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NeuralNet 2026, Nov 25th-27th, Paris – Registration and Abstract Submission Now Open

by Arthur Leblois

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

Sept. 11, 2026

Subject: Postdoc Position: Predicting Epilepsy from iEEG (University of Göttingen)

by Tristan Manfred Stöber

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

Sept. 11, 2026

Postdoctoral and PhD Opportunities in Infant NeuroAI at Trinity College Dublin

by ainetdineen＠gmail.com

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

Sept. 11, 2026

Call For Papers - UniReps Workshop in Paris 🔵🔴

by Organizers

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

Sept. 10, 2026

Frontier Series 2026 / Translational Neurocognitive Technologies

by Vasiliki Kondyli

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

Sept. 10, 2026

cuttingEEG garden Groningen

by Jelmer Borst

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

Sept. 9, 2026

Postdoctoral Positions at Washington University in St. Louis

by rncao90＠gmail.com

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

Sept. 8, 2026

[Jobs] 2 PhD + 1 Postdoc + 2 RA positions: hippocampus, world models, epilepsy (Göttingen)

by Tristan Manfred Stöber

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

Sept. 7, 2026

Application deadline approaching: Patagonian School of Science

by Ines Samengo

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

Sept. 7, 2026

Announcing SNUFA 2026: Nov 4-5 (online) - Abstract submission and registration now open!

by Friedemann Zenke

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

Sept. 3, 2026

Postdoctoral and PhD Positions in Computational Neuroscience & Machine Learning at UCLA

by Marcus Triplett

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.

Sept. 2, 2026

Submit to Collection: Computational and Theoretical Approaches to Multi-Scale Dynamics from Cells to Behavior

by DEPANNEMAECKER Damien

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

Sept. 2, 2026

Re: 2026 INCTN meeting @ Trieste, Italy - 22-24 Sept - abstract submission deadline approaching

by Eugenio Piasini

Dear all, This is a reminder that the registration deadline for the 2026 meeting of the Italian Network for Computational and Theoretical Neuroscience (INCTN) is approaching. Please register here<https://indico.sissa.it/event/190/> by September 3rd if you are planning to attend! We look forward to seeing you in Trieste! The organisers: Francesca Mastrogiuseppe, Eugenio Piasini, and Sebastian Goldt https://inctn.it/ ________________________________ From: Eugenio Piasini <epiasini(a)sissa.it> Sent: Tuesday, June 30, 2026 14:02 Subject: 2026 INCTN meeting @ Trieste, Italy - 22-24 Sept - abstract submission deadline approaching 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

Sept. 1, 2026

Algonauts Project 2027 Challenge

by Alessandro Gifford

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

Aug. 31, 2026

Last Seats Available! International Artificial Intelligence Summer School – IAISS 2026

by ICAS Organizing Committee

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

Aug. 30, 2026

GeMAIHc 2027: early registration September 18

by David Silva - IRDTA

******************************************************** 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

Aug. 29, 2026

The NIH BRAIN Theories, Models and Methods Program Application Information

by Mollick, Jessica (NIH/NIDA) [E]

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.

Aug. 28, 2026

PhD and Postdoc positions [Neuro-AI lab @ Technion] - Stefano Recanatesi

by Stefano Recanatesi

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

Aug. 28, 2026

Postdoctoral Fellow positions available to study spinal mechanisms of motor control

by Levine, Ariel (NIH/NINDS) [E]

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

Aug. 28, 2026

Funded PhD Position in NeuroAI and Computational Neuroimaging – University of Rome Tor Vergata

by nicola toschi

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

Aug. 27, 2026

Academic positions in Artificial Intelligence at the University of Surrey

by roman bauer

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

Aug. 27, 2026

Postdoc Positions in Cognitive and Computational Neuroscience at Washington University in St. Louis

by Runnan Cao

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

Aug. 26, 2026

Call for Papers: Novel Insights and Approaches in Time-frequency Analysis

by alireza valizadeh

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

Aug. 26, 2026

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

by Laurenz Wiskott

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

Aug. 25, 2026

Spectral analysis in neuroscience course for non-specialists

by Axel Hutt

============================================================= Course: Spectral analysis of time series in neuroscience: Fundamental methods ============================================================= The 1-day course addresses fundamental aspects of spectral analysis without diving much into theory, just from a practical point of view. The aim is to provide a fundamental understanding of the different techniques out there to avoid mistakes, artefacts and to be able to choose the best technique for the own data. The course is planned like an interactive workshop, where we discuss analysis techniques and clarify open questions and possibly fill gaps of methodology understanding. The course content addresses non-specialists in mathematical analysis, e.g. researchers with education in neurobiology, medicine or psychology, but of course it is also open to theory-oriented researchers who intend to understand the practical side of spectral analysis in neuroscience. Possible topics to be discussed are, e.g. * Sampling theory * Fourier analysis and its possible artefacts, e.g. aliasing, spectral leakage * Time-frequency analysis (Short-Time Fourier Transform, Wavelet Transform, Hilbert Transform and Empirical Mode Decomposition) and its limits in applications * Synchronisation, coherence and Phase-Amplitude Coupling Event information: * Location: Bernstein Center Freiburg im Breisgau, Großer Hörsaal, Hansastr. 9a , 79104 Freiburg, Germany ( [ https://www.bcf.uni-freiburg.de/ | https://www.bcf.uni-freiburg.de ] ) * Date of course and time: Friday, November 27 2026, 9:15-15:45 * Registration : send an email to Axel Hutt (email address: first name.lastname at inria.fr) * Registration deadline: Monday, November 9 2026 * Registration fee: none, free of charge The course is supported by the Neurowissenschaftliche Gesellschaft ( [ https://www.nwg-info.de/ | https://www.nwg-info.de/ ] ). -- Dr. rer. nat. Axel Hutt Directeur de Recherche Equipe NECTARINE - INRIA Nancy Center at University of Lorraine Equipe MLMS - iCube Strasbourg Bâtiment NextMed , 2, rue Marie Hamm 67000 Strasbourg, France Team webpage: https://www.inria.fr/fr/nectarine

Aug. 25, 2026