and a hackathon. Leading academics and industry pioneers will share their expertise and perspectives with attendees. In-person interaction and networking will be central components of the event, while full remote participation will also be possible. ADDRESSED TO The program is open to PhD students and postdoctoral researchers in AI, data science, and biomedical disciplines, clinicians and healthcare professionals, industry practitioners and innovators, and policymakers and stakeholders in digital health. There are no formal academic prerequisites for participation. Researchers and professionals at all career stages are welcome. An international audience is expected, with backgrounds spanning computer science, medicine, engineering, mathematics, statistics, physics, and the social sciences. GeMAIHc 2027 will offer a unique opportunity to gain in-depth knowledge of a rapidly evolving field, to interact with experts across disciplines, to establish collaborations and expand professional networks, and to explore how AI is reshaping the future of healthcare. VENUE GeMAIHc 2027 will take place in Milan, one of Europe’s leading international centers for science, industry, fashion, and finance. The venue will be: Human Technopole Viale Rita Levi-Montalcini, 1 20157 Milan, Italy https://humantechnopole.it/en/ STRUCTURE Three parallel courses will run throughout the event. Participants will be free to choose the sessions they wish to attend and may move between courses at any time. A symposium will offer participants and companies the opportunity to present ongoing research or industrial developments through 10-minute oral presentations. The school will include a hackathon, during which participants will work in teams to tackle challenges in generative and multimodal AI for healthcare. All lectures will be video recorded and made available to participants for 45 days after the event. Full live online participation will be possible. Nevertheless, the organizers emphasize the importance of in-person interaction and networking in research training events of this kind. KEYNOTE SPEAKERS Deborah Estrin (Cornell University), Transforming Longitudinal Care with Digital Biomarkers and Therapeutics Lyle Palmer (Adelaide University), Deep Learning in Medicine: Some Lessons from Epidemiology and Genomics PROFESSORS AND COURSES Pierre Baldi (University of California Irvine), [introductory/advanced] The AI-driven Healthcare of the Future David Buckeridge (McGill University), [intermediate] Multi-Modal Data Analysis in Population and Public Health Alejandro Frangi (University of Manchester), [intermediate/advanced] Virtual Patient Populations for In Silico Trials Using Generative AI Based on Multimodal Real-World Data Charles Friedman (University of Michigan), [introductory] Synergizing AI and Learning Health Systems to Transform Health Judy Wawira Gichoya (Emory University), [introductory/advanced] Combination in a Hands on Lab for Harmonizing Radiology Datasets Maryellen Giger (University of Chicago), [introductory/intermediate] Role of Data & Algorithms in Trustworthy Medical Imaging AI Casey Greene (University of Colorado), [introductory/advanced] Translating Generative AI into Healthcare from Pharmacogenomics to Foundation Models Tina Hernandez-Boussard (Stanford University), [intermediate/advanced] The AI Lifecycle in Healthcare: Evaluation, Deployment, and Responsible Implementation Jianying Hu (IBM Thomas J. Watson Research Center), [intermediate/advanced] Advanced Computing for Biomedical Research and Discovery Jayashree Kalpathy-Cramer (University of Colorado), [introductory] Toward Digital Twins: Multimodal AI for Imaging and Precision Medicine Alex John London (Carnegie Mellon University), [intermediate/advanced] Ethical and Scientific Challenges to Unlocking the Clinical Value of Artificial Intelligence Asoke Nandi (Brunel University of London), [introductory/advanced] Selected Case Studies of Medical Image Segmentation Tom Pollard (Massachusetts Institute of Technology), [introductory/intermediate] Data: The Foundation, Constraint, and Failure Mode of Deployable Health AI Hoifung Poon (Recursion), [advanced] Toward Virtual Patient: AI for Accelerating Medical Discovery Jian Tang (Mila-Québec AI Institute), [introductory/advanced] Generative AI for Protein Design Peter van Ooijen (University of Groningen), [intermediate] Multimodal AI for Adaptive Radiotherapy: Tumor Segmentation, Uncertainty, and Explainability Karin Verspoor (Royal Melbourne Institute of Technology), [introductory/intermediate] AI Scientists and beyond: Roles for GenAI in Biomedical Research and Discovery Jelmer M. Wolterink (University of Twente), [intermediate/advanced] Data Representations in Health Digital Twinning: From Features to Foundation Models HT RESEARCH PERSPECTIVES Human Technopole will organize 3 scientific sessions: Probabilistic Models for (Medical) Image Analysis, by Jan Funke, Florian Jug, Federico Carrara, and Benjamin Salmon AI Models for Computational Biology, by Andrea Sottoriva, Michele Calabrò, and Manuel Dileo AI in Health Data Science, by Francesca Ieva, Andrea Ganna, Michela Carlotta Massi, Nicole Fontana, and Alessia Mapelli SYMPOSIUM A symposium will feature voluntary 10-minute oral presentations on ongoing research projects and industrial developments. Participants interested in presenting should submit a one-page abstract including title, authors, and summary to david(a)irdta.eu by January 8, 2027. HACKATHON Hands-on team activities will be organized around challenges in generative and multimodal AI for healthcare. The challenges will be released two weeks before the beginning of the school. A jury will evaluate the submissions, and the winners will be announced at the end of February 2027. Winning teams will receive a modest monetary prize, while runners-up will receive certificates of recognition. ORGANIZING COMMITTEE Jan Funke (Milan) Ilaria Guerini (Milan) Francesca Ieva (Milan) Carlos Martín-Vide (Tarragona, program chair) Michela Carlotta Massi (Milan, local chair) Santiago Montes (Tarragona, webpage) Sara Morales (Luxembourg, finances) David Silva (London, organization chair) REGISTRATION Registration is available at: https://gemaihc.irdta.eu/2027/registration/ The selection of six courses requested during registration is tentative and non-binding. This information will help estimate demand for logistical planning purposes. As venue capacity is limited, registrations will be processed on a first-come, first-served basis. Registration will close once capacity has been reached. Early registration is strongly recommended. FEES Registration fees include access to all school activities and lunches. Several early registration deadlines are available, and fees vary depending on the registration period. Fees are identical for on-site and online participation. ACCOMMODATION Accommodation suggestions will be provided in due time at: https://gemaihc.irdta.eu/2027/accommodation/ CERTIFICATE Participants will receive a certificate indicating 40 hours of academic activities. This certificate should be suitable for participants seeking ECTS recognition from their home institutions. SPONSORS Companies, institutions, and organizations interested in sponsoring the event may download the sponsorship leaflet from: https://gemaihc.irdta.eu/2027/sponsors/ QUESTIONS AND FURTHER INFORMATION david(a)irdta.eu ACKNOWLEDGMENTS Human Technopole Universitat Rovira i Virgili IRDTA – Institute for Research Development, Training and Advice

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

Aug. 28, 2026

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

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