- Comp-neuro - lists.cnsorg.org

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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PhD and Postdoc positions [Neuro-AI lab @ Technion] - Stefano Recanatesi
by Stefano Recanatesi Aug. 28, 2026

Aug. 28, 2026

*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)

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Postdoctoral Fellow positions available to study spinal mechanisms of motor control
by Levine, Ariel (NIH/NINDS) [E] Aug. 28, 2026

Aug. 28, 2026

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>

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Funded PhD Position in NeuroAI and Computational Neuroimaging – University of Rome Tor Vergata
by nicola toschi Aug. 27, 2026

Aug. 27, 2026

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>

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