October 2025 - Comp-neuro - lists.cnsorg.org

Meetings - 2026 Nengo Summer School Call For Applications

by Madeleine Bartlett

Dear colleagues, All details about this school can be found online at https://www.nengo.ai/summer-school The Centre for Theoretical Neuroscience at the University of Waterloo is excited to announce our 11th annual Nengo summer school on large-scale brain modelling and neuromorphic computing. This two-week school will teach participants to use the Nengo simulation package to build state-of-the-art cognitive and neural models to run both in simulation and on neuromorphic hardware. Summer school participants will be given on-site access to neuromorphic hardware and will learn to run high-level applications using Nengo! More generally, Nengo provides users with a versatile and powerful environment for designing cognitive and neural systems and has been used to build what is currently the world's largest functional brain model, Spaun, which includes spiking deep learning, reinforcement learning, adaptive motor control, and cognitive control networks. For a look at the last in-person summer school, check out this short video: https://youtu.be/hHwIryt053M?si=N70eVlC3Sm_2sDy5 We welcome applications from all interested graduate students, postdocs, professors, and industry professionals with a relevant background. ***Application Deadline: December 22nd, 2026*** Format: A combination of tutorials and project-based work. Participants are encouraged to bring their own ideas for projects, which may focus on testing hypotheses, creating models to account for neural or cognitive data, implementing specific behavioural functions with neurons, expanding past models, or providing a proof-of-concept of various neural mechanisms. Hands-on tutorials, individual or group projects, and talks from invited faculty members will make up the bulk of day-to-day activities. A project demonstration event will be held on the last day of the school, with prizes for strong projects! Participants will have the opportunity to learn how to: * interface Nengo with various kinds of neuromorphic hardware (e.g. BrainDrop, SpiNNaker) * build perceptual, motor, and sophisticated cognitive models using spiking neurons * build models to account for anatomical, electrophysiological, cognitive, and behavioural data * use a variety of single cell models within a large-scale model  * integrate machine learning methods into biologically oriented models * interface Nengo with cameras and robotic systems * implement modern nonlinear control methods in neural models * neurally implement vector symbolic architecture algorithms * and much more… Date and Location: May 31st to June 12th, 2026 at the University of Waterloo, Ontario, Canada. Applications: Please visit http://www.nengo.ai/summer-school, where you can find more information regarding costs, travel, lodging, along with an application form listing required materials. If you have any questions about the school or the application process, please contact: Madeleine Bartlett: madeleine.bartlett(a)uwaterloo.ca<mailto:madeleine.bartlett@uwaterloo.ca> Kathryn Simone: kpsimone(a)uwaterloo.ca<mailto:kpsimone@uwaterloo.ca> The school is partly supported by ABR, Inc. We look forward to hearing from you! Maddy she/her Postdoctoral Fellow University of Waterloo email: m2bartle(a)uwaterloo.ca

Oct. 27, 2025

Ph.D. position in event-based computing / spiking networks at Champalimaud, Lisbon

by Christian Machens

PhD position in computational neuroscience (event-based computing / spiking networks) As part of a Marie-Curie Doctoral Network (ELEVATE <https://www.elevate-dn.eu/index.php/about/>), we are offering a PhD student position. The proposed project sits a the interface of computational neuroscience and neuromorphic computing, and is embedded within a strong network of European academic and industrial partners. ENVIRONMENT: The student will be part of the Theoretical Neuroscience lab <https://www.machenslab.org/>, led by Christian Machens, which is hosted at the Champalimaud Centre for the Unknown in Lisbon, Portugal. The Champalimaud Foundation <https://www.fchampalimaud.org/> is a private, non-profit institute with a vibrant and highly international academic community. Many groups work in the field of systems and computational neuroscience, <https://www.fchampalimaud.org/champalimaud-research> providing a stimulating and exciting work environment. The student will also interact with the training network ELEVATE <https://www.elevate-dn.eu/index.php/about/> and spend several months at Rodolphe Sepulchre <https://sites.google.com/site/rsepulchre/>‘s lab at KU Leuven, Belgium. PROJECT: Across the animal world, biological networks are made up of different types of neurons. The most prominent division is that between excitatory (E) and inhibitory (I) neurons. However, modern AI system as well as most neuromorphic systems ignore this division and assume only one type of neuron. In this project, we will study the specific functional or structural qualities arising from a division into E and I neurons, and work out any potential benefits. One key design feature of networks with E and I neurons is that they are composed of intrinsically unstable subsystems, namely recurrently connected E neurons, that are controlled and stabilized by other subsystems, namely I neurons. The benefits of designing and controlling intrinsically unstable systems have long been known to engineers in other context, e.g., the desing of modern fighter aircraft. The goal of this project is to use some of these engineering insights in order to investigate how the interplay of excitation and inhibition can be utilized to perform specific computations. Since real neurons communicate with discrete events (spikes), a key aim is to work out the distinct computational roles of inhibitory and excitatory spikes, and apply the concepts to a few example systems. TASKS: * Study the relevant background literature from both engineering and neuroscience fields. Based on geometric and analytical insights from the framework of ‘spike coding networks’, develop analytical or geometric methods to study the roles of excitatory and inhibitory spikes. Develop a few canonical systems and use numerical simulations to demonstrate the role of excitatory and inhibitory populations in computational tasks. * Publish research articles, regular participation in top international conferences to present your work. * Complete an internship at KU Leuven with Prof. Rodolphe Sepulchre * Participate in yearly retreats organized by the doctoral network participants * Support the dissemination of software tools and concepts. SALARY AND CONDITIONS: The salary and benefits will follow standard EU rules. PhD students will receive their degree from the NOVA University of Lisbon. APPLICATION: We are looking for a candidate with strong quantitative skills (e.g., degree in physics, computer science, engineering, etc.) and curiosity about how the brain works. Interested candidates should submit a detailed CV, a cover letter explaining their interest in the position (1 page), a transcript for their BSc and Msc, and the contact information of 2 references to christian.machens(a)neuro.fchampalimaud.org. The application process will remain open until the position is filled. We strive to build a diverse work environment and encourage applications from all qualified individuals irrespective of their gender, age, cultural background, and disability status. Only candidates shortlisted for this position will be contacted for an interview. STARTING DATE: We anticipate a start in the year 2026. The earliest starting date is January 1st, 2026.

Oct. 27, 2025

World wide VVTNS series: Sixth season opening lecture, Wednesday, October 29, 2025, at 11:00 am EDT - Andrew Barto

by David Hansel

*Important:* The seminar is at 11 am *EDT* Europe moved to Winter Time on Sunday, October 26, 2025 US will move to Winter Time next Sunday, November 2 This week 11 am EDT= 4pm CET Check the time where you are [image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the sixth season opening lecture of the online VVTNS series Andrew Barto University of Massachusetts Amherst on the topic of What is So Interesting About Reinforcement Learning? The lecture will be held on zoom on October 29, 2025, at *11:00 am EDT * > To receive the link: https://www.wwtns.online/register-page > > *Abstract: *This talk aims to answer these questions along four dimensions. First is history. RL was the basis of AI long before the term AI was introduced in 1956. The first machine learning (ML) systems were based on RL even before digital computers existed. Despite notable early successes of ML based on RL, RL essentially disappeared from ML until relatively recently. A second reason for renewed interest in RL is the clarification of some misunderstandings that have been prevalent in the ML community. A third, and most important, reason for this resurgence is that new, or rediscovered, algorithms and connections to well developed mathematical and engineering methods have been worked out. Finally, a fourth reason for the renewed interest in RL is its strong links to animal reward systems, in particular, to the role that dopamine plays in motivation and learning. *About VVTNS : Launched as the World Wide Theoretical Neuroscience Seminar (WWTNS) in November 2020 and renamed in homage to Carl van Vreeswijk in Memoriam (April 20, 2022), Speakers have the occasion to talk about theoretical aspects of their work which cannot be discussed in a setting where the majority of the audience consists of experimentalists. The seminars, **held on Wednesdays at 11 am ET,** are 45-50 min long followed by a discussion. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.* ᐧ

Oct. 26, 2025

IMPRS for Language Sciences PhD Fellowships 2026

by Lam, Kevin

** IMPRS for Language Sciences PhD Fellowships 2026 ** The International Max Planck Research School (IMPRS) for Language Sciences is offering two fully-funded PhD Fellowship for four years (2026-2030) with a preferred start-date in September or October, 2026. The goal of the scheme is to enable young researchers to pursue interdisciplinary research projects in the language sciences, supervised by leading scientists at the Max Planck Institute for Psycholinguistics and its partner institutes at the Radboud University -- the Centre for Language Studies and the Donders Institute for Brain, Cognition and Behaviour. https://www.mpi.nl/ | https://www.ru.nl/cls | https://www.ru.nl/donders Find out more about the Fellowships and read first-hand accounts by our members: https://www.mpi.nl/imprs-phd-fellowships-2026 | https://www.mpi.nl/imprs The application deadline is 5 January, 2026. Thanks in advance. Best wishes from Nijmegen, Dr. Kevin Lam, Graduate School Coordinator http://www.mpi.nl/imprs | https://www.mpi.nl/people/lam-kevin

Oct. 23, 2025

Open PhD and Postdoc position at El-Boustani Lab (University of Geneva, Switzerland)

by sami_elboustani＠msn.com

The El-Boustani Lab at the University of Geneva (Switzerland) is looking for a highly motivated PhD student and Postdoctoral fellow to research the plasticity mechanisms underlying the learning of goal-directed sensorimotor associations in mice. This project involves whole-brain mappings, two-photon calcium imaging of neuronal populations, as well as dendritic spine imaging in mice during the acquisition of perceptual decision-making tasks. Genetically encoded tools will be used to dissect the circuits that contribute to the learning of these tasks, and state-of-the-art behavioral modeling will help infer the timescale and nature of synaptic plasticity. Successful applicant will contribute to a research program focused on understanding how changes in specific sensorimotor synapses underpin the acquisition of new associations. We welcome applicants with diverse quantitative backgrounds, including but not limited to neuroscience, mathematics, physics, and engineering. We are especially interested in applicants with excellent programming skills (e.g., MATLAB, Python), experience with mouse behavior and imaging techniques in vivo. Switzerland offers a vibrant neuroscience community with outstanding research conditions and attractive salaries. Candidates should send their CV, at least two references and a brief cover letter describing their previous work and future goals to Sami El-Boustani: sami.el-boustani(a)unige.ch. Please visit http://elboustani-lab.org/ for more details.

Oct. 21, 2025

Doctoral studies in Computational/Theoretical Neuroscience at NYU

by Eero Simoncelli

New York University is home to a thriving interdisciplinary community of researchers using computational and theoretical approaches in neuroscience. We are interested in exceptional PhD candidates with strong quantitative training (e.g., physics, mathematics, engineering) coupled with a clear interest in scientific study of the brain. A listing of faculty, sorted by their primary departmental affiliation, is given below. Doctoral programs are flexible, allowing students to pursue research across departmental boundaries. Nevertheless, admissions are handled separately by each department, and students interested in pursuing graduate studies should submit an application to the program that best fits their goals and interests. Center for Neural Science (CNS), Graduate School of Arts & Sciences (deadline: 1 December) [https://as.nyu.edu/cns/DoctoralProgram.html https://neuroscience.nyu.edu/program.html] * Andre A. Fenton - Molecular, neural, behavioral, and computational aspects of memory. * David Heeger (also in Psychology) - Computational neuroscience, vision, attention. * Roozbeh Kiani - Vision and decision-making. * Wei Ji Ma (also in Psychology) - Perception, working memory, and decision-making. * Tony Movshon - Vision and visual development. * Alex Reyes - Functional interactions of neurons in a network. * John Rinzel (also in Mathematics) - Biophysical mechanisms and theory of neural computation. * Cristina Savin (also in the Center for Data Science) - Computational models of learning and memory, machine learning. * Robert Shapley - Visual physiology and perception. * Eero Simoncelli (also in the FlatIron Institute) - Computational vision and audition. * Xiao-Jing Wang - Computational neuroscience, decision-making and working memory, neural circuits. * Alex Williams (also in the FlatIron Institute) - Statistical analysis of neural data. Neuroscience Institute, School of Medicine (deadline: 1 December) [https://med.nyu.edu/departments-institutes/neuroscience/ https://neuroscience.nyu.edu/program.html] * Gyorgy Buzsaki - Rhythms in neural networks. * Dmitri Chklovskii (also in the FlatIron Institute) - Neural computation and connectomics. * Paul W. Glimcher - Decision-making in humans and animals. Neuroeconomics. * Biyu He - Large-scale brain dynamics underlying human cognition. * Dima Rinberg - Olfaction, sensory information processing, perception. * Shy Shoham - Methods for controlling, imaging, and analyzing neural systems. * Mario Svirsky - Auditory neural prostheses; experimental/computational studies of speech production/perception. Psychology, Cognition & Perception program (deadline: 1 December) [http://as.nyu.edu/psychology/graduate/phd-cognition-perception.html] * Todd Gureckis - Memory, learning, and decision processes. * Michael Landy - Computational approaches to vision. * Laurence Maloney - Mathematical approaches to psychology and neuroscience. * Marcelo Mattar - Learning and planning in the brain/mind. * Denis Pelli - Visual object recognition. * Jonathan Winawer - Visual perception and memory. Data Science (deadline: 4 December) [https://cds.nyu.edu/phd-program/] * Joan Bruna (also in Computer Science) - Machine learning, signal/image processing. * Kyungyun Cho (also in Computer Science) - Machine learning, natural language processing. * Carlos Fernandez-Granda (also in Mathematics) - Optimization methods for medical imaging, neuroscience, computer vision. * Brenden Lake (also in Psychology) - Computational modeling of cognition, deep learning. * Grace Lindsay (also in Psychology) - Machine learning models of the brain/mind. * Mengye Ren (also in Computer Science) - Brain and cognitively inspired representation learning. Mathematics (deadline: 18 December) [https://gsas.nyu.edu/admissions/arc/programs/mathematics.html] * Aaditya Rangan - Computational neurobiology, numerical analysis. * Charles Peskin - Mathematical biology. * Daniel Tranchina - Information processing in the retina. * Lai-Sang Young - Dynamical systems, statistical physics, computational modeling and theoretical neuroscience. Physics (deadline: 30 December) [https://as.nyu.edu/physics/programs/graduate.html] * Marc Gershow - Perception, decision-making, and learning in neural circuits. * Stefano Martiniani - Fundamental principles governing neural systems. Computer Science (deadline: 12 December) [http://www.cs.nyu.edu/home/phd/] * Davi Geiger - Computational vision and learning. * Yann LeCun - Machine learning, computer vision, robotics, computational neuroscience. Economics (deadline: 18 December) [https://as.nyu.edu/econ/graduate/phd.html] * Andrew Caplin - Economic theory, neurobiology of decision. * Andrew Schotter - Experimental economics, game theory, neurobiology of decision.

Oct. 20, 2025

PhD positions in Multi-level modelling of neuromodulation and lesioning

by Nada Yousif

Applications are invited from PhD studentship candidates to work on multi-level modelling of neuromodulation and lesioning at the Biocomputation Research Group, University of Hertfordshire, UK. The projects are focussed on understanding the human nervous system in health and disease using computational modelling of neurons and networks. More details can be found at: https://tinyurl.com/2xe2sxva Informal enquiries to Dr Nada Yousif (n.yousif(a)herts.ac.uk) Application deadline: 14 November 2025 Studentship: approximately £20,700 per annum bursary plus payment of the student fees. Applicants from inside and outside the UK are eligible. The Centre for AI and Robotics Research and the University of Hertfordshire provide a very stimulating environment, offering a large Doctoral School with many specialised and interdisciplinary seminars as well as general training and researcher development opportunities. The University is situated in Hatfield, in the green belt just north of London. Research in Computer Science at the University of Hertfordshire has been recognised as excellent in REF 2021, with 90% of the research submitted and all the research impact rated as internationally excellent or world leading. Information on the application procedure and an application form can be found at: https://tinyurl.com/3k8j9c3m

Oct. 19, 2025

Computational Psychology position at Tufts University

by Erin Munro Krull

Oct. 19, 2025

PhD Studentships in Computational Neuroscience at the University of Hertfordshire, UK

by Volker Steuber

PhD Studentship in Computational Neuroscience Biocomputation Research Group Centre for AI and Robotics Research School of Physics, Engineering and Computer Science University of Hertfordshire, UK Informal enquiries: Prof Volker Steuber, UH (v.steuber(a)herts.ac.uk) Dr Arnd Roth, UCL (arnd.roth(a)ucl.ac.uk) Application deadline: 14 November 2025 Studentship: approximately £20,700 per annum bursary plus payment of the student fees. Applicants from inside and outside the UK are eligible. Proposed Project: Reinforcement Learning and Microzones in the Cerebellum The crystalline structure of the cerebellar cortex has inspired the development of theories and computational models of learning in the cerebellum. In these computational models, learning is typically based on long-term depression (LTD) between parallel fibres and Purkinje cells in cerebellar cortex. More recently, however, plasticity has been shown to be present at different types of cerebellar synapses, and recent observations of reward signals conveyed by both mossy fibres and climbing fibres to the cerebellar cortex indicate that the roles of the instructive signals for cerebellar plasticity are more complex than assumed by classic theories. The presence of reward signals suggests that the cerebellum may be involved in reinforcement learning, by predicting the consequences of different actions. A further level of complexity arises from the existence of alternating cerebellar microzones that have been shown to contribute in different ways to cerebellar learning. The proposed PhD project will extend a previously developed detailed network model of the cerebellum. Simulations of the network model will be used to investigate the implications of reward signals and microzones for cerebellar learning. The work will contribute to a better understanding of learning in the cerebellum with potential applications in machine learning and neurorobotics. Applicants should have a keen interest in computational neuroscience and an excellent first degree or MSc in computer science, neuroscience, AI, machine learning, physics, maths, biology, medicine or a related discipline. The project involves a collaboration between the Biocomputation Research Group in the Centre for AI and Robotics Research at the University of Hertfordshire (Volker Steuber) and the Wolfson Institute for Biomedical Research at UCL (Arnd Roth) and will require regular visits to London. The Centre for AI and Robotics Research and the University of Hertfordshire provide a very stimulating environment, offering a large Doctoral School with many specialised and interdisciplinary seminars as well as general training and researcher development opportunities. The University is situated in Hatfield, in the green belt just north of London. Research in Computer Science at the University of Hertfordshire has been recognised as excellent in REF 2021, with 90% of the research submitted and all of the research impact rated as internationally excellent or world leading. Information on the application procedure and an application form can be found at: https://www.herts.ac.uk/study/schools-of-study/physics-engineering-and-comp… Volker Steuber Professor of Computational Neuroscience Biocomputation Research Group School of Physics, Engineering and Computer Science University of Hertfordshire College Lane, Hatfield, AL10 9AB, UK biocomputation.herts.ac.uk<http://biocomputation.herts.ac.uk>

Oct. 17, 2025

Postdoc position at U Oregon

by James Murray

A postdoc position is available with Prof. James Murray (murraylab.uoregon.edu) at the University of Oregon’s NeuroAI Center (ion.uoregon.edu/neuroai) Application link: https://academicjobsonline.org/ajo/jobs/30896 Position Summary -- In our research, our group seeks to uncover the principles of how the brain performs computations and implements learning related to motor control and sensory perception. Some of the scientific questions that motivate our work are - How do different regions of the brain interact to learn new motor skills? - What are the principles that enable brains and artificial agents to learn efficiently from experience while minimizing forgetting? - How can models of learning and motor control be synthesized across different levels of description? Our research group aims at building mechanistic models of brain function grounded in a combination of theoretical approaches, neural network-based simulations, and machine-learning analysis of experimental data. The candidate will have the opportunity to collaborate with a large network of experimental collaborators at University of Oregon and at other institutions with expertise in sensory processing (visual, auditory, and olfactory), motor control, naturalistic behavior, neural engineering, and brain-computer interfaces. While previous experience in computational neuroscience and machine learning are welcome, applicants from other quantitative fields (e.g. math, physics, statistics, computer science) who are eager to learn about neuroscience are encouraged to apply as well. The Oregon NeuroAI Center is part of the Institute of Neuroscience at the University of Oregon (ion.uoregon.edu) a major hub for systems and theoretical neuroscience research. The University of Oregon is located in Eugene, Oregon, a vibrant college town in the Pacific Northwest with ample cultural offerings and phenomenal access to outdoor recreation. We offer a competitive salary commensurate with the candidate’s experience, and remote work arrangements may be considered. Required Qualifications -- Successful candidates will have a PhD in a quantitative field, including physics, neuroscience, mathematics, statistics, computer science, or related fields. Applicants should have a strong quantitative background including at least some coding experience. Application -- Application link: https://academicjobsonline.org/ajo/jobs/30896 Application reviews will start on December 1st and will continue until the position is filled. Please send inquiries to jmurray9(a)uoregon.edu. Applications should include a CV, two-page statement of research interests, and contact information for three letters of reference.

Oct. 15, 2025