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NeuroAI Assistant Professor Position at Carnegie Mellon University

by Aran Nayebi

Dear colleagues, *TL;DR: CMU is hiring for an Assistant Professor in NeuroAI. Apply here: https://apply.interfolio.com/189268 <https://apply.interfolio.com/189268>* *Details below:* Carnegie Mellon University (CMU) invites applications for a tenure-track Assistant Professor in the Neuroscience Institute from scholars working broadly at the intersection of Neuroscience and Artificial Intelligence. We welcome a wide range of research programs, provided they maintain a substantive connection to neuroscience through data, theory, or modeling. Examples of relevant research topics include but are not restricted to: generative models of brain data, AI-based analysis tools for neural activity or connectivity, explainable AI grounded in cognitive/neuroscience principles, human-AI alignment, normative agentic models of animal behavior, mechanistic models of memory or learning in neural networks, descriptive models of invariant representations and dynamics, and embodiment in both natural and artificial systems. The successful candidate will join a vibrant, collaborative environment spanning multiple departments at CMU. Our NeuroAI group leverages CMU’s world-class research in machine learning and AI, robotics, cognitive and systems neuroscience, neurotechnology, data science, engineering, and biological sciences. Joint appointments and courtesy appointments across departments are common in the Neuroscience Institute, and may be an opportunity for some candidates. CMU has a well-established structure for interdisciplinary collaboration in this domain, including specialized programs in neural computation and machine learning, and neurorobotics. The NI also encourages collaboration with industry and commercialization of new ideas. Aspiring entrepreneurs can be supported by a variety of business resources at CMU such as the Swartz Center and new entrepreneurship initiatives. Candidate responsibilities include establishing a visible, externally funded research program; teaching and mentoring in NI; recruiting and supervising both masters and Ph.D. students; and contributing to curricular innovation, including emerging initiatives, such as a new masters program in neural technologies. Information about the Neuroscience Institute can be found at https://www.cmu.edu/ni/. For more information on CMU’s NeuroAI group, see CMU Builds on Its Strengths To Advance NeuroAI <https://www.cmu.edu/news/stories/archives/2026/august/cmu-builds-on-its-str…> *Qualifications* Qualifications include a Ph.D. or equivalent in neuroscience, machine learning, robotics, computer science, cognitive science/psychology, electrical engineering, or a related field; evidence of research excellence and potential for leadership; and a commitment to high-quality teaching and mentoring. *Application Instructions* Applicants should submit their materials via Interfolio. Required materials include a one-page cover letter describing fit to NI, CMU, and the collaborative Pittsburgh community in neuroscience, AI, and related disciplines; a research statement (three to four pages); a one- to two-page teaching statement; a curriculum vitae; and three letters of recommendation. Applicants may also submit an optional 1-page Personal and Service statement. Review of applications will begin immediately and all applications received by November 1st, 2026 will be given full consideration. The positions will be open until filled. The position will start July 1, 2027. Best, Aran -- Assistant Professor Machine Learning Department Neuroscience Institute (core faculty), Robotics Institute (by courtesy) Carnegie Mellon University https://cs.cmu.edu/~anayebi

Sept. 14, 2026

2 postdoc and 1 phD positions on computational mechanisms of human perception (Alex Hyafil & Chris Summerfield, Barcelona)

by Alexandre Hyafil

The group of Alex Hyafil at the CRM Barcelona (https://ahyafil.github.io/) is looking for two postdoc researchers and a PhD student. One of the postdoc positions will be co-supervised by Chris Summerfield (Universitat Pompeu Fabra Barcelona / Oxford; https://humaninformationprocessing.com/) The selected candidate will investigate the computational operations underlying visual scene perception through a combination of simulation of artificial visual systems (conv nets, visual transformers) and human experiments. The position is for two years. The other postdoc researcher (2-year duration) and the PhD student (4-year) will work jointly on identifying canonical Bayesian operations at play in human visual and auditory perception. The project involves Bayesian modelling, artificial vision network simulations, behavioral and EEG experiments as well as intra-cranial EEG experiments (in collaboration with Benjamin Morillon, AMU Marseille). We will look for complementarity of the two profiles, notably in terms of quantitative and experimental backgrounds. The hired researchers will benefit from the stimulating environment of the Barcelona area in cognitive and computational neuroscience. Our groups form part of a larger interacting network of neuroscience labs in Barcelona ( http://www.barccsyn.org) Financial support is provided by the Spanish National Agency of Investigation (FPI fellowship for the PhD student). *APPLICATION:* Send a curriculum and motivation with a list of two contacts for recommendation letter at https://bit.ly/ChrisAlexPositions. Informal enquiries are welcome. *DEADLINE:* before October 31 for the PhD position; until position is filled for the postdoc positions. *STARTING DATE:* before July 2027 for the PhD position; flexible for the postdoc positions

Sept. 14, 2026

COSYNE 2027: Meeting announcement, Abstract submission is now open

by Tomas Hromadka

==================================================== Computational and Systems Neuroscience 2027 (Cosyne) MAIN MEETING & WORKSHOPS 11 - 16 March 2027 Montreal, Canada www.cosyne.org ==================================================== ---------------------------------------------------- MEETING ANNOUNCEMENT ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks is selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. All abstract submissions will be reviewed double blind. The deadline for Abstract submission is 18 October 2026. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, neuromodulation, and computation with spiking networks. We would like to foster increased participation from experimental groups as well as computational ones. Please circulate widely and encourage your students and postdocs to apply. IMPORTANT DATES Abstract submission is now open. Abstract submission deadline: 18 October 2026 When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. COSYNE INVITED SPEAKERS Dani Bassett (UPenn) Chand Chandrasekaran (Boston U) Christine Constantinople (NYU) Paul Cisek (U Montreal) Kevin Franks (Duke) Leslie P Kaelbling (MIT) Andy Leifer (Princeton) Scott Linderman (Stanford) Amy Orsborne (U Washington) Cengiz Pehlevan Kempner (Harvard) Kanaka Rajan (Harvard; Kempner Inst) Rebecca Saxe (MIT) Carsen Stringer (Janelia) ORGANIZING COMMITTEE General Chairs: Kimberly Stachenfeld (DeepMind) and Mark Histed (NIH) Program Chairs: Annegret Falkner (Princeton) and Guillaume Lajoie (MILA/U Montreal) Workshop Chairs: N Alex Cayco Gajic (ENS) and Marcelo Mattar (NYU) Tutorial Chairs: Eva Dyer (Georgia Tech) and Alex Williams (NYU) Mentorship and Networking Chairs: Renata Brito (Mount Sinai) and Srikanth Ramaswamy (Newcastle U) Undergraduate Travel Chairs: Lea Duncker (Columbia) and Kevin Miller (DeepMind) Development Chair: Michael Long (NYU) Media Chairs: Roxana Zeraati (MPI Biol Cybernetics) and Claire Sturgill (TU Dresden) Poster Design: Maja Bialon EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Anne-Marie Oswald (U Pittsburgh) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT meeting [at] cosyne.org ----------------------------------------------------- COSYNE MAILING LISTS ----------------------------------------------------- Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> About-> Mailing lists for details.

Sept. 11, 2026

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