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[jobs] Postdoc position in Toulouse (France): Deep learning models of the Global Workspace
by Rufin VanRullen June 29, 2026

June 29, 2026

Postdoctoral position available in an ERC-funded project exploring deep-learning implementations of the Global Workspace theory. We are seeking a highly motivated and dedicated post-doc to join our group in Toulouse, France in the Fall/Winter of 2026. The successful candidate will have a PhD and formal training in AI, Computer Science or related fields (e.g. computational neuroscience), and a keen interest in cognitive neuroscience. Our ERC Advanced Grant "GLoW" (2023-2028) aims to take inspiration from neuroscience and cognitive theories to build deep neural network models of cognition, capable of integrating or "grounding" information across sensory and linguistic modalities, and of displaying flexible cognitive behavior. Details on the ideas developed in the project can be found in this Opinion paper <https://www.cell.com/trends/neurosciences/fulltext/S0166-2236(21)00077-1>. The project is headed by Rufin VanRullen (CNRS, Toulouse, France), with external advisors Ryota Kanai (Araya, Tokyo, Japan) and Murray Shanahan (ICL/Deepmind, London, UK). Our lab <https://rufinv.github.io/> is part of the CerCo Institute <https://cerco.cnrs.fr/en> as well as the Artificial and Natural Intelligence Toulouse Institute (ANITI) <https://aniti.univ-toulouse.fr/en/>. Our team has many opportunities to collaborate with neuroscientists, computer scientists, linguists, roboticists etc. We have access to in-house (GPU) computing clusters as well as research-dedicated supercomputers. Typical appointments for post-docs are for 1 year, renewable for a 2nd year and beyond. The beginning post-doc salary is about 2,500 Euros/month (net), and can reach 3,500 Euros/month (net) for more experienced post-docs. The application procedure and additional information can be found on the CNRS portal <https://emploi.cnrs.fr/Offres/CDD/UMR5549-LESMAR-017/Default.aspx?lang=EN>. Please direct any query to: rufin.vanrullen [at] cnrs.fr --

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Postdoctoral Fellow – Generative AI for Mental Health at the Global Center for AI in Mental Health (GCAIMH) in New York
by Salvador Dura-Bernal June 29, 2026

June 29, 2026

Postdoctoral Fellow – Generative AI for Mental Health Global Center for AI in Mental Health (GCAIMH) University at Albany (SUNY) and SUNY Downstate Health Sciences University Albany, NY / Brooklyn, NY (Hybrid) Two-Year Fellowship Position Summary The Global Center for AI in Mental Health (GCAIMH),<https://gcaimh.org/> a collaboration between the University at Albany and SUNY Downstate Health Sciences University, seeks an outstanding Postdoctoral Fellow in Generative Artificial Intelligence to advance innovative AI solutions that improve mental health access, quality, and outcomes at scale. This position is funded through the Empire AI Postdoctoral Fellows Program and offers a unique opportunity to work at the intersection of artificial intelligence, mental health, global health, and public-good technology. Working closely with an interdisciplinary team of researchers, clinicians, computer scientists, and global health partners across SUNY institutions and international collaborators, the Fellow will contribute to the research, design, development, deployment, and evaluation of cutting-edge generative AI tools that support both frontline mental health interventions and evidence-based psychotherapy. Research Focus The Fellow will play a leading role in the development and evaluation of AI-powered initiatives for expanding access and equity in mental health, including but not limited to: JulienPFA: An AI-supported implementation tool designed to strengthen Psychological First Aid (PFA) delivery during humanitarian crises, disasters, terrorism, and mass violence events. The system offers just-in-time guidance to non-specialist providers while supporting implementation fidelity, workforce development, and ethical learning systems. TherAssist: A clinician-facing generative AI platform that supports psychotherapists delivering evidence-based treatments for anxiety and depression through real-time analysis, personalized treatment recommendations, and fidelity monitoring. Responsibilities The successful candidate will: * Research, design, develop, and evaluate generative AI models for mental health applications. * Deploy and use retrieval-augmented generation (RAG) to constrain large language models (LLMs) and multimodal AI systems. * Conduct research using large-scale clinical, behavioral, and linguistic datasets. * Utilize Empire AI computing resources for model training, evaluation, and deployment. * Develop methods for responsible, ethical, and explainable AI in healthcare settings. * Collaborate with clinicians, mental health researchers, software engineers, and data scientists. * Publish findings in peer-reviewed journals and present at national and international conferences. * Contribute to grant proposals and research dissemination activities. * Mentor graduate and undergraduate students involved in AI and mental health research. * Support partnerships with international collaborators focused on global mental health innovation. Required Qualifications * Ph.D. completed by start date, and not more than 5 years ago, in Computer Science, Artificial Intelligence, Machine Learning, Information Science, Data Science, Computational Neuroscience, Biomedical Informatics, or a closely related social science field with demonstrated skills and experience in computer science/artificial intelligence/machine learning. * Demonstrated expertise with large language models, retrieval-augmented generation (RAG), agentic AI systems, and/or multimodal AI. * Strong programming skills in Python and experience developing web-based AI applications with modern frameworks (e.g., Google Cloud Vertex, Gemini, CloudRun, Kubernetes, Firebase). * Experience working with large datasets and high-performance computing environments. * Strong publication record or evidence of research productivity. * Excellent written and verbal communication skills, including the ability to communicate clearly and effectively about complicated scientific topics with a range of audiences. * Ability to work effectively in interdisciplinary and collaborative research environments. Preferred Qualifications * Experience applying AI to healthcare, mental health, psychology, or social science domains. * Familiarity with responsible AI, AI ethics, fairness, privacy, and safety considerations. * Knowledge of natural language processing, speech analysis, or conversational AI systems. * Experience working with clinical or healthcare data. Research Environment The mission of GCAIMH is to leverage artificial intelligence to improve mental health as a public good through innovative research, workforce development, and scalable solutions with local and global impact. See website: https://gcaimh.org<https://gcaimh.org/>. To support this mission, the Fellow will have access to Empire AI's state-of-the-art high-performance computing infrastructure, enabling research that requires large-scale AI model training and evaluation. Appointment Details * Position Title: Postdoctoral Fellow, Generative AI for Mental Health * Appointment Length: Two years * Salary Range: $85,000 annually, plus benefits. * Location: The position will be physically located at the University at Albany with occasional site visits to SUNY Downstate in Brooklyn. Hybrid arrangements will be considered. * Start Date: Fall 2026 (anticipated) Application Instructions Applicants should submit: 1. Cover letter describing research interests and fit for the position 2. Curriculum vitae 3. Representative publications or writing samples 4. Contact information for three professional references Submit application materials to: Amy Nitza, Ph.D. Director, Global Center for AI in Mental Health University at Albany anitza(a)albany.edu<mailto:anitza@albany.edu> Review of applications will begin immediately. The position will remain open till filled. Commitment to Public Impact This position offers a rare opportunity to develop AI technologies that address critical challenges in mental health care, including workforce shortages, treatment quality, implementation fidelity, and equitable access to services worldwide. The successful candidate will contribute to innovations designed to improve mental health outcomes for diverse populations while advancing responsible and ethical AI development. ________________________________ The contents of this email message and any attachments are confidential and are intended solely for the addressee. The information may also be legally privileged. This transmission is sent in trust, for the sole purpose of delivery to the intended recipient. If you have received this transmission in error, any use, reproduction or dissemination of this transmission is strictly prohibited. If you are not the intended recipient, please immediately notify sender by reply email or by (718) 270-HELP.

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[CFP Deadline Extension] BEACON 2026 Workshop @ ICMI – Grounding Abstract Concepts in Multimodal Interaction (Deadline: July 17, 2026)
by rahul.simha.is＠gmail.com June 29, 2026

June 29, 2026

[Apologies for multiple posts; please distribute to interested colleagues and relevant mailing lists.] Dear all, We are pleased to announce that the submission deadline for the BEACON 2026 Workshop — Beyond the Concrete: Grounding Abstract Concepts in Multimodal Interaction, co-located with ACM ICMI 2026, has been extended to July 17, 2026. BEACON 2026 brings together researchers working on multimodal representation learning, embodied and developmental models, robotics, cognitive science, and hybrid cognitive architectures. The workshop aims to consolidate computational approaches, datasets, and evaluation methodologies for abstract concept grounding while identifying shared assumptions and open research challenges. A keynote talk will be given by Professor Gabriella Vigliocco, Professor of the Psychology of Language at University College London. Topics of interest include, but are not limited to: Grounding abstract concepts in multimodal interaction Hierarchical and developmental models of abstraction Cross-modal abstraction and alignment Embodied and interactive concept learning Multimodal action and goal representations Affective and contextual abstraction Embodied and interactive learning of abstract language Hybrid cognitive architectures for abstract grounding Evaluation methodologies for abstract concept grounding Multimodal datasets and benchmarks for abstract concepts Applications of abstract grounding in HCI and HRI Submission Formats Short papers: 4 pages Full papers: 8 pages All accepted and presented papers will be included in the proceedings of the ACM ICMI 2026 workshops. Submission Instructions Submit through the ICMI 2026 PCS portal: https://new.precisionconference.com/icmi26/ After signing in, select: SIGCHI → ICMI 2026 → ICMI 2026 Workshop: Beyond a Concrete: Grounding Abstract Concepts in Multimodal Interaction Then click Go. Updated Important Dates Submission deadline: July 17, 2026 Notification of acceptance: July 31, 2026 Camera-ready submission: August 7, 2026 Workshop: October 9, 2026 Workshop website: https://beacon2026.github.io/ We welcome contributions from the multimodal interaction, artificial intelligence, robotics, human–computer interaction, human–robot interaction, and cognitive science communities. For questions, please contact Rahul Singh Maharjan at rahul.simha.is(a)gmail.com Best regards, Rahul Singh Maharjan on behalf of the BEACON 2026 Organizers

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Doctoral Summer School on Robotics and Intelligent Machines
by Calogero Maria Oddo June 26, 2026

June 26, 2026

𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗿𝗲 𝗼𝗽𝗲𝗻 𝗳𝗼𝗿 𝘁𝗵𝗲 𝟰𝘁𝗵 𝗗𝗼𝗰𝘁𝗼𝗿𝗮𝗹 𝗦𝘂𝗺𝗺𝗲𝗿 𝗦𝗰𝗵𝗼𝗼𝗹 𝗼𝗻 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗮𝗻𝗱 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗠𝗮𝗰𝗵𝗶𝗻𝗲𝘀 (𝗗𝗥𝗜𝗠𝗦 𝟮𝟬𝟮𝟲) Join us in the seaside of Tuscany, Italy, for a week of training, innovation, hands-on experimentation, and international networking. From August 30 to September 6, 2026, DRIMS will bring together PhD students, researchers, and professionals from academia and industry for an immersive experience dedicated to the latest advances in robotics and intelligent machines. The programme combines lectures, hands-on activities, multidisciplinary teamwork, project-based learning, and networking opportunities with leading researchers and peers from around the world. Participants will have the opportunity to deepen their knowledge in areas including: • 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗮𝗻𝗱 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗠𝗮𝗰𝗵𝗶𝗻𝗲𝘀 • 𝗠𝗲𝗰𝗵𝗮𝗻𝗶𝗰𝗮𝗹 𝗗𝗲𝘀𝗶𝗴𝗻 • 𝗩𝗶𝘀𝗶𝗼𝗻 𝗮𝗻𝗱 𝗧𝗼𝘂𝗰𝗵 𝗦𝗲𝗻𝘀𝗶𝗻𝗴 • 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 • 𝗛𝘂𝗺𝗮𝗻–𝗥𝗼𝗯𝗼𝘁 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻 • 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗡𝗲𝘂𝗿𝗼𝗔𝗜 𝗳𝗼𝗿 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 Several full and partial registration fee waivers are available thanks to the generous support of the IEEE Robotics and Automation Society (IEEE RAS), the Italian Institute of Robotics and Intelligent Machines (I-RIM), the BRIEFS research infrastructure, and several sponsoring companies (https://www.phdrims.com/sponsors.php<https://www.phdrims.com/sponsors.php?s=7>). 𝗙𝗼𝗿 𝗺𝗼𝗿𝗲 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝘁𝗼 𝗮𝗽𝗽𝗹𝘆: • https://www.phdrims.com/ • https://www.santannapisa.it/en/alta-formazione/4th-Doctoral-Summer-School-o… We look forward to welcoming the next generation of researchers and innovators in robotics and intelligent machines, The DRIMS Steering and Scientific Committee https://www.phdrims.com/comitato_organizzatore.php<https://www.phdrims.com/comitato_organizzatore.php?s=3> -- Calogero M. Oddo, PhD (‪Scholar‬<https://scholar.google.com/citations?hl=it&user=y1rffgkAAAAJ&view_op=list_w…>, Scopus<https://www.scopus.com/authid/detail.uri?authorId=16176089500>) Associate Professor of Bioengineering, Sant'Anna School of Advanced Studies, Pisa, Italy https://www.santannapisa.it/en/calogero-maria-oddo http://www.santannapisa.it/en/neuro-robotic-touch-laboratory Vice-Director, Centro Interdisciplinare Linceo Giovani https://www.lincei.it/en/oddo-calogero-maria email: calogero.oddo(a)santannapisa.it<mailto:calogero.oddo@santannapisa.it> While it suits me to email now, I do not expect a reply outside of your own working hours.

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Deadline approaching: Call for Abstracts for the Bernstein Conference 2026
by Bernstein Conference June 24, 2026

June 24, 2026

+++ The Bernstein Network Computational Neuroscience invites proposals for Poster Sessions at the Bernstein Conference 2026 in Frankfurt am Main. +++ ____ *Bernstein Conference * Each year, the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange. It has established itself as one of the most renowned conferences worldwide in this field, attracting students, postdocs, and PIs from around the world to meet and discuss new scientific discoveries.** https://www.bernstein-conference.de/ <https://www.bernstein-conference.de/> ____ *IMPORTANT DATES * Bernstein Conference: *September 28 – October 1, 2026 * Deadlines: *Poster Session* abstract submission: *July 1, 2026 at 15:00 CEST Travel Grant *application: *July 1, 2026 at 17:00 CEST * Notification of acceptance: *July 2026 **____ ABSTRACTS* We invite the computational neuroscience community to submit their abstracts for Poster Sessions. All accepted abstracts will be published online and will be citable via Digital Object Identifiers (DOI). Further information can be found here: https://bernstein-network.de/bernstein-conference/abstract-submission/ <https://bernstein-network.de/bernstein-conference/abstract-submission/> ____ *TRAVEL GRANTS* To support the participation of young researchers at the Bernstein Conference, the Bernstein Network offers up to 10 Travel Grants, each endowed with 500 €. Further information can be found here: https://bernstein-network.de/bernstein-conference/early-career-scientists/t… <https://bernstein-network.de/bernstein-conference/early-career-scientists/t…> ____ *INVITED SPEAKERS* Roshan Cools (Donders Institute for Brain, Cognition and Behaviour, The Netherlands) Benjamin Grewe (Institute of Neuroinformatics of the ETH and UZH, Switzerland) Andreas Herz (LMU Munich, Germany) Ewelina Knapska (Nencki Institute of Experimental Biology, Poland) John Krakauer (Champalimaud Foundation, Portugal) Jeehyun Kwag (Seoul National University, Korea) Anna Levina (University of Tübingen, Germany) Richard Naud (University of Ottawa, Canada) Bence Ölveczky (Harvard University, USA) Sandro Romani (Janelia Research Campus, USA) ____ *CONFERENCE COMMITTEE* Stefan Rotter (Conference Chair) Matthias Kaschube (Conference Host) Tim Vogels (Program Chair) Panayiota Poirazi (Program Vice Chair) Katharina Wilmes (Workshop Chair) Juan Álvaro Gallego(Workshop Vice Chair) & Nicolas Brunel, Alex Cayco-Gajic, Monika Jadi, Jennifer Li, Wiktor Młynarski, Richard Naud, Joseph Raimondo, Tatyana Sharpee, Taro Toyoizumi, Eleni Vassilaki ____ For any further questions, please contact: bernstein.conference(a)fz-juelich.de <mailto:bernstein.conference@fz-juelich.de>

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Call for participation - Summer School on Computational Decision Sciences, London, Sept 7-11
by Subramoney, Anand June 23, 2026

June 23, 2026

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.

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Last Call: Apply to the Master in Data Management and Curation in Trieste, Italy (Deadline: 30 June 2026)
by Eugenio Piasini June 22, 2026

June 22, 2026

Dear all, We would like to remind you that applications for the 2026–2027 edition of the Master in Data Management and Curation (MDMC), jointly organized by AREA Science Park<https://www.areasciencepark.it/en/> and SISSA<https://www.sissa.it/> in Trieste, Italy, are open until 30 June 2026, 1PM CEST. MDMC is an advanced postgraduate program designed to train the next generation of professionals in Research Data Management, FAIR data, Open Science, data stewardship, semantic technologies, and AI-enabled data infrastructures. The program combines lectures from international experts with a six-month internship carried out within leading research institutions and organizations like OGS<https://www.ogs.it/en>, FBK<https://energy.fbk.eu/>, FIF<https://www.fegato.it/eng/>, CNR-IOM<https://www.iom.cnr.it/> and several companies. Multiple forms of financial support are available for outstanding candidates: • 5 institutional fellowships offered by OGS<https://www.ogs.it/en>, SISSA<https://www.sissa.it/>, and AREA Science Park,<https://www.areasciencepark.it/en/> covering the participation fee and, in some cases, including an additional financial grant. • 8 additional tuition fee waivers for the highest-ranked candidates admitted to the program. • 6 excellence grants of €3,000. • Additional financial support opportunities for non-resident students. The total amount of available support makes MDMC accessible to a large number of talented candidates interested in pursuing a career in data management, data stewardship, Open Science, and research infrastructures. Further details on the program, admission requirements, and available fellowships can be found at: https://www.areasciencepark.it/call/mdmc/

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Doctoral and postdoctoral studies in the neuroscience of dynamic action planning and motor control, University of Montreal
by Paul Cisek June 22, 2026

June 22, 2026

Doctoral and postdoctoral studies in the neuroscience of dynamic action planning and motor control Department of Neuroscience, University of Montreal Applications are invited for doctoral and postdoctoral studies in systems neuroscience in the laboratories of Andrea Green and Paul Cisek. Successful applicants will join a multidisciplinary research group studying how the primate brain controls real-time, natural behavior in dynamic environments. Different projects address how we specify and plan potential actions such as reaching under changing conditions as we move through our environment, decide between actions even during ongoing behavior, control and learn to execute movements in different behavioral contexts (e.g., body stationary vs. in motion) and integrate multisensory cues to estimate and keep track of our motion through space. Research in our group involves single- and multi-electrode neural recording experiments in non-human primates, human behavioral studies using techniques such as transcranial magnetic stimulation and galvanic vestibular stimulation, and computational modeling of the nervous system. New collaborative projects will combine use of sophisticated spatial motion systems and virtual reality environments to study naturalistic behavior in both humans and non-human primates and develop computational models of real-time action selection, planning and control. For more information, see: https://neurosciences.umontreal.ca/recherche/les-chercheurs/andrea-green/ and https://cisek.org/pavel/ Multiple positions are available. All students with a strong background in biological sciences, engineering, mathematics, computer science, physics or psychology and an interest in system-level study of the brain are encouraged to apply. Prior experience in neurophysiology, behavioral neuroscience and/or computational modeling of neural systems is highly desirable. Depending on the applicant's qualifications and interests, they will help to design and conduct behavioral and neurophysiological experiments, analyze data, develop theoretical models of neural systems, prepare manuscripts for publication, and participate in international conferences. Interested candidates are asked to send a curriculum vita, copies of academic transcripts, a statement of research interests and the names and contact information for two references, to Andrea Green (andrea.green(a)umontreal.ca<mailto:andrea.green@umontreal.ca>) and Paul Cisek (paul.cisek(a)umontreal.ca<mailto:paul.cisek@umontreal.ca>). Applications will be accepted until the positions are filled, but preference will be given to applications received before July 31st, 2026. Paul Cisek, PhD Département de neurosciences Université de Montréal Physical: 2960 chemin de la tour, local 4117 Montréal, QC H3T 1J4 CANADA Mailing: CP 6128 Succursale centre-ville, Montréal, QC H3C 3J7 CANADA e-mail: paul.cisek(a)umontreal.ca<mailto:paul.cisek@umontreal.ca> Web: www.cisek.org/pavel<http://www.cisek.org/pavel>

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Andrew Barto speaking in Developing Minds Lecture Series on June 25
by Jochen Triesch June 22, 2026

June 22, 2026

Dear colleagues, On June 25, the Developing Minds global online lecture series is proud to host Andrew Barto, Prof. Emeritus of Univ. of Massachusetts Amherst, USA, speaking on „Rediscovering Reinforcement Learning“. His talk will take place at: 10:00 am EDT (Eastern Daylight Time, USA) 14:00 UTC (Universal Coordinated Time) 16:00 CEST (Central European Summer Time) 23:00 JST (Japan Standard Time). The talk will be hosted via zoom: https://uni-frankfurt.zoom-x.de/j/62410045708?pwd=EmEDiJtB0NZ0XPbSBngt6sbx2… Meeting-ID: 624 1004 5708 Kenncode: 883974 Abstract: The idea of reinforcement learning (RL) as a key principle of animal learning has been around at least since Edward Thorndike proposed the “Law of Effect” in 1898. Machine implementation of this principle began with electro-mechanical machines in the 1930s, and the earliest idea for computer implementation was probably Turing’s 1948 proposal of a computer implementation of a “pleasure-pain system”. In this talk I review what has followed Turing’s unimplemented proposal, starting with the first computer experiments in 1954, up to what we now know as modern computational RL. Short Bio: Andrew Barto is Professor Emeritus of Computer Science, University of Massachusetts Amherst, having retired in 2012. He served as Chair of the UMass Department of Computer Science from 2007 to 2011. He received a B.S. with distinction in mathematics from the University of Michigan in 1970, and a Ph.D. in Computer Science in 1975, also from the University of Michigan. He joined the Computer Science Department of the University of Massachusetts Amherst in 1977. Before retiring he co-directed the Autonomous Learning Laboratory at UMass Amherst, which produced many notable machine learning researchers. Professor Barto is a Fellow of the American Association for the Advancement of Science (AAAS) and a Fellow and Life Member of the IEEE. He received the 2004 IEEE Neural Network Society Pioneer Award for contributions to the field of reinforcement learning, the IJCAI-17 Award for Research Excellence for groundbreaking and impactful research in both the theory and application of reinforcement learning, and a University of Massachusetts Neurosciences Lifetime Achievement Award in 2019. Most recently, he and his former doctoral student, Richard Sutton, were co-recipients of the 2024 Association for Computing Machinery’s A.M. Turing Award for developing the conceptual and algorithmic foundations of reinforcement learning, and he and Sutton received the 2026 IEEE Frank Rosenblatt Award for contributions to reinforcement learning and artificial intelligence. He has published over one hundred papers or chapters in journals, books, and conference and workshop proceedings. He is co-author with Sutton of "Reinforcement Learning: An Introduction," MIT Press, 1998. A much expanded second edition was published in 2018. The talk will be recorded and made available for later viewing. For more information on the talk series and recordings of previous events, please visit: https://sites.google.com/view/developing-minds-series/home Best regards, Jochen Triesch -- Prof. Dr. Jochen Triesch Johanna Quandt Chair for Theoretical Life Sciences Frankfurt Institute for Advanced Studies and Goethe University Frankfurt Recent publications: https://www.nature.com/articles/s41467-025-64234-z https://ieeexplore.ieee.org/abstract/document/11204381?casa_token=RBlsm2RTa…

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Funded postdoctoral position in non-human primate electrophysiology in the Michaels Lab
by Jonathan Michaels June 21, 2026

June 21, 2026

Hi all, The Neural Control & Computation Lab at York University in Toronto, Canada, is recruiting a Postdoctoral Fellow. Under the direction of Jonathan Michaels, Ph.D., the fellow will investigate the neural basis of learning, flexible neural computation, and skilled movement control using large-scale electrophysiology from single-neuron populations in non-human primates, including high-density Neuropixels recordings and our recently developed capability for wireless, chronic Neuropixels recordings during naturalistic behavior. The fellow will be encouraged to develop an independent line of research within these themes. The fellow will join an exceptional and fast-growing neuroscience community. The lab is housed in York’s brand new, state-of-the-art Neuroscience Facility, which includes lab and office space for multiple neuroscience research labs and access to shared infrastructure such as MRI and CT. York is home to a collaborative community spanning the Centre for Integrative and Applied Neuroscience (CIAN), the Centre for Vision Research (CVR), and the Connected Minds (Neural and Machine Systems for a Healthy, Just Society) initiative. Toronto – Canada’s largest and most diverse city – offers a dense concentration of neuroscience research and an incredible culture and environment. This is a two-year funded position, with the potential for extension, offering a competitive salary (starting at $65k/year), benefits, and a negotiable start date (earliest September 2026). Visa and moving support are provided for international applicants. Applicants should hold a Ph.D. in Neuroscience or a closely related discipline. Favorable consideration will be given to candidates with expertise or substantial interest in one or more of the following: non-human primate electrophysiology, large-scale neural data analysis, computational modeling of neural circuits or motor control, and a strong record of research productivity. To apply, please email the following to Dr. Michaels: a cover letter describing your research experience and interests and how they align with the lab, a CV, one to two representative publications or preprints, and the names and contact information of two references. Review of applications will begin immediately and continue until the position is filled. https://www.ncclab.ca/join-the-lab (link to job ad and more info) Best, Jonathan __________________________________ Jonathan A. Michaels, Ph.D. Assistant Professor Neural Control & Computation Lab School of Kinesiology & Health Science York University

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