June 2026 - Comp-neuro - lists.cnsorg.org

1st Call for Participation: International Artificial Intelligence Summer School – IAISS 2026, Sept 20-24, Riva del Sole Resort & SPA @ Tuscany * Registration: by June 23 *

by ICAS Organizing Committee

* Apologies for multiple copies. Please forward to anybody who might be interested, thanks! * IAISS2026, A Residential Summer School in Frontier AI IAISS 2026 is a full-immersion 5-day Summer School in Tuscany on cutting-edge advances in AI and Generative AI with lectures delivered by world-renowned experts. 📍 Riva del Sole Resort & SPA @ Tuscany, Italy, 🗓 Sept 20-24, 2026 🔗 https://2026.iaiss.cc iaiss(a)icas.cc 🎤 LECTURERS: Each Lecturer will hold up to four lectures on one or more research topics. Stefano V. Albrecht, Nanyang Technological University, Singapore Giuseppe De Giacomo, University of Oxford, UK Christoph Feichtenhofer, Meta Superintelligence Labs, USA Sven Giesselbach, T-Systems International, Germany Jamie Hayes, Google DeepMind, UK Sumi Helal, University of Bologna, Italy Albert Q. Jiang, Mistral AI, Paris, France & University of Cambridge, UK Marine Le Morvan, INRIA Saclay, France Bruno Lepri, FBK, Italy Sebastian Lins Risi, Sakana AI, Japan & IT University of Copenhagen, Denmark George Paliouras, National Center for Scientific Research "Demokritos", Athens, Greece Panos Pardalos, University of Florida, USA More Lecturers TBA 🔗 https://2026.iaiss.cc/lecturers/ 🔗 https://2026.iaiss.cc/lectures/ 🚨 REGISTRATION: by June 23 (AoE) https://2026.iaiss.cc/registration/ Applicant *may* submit (during the Registration Process) a research abstract (max 2 pages; any format) for presentation. School directors and the scientific committee will review the abstracts and will recommend for poster and/or short talk. Abstract can be submitted by June 23 during the registration process. PAST EDITIONS: https://2026.iaiss.cc/previous-editions/ IAISS Norbert Wiener Best Presentation Award in Artificial Intelligence: https://2026.iaiss.cc/best-presentation-award/ VENUE: https://2026.iaiss.cc/venue/ Riva del Sole Resort & SPA Località Riva del Sole‚ Castiglione della Pescaia (Grosseto) CAP 58043‚ Tuscany‚ Italy p: +39-0564-928111 e: booking.events(a)rivadelsole.it w: https://www.rivadelsole.it/en/ ✅ CERTIFICATE & 8 ECTS: The International Artificial Intelligence Summer School – IAISS 2026 is a full-immersion five-day Summer School at the Riva del Sole Resort & SPA (Castiglione della Pescaia – Grosseto – Tuscany, Italy) on cutting-edge advances in AI and Generative AI with lectures delivered by world-renowned experts. The Summer School provides a stimulating environment for PhD students, Post-Docs, junior academics (only up to assistant professors), early career researchers, and industry leaders (and highly motivated, promising and brilliant Master students / BSc students). Participants will also have the chance to present their results with talks, and to interact with their colleagues, in a convivial, professional and productive environment. PhD students, PostDocs, Industry Practitioners and Junior Academics (only up to assistant professors) will be typical profiles of the IAISS attendants. The Summer School will involve a total of 36–40 hours of lectures, according to the academic system the final achievement will be equivalent to 8 ECTS points for the PhD Students (and some strongly motivated Master Student – BSc Student) attending the Summer School. Language: English. To participate in the IAISS 2026, all attendants must (1/2) register for the school (by June 23, 2026) and (2/2) book accommodation at the school venue, “Riva del Sole Resort & SPA” (by July 23, 2026); all attendants must stay at the “Riva del Sole Resort & SPA”. Once accommodation has been booked at “Riva del Sole Resort & SPA“, the participant must send this information (including the Booking Number) to the IAISS organizing committee (iaiss(a)icas.cc) IAISS is a residential school, so all lecturers and participants must reside in the same Hotel (Riva del Sole Resort & SPA). No exceptions are made. For privacy reasons, the Hotel cannot match people. If you have someone to share the apartment with, please send to the Hotel ( booking.events(a)rivadelsole.it ) the name, surname and email address. Otherwise the solution is to book an apartment in single use. IAISS is organized as a non-profit scientific event. Please note that only IAISS registered participants can book a room (in hotel or apartment) at the Riva del Sole Resort & SPA with the accommodation form attached in the registration email and with the IAISS Discounted Rates. The Booking Office of the Riva del Sole Resort & SPA will verify the names of the participants and the corresponding registration number to confirm the booking. Anyone interested in participating in IAISS 2026 should register as soon as possible: 👉 https://2026.iaiss.cc/registration/ See you in Riva del Sole in September! IAISS 2026 Organizing Committees. https://2026.iaiss.cc iaiss(a)icas.cc https://www.linkedin.com/groups/19146028/ Obviously, this is only a Call for Participation, to have complete and updated information we recommend you access the relevant website: https://2026.iaiss.cc the News Section: https://2026.iaiss.cc/category/news/ and the FAQ: https://2026.iaiss.cc/faq/ * Apologies for multiple copies. Please forward to anybody who might be interested, thanks! *

June 7, 2026

GeMAIHc 2027: early registration June 22

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: June 22, 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, 1 symposium, 4 local presentations, and hands-on activities with 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), tba PROFESSORS AND COURSES (list to be completed) Pierre Baldi (University of California Irvine), [introductory/advanced] The AI-driven Healthcare of the Future 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 Faisal Mahmood (Harvard University), tba Tom Pollard (Massachusetts Institute of Technology), tba Hoifung Poon (Microsoft Research), [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), tba 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. HANDS-ON ACTIVITIES 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

June 6, 2026

Call for participation - Summer School on Computational Decision Sciences, London, Sept 7-11

by Subramoney, Anand

Dear all, It’s our pleasure to announce the Graduate Summer School on Computational Decision Sciences (GSS-CDS<https://center-decision-sciences.com/cds-graduate-school-2026/>)––the second edition of the summer school at the Centre for Decision Sciences, Royal Holloway, University of London. What GSS-CDS will bring together an interdisciplinary audience tackling decision making in different scientific fields (see Program<https://center-decision-sciences.com/program-2026/>). The focus is on mathematical and computational modelling, integrating concepts and methods from mathematical psychology, computational psychiatry, computational neuroscience, computational social sciences, machine learning, and cultural evolution. Attendees will benefit from talks from leading researchers and practical hands-on sessions. Attendees will also have the opportunity to receive career advice during social networking events and reflect critically about research practices in EDI sessions. Where and When GSS-CDS will take place at Stewart House, within Senate House<https://center-decision-sciences.com/directions/>, in Central London, on September 7th-11th (see Schedule<https://center-decision-sciences.com/schedule-2026/>). Target audience GSS-CDS is targeted towards attendees from diverse fields (e.g., psychology, neuroscience, social sciences, computer science, etc.) and career stages (masters, PhD, postdoc, and junior PI). Prerequisite A basic background knowledge in elementary statistics (e.g., probability theory) and programming in Python/R is highly recommended to master the technical skills, but no prior experience with computational modeling is required. Registration Course fee is £480 (includes the registration fee, lunch, tea/coffee breaks, reception events and VAT). To register, please visit this page<https://center-decision-sciences.com/registration-2/>. Places are limited and registrations will close on Monday, June 15th, at 10am UK time. Please feel free to share this information with anyone you think might be interested in participating. Looking forward to seeing you all in September. Best wishes, Gabriele, Nura, Anand This email, its contents and any attachments are intended solely for the addressee and may contain confidential information. In certain circumstances, it may also be subject to legal privilege. Any unauthorised use, disclosure, or copying is not permitted. If you have received this email in error, please notify us and immediately and permanently delete it. Any views or opinions expressed in personal emails are solely those of the author and do not necessarily represent those of Royal Holloway, University of London. It is your responsibility to ensure that this email and any attachments are virus free.

June 5, 2026

Fully Funded PhD Fellowship in Computational Neuroscience in Rome

by Pazienti Antonio

A PhD position is available at the Italian National Institute of Health (Rome) in the group of Maurizio Mattia ____________________________________________________________________________________ PhD (Rome) – Computational Neuroscience / Dynamical Systems / Epilepsy Fully funded PhD at Sapienza University Project: Multiscale Digital Twin for Pediatric Focal Epilepsy Based on Recurrent Neural Networks. Focus on: * Data-driven modeling of brain dynamics * Analysis of clinical time-series * Inference of dynamical systems from experimental data Looking for candidates with strong background in: physics / applied math / theoretical neuroscience, and interest in real data analysis. ML (incl. RNNs) used as a tool—not the main focus. Deadline: 17 June 2026 Oral interview for selected applicants (in-presence): 7 July 2026 https://phd.uniroma1.it/web/concorso42.aspx?s=&i=3528&m=&l=EN&p=&a= Contact: Antonio Pazienti antonio.pazienti(a)iss.it<mailto:antonio.pazienti@iss.it> , Maurizio Mattia maurizio.mattia(a)iss.it<mailto:maurizio.mattia@iss.it> ______________________________________________________________________________________________ Long version follows: ________________________________________________________________________________________ PhD position (f/m/d) in Computational Neuroscience (Strong Mathematics / Theoretical Physics Background Preferred) Project: Multiscale Digital Twin for Pediatric Focal Epilepsy Based on Recurrent Neural Networks Sapienza University of Rome (Italy) and Italian National Institute of Health (ISS) Application deadline: 17 June 2026, 14:00 (CET) Oral interview for selected applicants (in-presence): 7 July 2026, 14:00 (CET) @Sapienza University, Rome Project Overview We invite applications for a fully funded PhD position within the Sapienza PhD programmes (42nd cycle, A.Y. 2026/2027) focused on developing quantitative models of pediatric focal epilepsy grounded in experimental data. The project aims to build a multiscale digital twin of the epileptic brain, integrating: * Experimental recordings (e.g., EEG, SEEG) * Neuroimaging-derived structure and connectivity * Mathematical and dynamical models of neural activity Digital brain twins are personalized computational models that integrate structural and functional data to capture brain dynamics and support clinical decision-making, particularly relevant for epilepsy. The PhD will focus on: * Analysis of large-scale experimental datasets (EEG, clinical recordings) * Inference of dynamical models from data * Development of data-constrained multiscale models of seizure dynamics * Use of machine learning tools (including RNNs) as part of a broader modeling and inference framework, rather than as an end in itself PhD Programme The position is part of a Sapienza PhD programme in neuroscience / computational neuroscience-related disciplines at one of Europe’s largest universities. Key features: * Duration: 3 years * Interdisciplinary training combining: * Neuroscience and clinical research * Mathematics, physics, and dynamical systems * Data analysis and statistical inference * Structured doctoral training with research activities and seminars Sapienza PhD programmes aim to develop independent researchers with strong analytical and methodological skills in complex systems and biomedical data. Funding This is an externally funded PhD position within the official Sapienza call, including: * Full PhD scholarship (baseline ≈ €16k gross/year) * Additional funding for research and mobility Candidate Profile We are explicitly seeking candidates with a strong quantitative and analytical background, and a clear interest in working with real experimental data. Required * MSc (or equivalent) in: * Physics * Applied Mathematics * Theoretical Physics * Engineering or related quantitative disciplines * Strong skills in: * Mathematical modeling (dynamical systems, stochastic processes) * Data analysis and statistical inference * Programming (Python or equivalent) Strongly preferred * Demonstrated interest in: * Analysis of experimental or observational data * Time-series data and signal processing * Experience with: * Neural or physiological data (e.g., EEG/MEG) * Inverse problems or parameter estimation * Scientific computing Additional (not mandatory) * Familiarity with machine learning methods (e.g., RNNs) (primarily as tools for modeling or inference, not as a core requirement) What You Will Gain * Training at the interface of mathematics, data analysis, and neuroscience * Experience working with real clinical and experimental datasets * Skills in model-based inference and multiscale modeling * Opportunity to contribute to clinically relevant research in epilepsy Location Rome, Italy — Sapienza University, a leading European research institution with a large international PhD community, and Italian National Institute of Health Application Process Applications must be submitted via the official Sapienza portal: https://phd.uniroma1.it/web/concorso42.aspx?s=&i=3528&m=&l=EN&p=&a= Typical required documents: * CV * Academic transcripts * Motivation letter (strong emphasis on quantitative/data analysis experience) * References Oral interview for selected applicants (in-presence): 7 July 2026, 14:00 (CET) @Sapienza University, Rome Informal Inquiries For questions, please contact: Antonio Pazienti antonio.pazienti(a)iss.it<mailto:antonio.pazienti@iss.it> Maurizio Mattia maurizio.mattia(a)iss.it<mailto:maurizio.mattia@iss.it> behavneurosci-phd(a)uniroma1.it<mailto:behavneurosci-phd@uniroma1.it> ________________________________________________________________________________________ Thank you, ---- Antonio Pazienti, PhD National Center for Radiation Protection and Computational Physics Italian National Institute of Health Viale Regina Elena 299, 00161 Roma (Italy) Phone: +39 06 4990 2857 E-mail: antonio.pazienti(a)iss.it<mailto:antonio.pazienti@iss.it> [https://www.iss.it/o/iss/images/ISS.png] Scegli l'Istituto Superiore di Sanità. Dona il 5x1000 alla Ricerca Sanitaria Firma e inserisci il Codice Fiscale 80211730587 ________________________________ Per saperne di più clicca qui<[https://www.iss.it/-/l-iss-sostiene-i-giovani-ricercatori-con-il-5x1000-1]>

June 4, 2026

NEST Conference 2026 on 16/17 June — Program overview — Register now!

by Hans Ekkehard Plesser

Dear Colleagues! We are very much looking forward to the NEST Conference 2026 which will take place in two weeks time on Tuesday / Wednesday 16/17 June 2026. We are excited to share with you an overview over the program we have assembled with three keynotes, three tutorials, one dozen talks and eleven posters. You will find presenters and contributions below. Please register at https://nest-simulator.org/conference at your earliest convenience! If you want to use the member rate (20€; normal rate 50€), you must apply for NEST Initiative e.V. membership and pay your dues by Sunday 7 June. Students, including PhD students, do not need to pay membership dues, for all others it is 25€ for 2026. Please go to https://www.easyverein.com/public/NESTINI/applicationform/13809 to apply. Absolutely last deadline for registration is Sunday 14 June at 23.59 CEST (UTC+2). See you at the NEST Conference 2026! Hans Ekkehard Plesser on behalf of the organizing committee Keynote Agnes Korcsak-Gorzo Biologically plausible supervised learning in large-scale networks Fynn Dobler, Maxime Carrire Lost in translation: How porting a brain-constrained model of word semantics to NEST revealed undocumented model assumptions Pablo Martinez-Canada From Circuits to Signals and Back: Integrating Biophysical Forward Modelling and Simulation-Based Inference to Decode Brain Dynamics Tutorial Agnes Korcsak-Gorzo Biologically plausible supervised learning with event-driven eligibility propagation Charl Linssen, Pooja Babu Modeling and simulating neuron models from NESTML on neuromorphic hardware Willem Wybo Creating, analyzing, simplifying, and simulating biophysical neurons with NEAT Talks Carlos Enrique Gutierrez Neuro-Workflow: Agent-Assisted Brain Modeling Catherine Schofmann Scaling Neural Networks On Accelerators With Procedural Connectivity Generation Gianmarco Tiddia Scalable network construction method for NEST GPU enables efficient multi-GPU simulations Jan Eirik Skaar, Hans Ekkehard Plesser Practice report: Porting a complex network model from BRIAN2 to NEST Jan Vogelsang, Susanne Kunkel Rethinking Synapse Placement in NEST for Cache-Efficiency on Many-Core Exascale Architectures Mahesh Madhav, Hans Ekkehard Plesser Issue #3217: Making NEST a part of the SPEC CPU 2026 benchmark suite Melissa Lober NUMA balancing hampering performance of spiking network simulations Pedro Ribeiro Pinheiro Simulating prefrontal cortex dynamics in a data-driven spiking neural network Rafael Fernando Gigante A Large-Scale Spiking Network Model of the Primary Motor Cortex Razvan Gamanut Subthreshold Dynamics in a Gap-Junction-Coupled PV Network Model of the Claustrum Sinovia Fotiadou Bridging NEST Microcircuits to Zerlaut Mean-Field Models: A Reproducible Single-Region Workflow for the Virtual Brain Twin Tibor Rozsa Toward reliable visual prosthetic stimulation under highly variable spontaneous activity Poster Alex Dimitrov et al Statistics of spiking neural networks based on counting processes Ariel Shmilli et al Long-term memory consolidation in spiking neural networks Camilo Jara Do Nascimento et al Dendritic plateau potentials enable learning over long timescales Charl Linssen et al Automated code generation of advanced plasticity rules for the SpiNNaker neuromorphic platform using NESTML Daniel Todt Parameter specification in spiking neural networks using NEST and simulation-based inference José Villamar et al Scaling up to billions of spiking neurons and trillions of synapses with NEST GPU Krishna Kant Singh Empowering Neuroscience Research with Portable HPC Containers Marie Olli Structural plasticity in large-scale spiking neural networks Markus Diesmann On polynomials in spiking neuronal network simulations Noah Ostendorf Motiforge: Flexible Motif-Constrained Network Generation for Structured Neural Architectures Pooja Babu Modeling and simulating two-compartment neuron model with NESTML on NEST GPU -- Prof. Dr. Hans Ekkehard Plesser Research Committee Chair, Faculty of Science and Technology Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

June 2, 2026

PhD positions in mathematical neuroscience at Université Côte d'Azur

by yuxiu.shao＠univ-cotedazur.fr

Dear all, I am establishing a new research group at Université Côte d'Azur and am recruiting PhD students to work at the interface of mathematics, physics, and neuroscience. Our research develops a unified mathematical framework to understand how structural connectivity shapes neural dynamics, and uses this framework to uncover the mechanisms underlying adaptive, flexible behavior. More details about the PhD positions can be found here: https://shaonannan.github.io/position/ I would greatly appreciate it if you could share this message with anyone who might be interested. All applications will be treated confidentially and without bias. Best regards, Yuxiu SHAO Chaire de Professeur Junior Laboratoire Jean Alexandre Dieudonne (LJAD/CNRS UMR7351) & NeuroMod Université Côte d'Azur Campus Sciences, Parc Valrose, 28 avenue Valrose

June 2, 2026

Open postdoc position: Spinal Cord Stimulation for Children with Cerebral Palsy

by Genís Prat Ortega

Hi all, We invite applications for a postdoctoral researcher at the Rehab and Neural Engineering Labs (RNEL), University of Pittsburgh. RNEL <https://www.rnel.pitt.edu/> offers a highly collaborative environment where BCI and neurostimulation groups work together with the mission to improve the quality of life of individuals with neurological impairments. The postdoctoral researcher will lead a pioneering research to test the efficacy and safety of spinal cord stimulation and deep brain stimulation to improve motor and cognitive function for children with Cerebral Palsy. This role involves: - Leading first-in-human clinical trials - Design and conduct human electrophysiology experiments - Develop computational modeling of neural networks to investigate the mechanisms underlying neurostimulation. The ideal candidate has a background in Mathematics, Physics, Computational Neuroscience, Neuroengineering or any related field. Experience in clinical trials is not required but the candidate must be motivated to lead the research sessions. We are seeking a Postdoctoral Researcher motivated to work in a multidisciplinary team together with neurosurgeons, physical therapists, neurologists and neuroengineers to bring new neurostimulation therapies to children with Cerebral Palsy. If any of these ideas sound interesting to you, send me an email with your CV and a short motivation at gep67(a)pitt.edu. Questions are welcome—don't hesitate to reach out. The position is available immediately and will remain open until filled. Genis Prat Ortega, PhD Assistant Professor Department of Neurological Surgery Rehabilitation and Neural Engineering Laboratories, University of Pittsburgh

June 1, 2026