- Comp-neuro - lists.cnsorg.org

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 Pearson - Development, structure and function of sensory systems. * 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. * Zhe Chen - Memory and learning, cognitive flexibility and decision making, social behaviors, and pain. * 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: 3 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. 13, 2026

COSYNE 2027: Abstract submission closes soon

by Tomas Hromadka

==================================================== Computational and Systems Neuroscience 2027 (Cosyne) MAIN MEETING & WORKSHOPS 11 - 16 March 2027 Montreal, Canada www.cosyne.org ==================================================== IMPORTANT DATES Abstract submission is now open. Abstract submission deadline: 18 October 2026 Workshop proposal submission is now open. Workshop proposal submission deadline: 01 November 2026 UNDERGRADUATE travel grant applications are now open. UNDERGRADUATE travel grant submission deadline: 30 October 2026 ---------------------------------------------------- COSYNE MEETING & WORKSHOPS ---------------------------------------------------- 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. 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. 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 TRAVEL GRANTS ----------------------------------------------------- The COSYNE community is committed to bringing talented scientists together at our annual meeting, regardless of their ability to afford travel. Thus, a number of travel grants will be awarded to students, postdocs, and PIs for travel to the COSYNE meeting. We currently offer five travel grant programs: Childcare, Presenters, New Attendees, Mentorship, and Undergraduate Travel Grants, see Cosyne.org -> Attend -> Travel Grants for details. Applicants may apply for more than one grant program, but no applicant will receive more than one award. You may apply for a travel grant before receiving notification about the outcome of your submission. You may also apply if you are not submitting anything to the Main Meeting but still wish to attend Cosyne 2027. ---------------------------------------------------- COSYNE 2027 ---------------------------------------------------- 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) Social Media Chair: Shervin Safavi (TU Dresden) Poster Design: Maja Bialon PROGRAM COMMITTEE Annegret Falkner (Princeton) Guillaume Lajoie (MILA/U Montreal) Thomas Akam (Oxford) Mikio Aoi (UCSD) Shahab Bakhtiari (U Montreal) Arkarup Banerjee (CSHL) Joao Barbosa Pouya Bashivan (McGill) Marcus Benna (UCSD) Colin Bredenberg (U Oregon) Fanny Cazettes (Aix-Marseille U) Angus Chadwick (U Edinburgh) Vincent Costa (Emory) Ben Cowley (CSHL) Emily Dennis (Janelia) Sridhar Devarajan (IISc) Celine Drieu (JHU) Eva Dyer (UPenn) Becket Ebitz (U Montreal) Noemi Elteto (Google) Rainer Engelken (UIUC) Arseny Finkelstein (Tel Aviv University) Juan Gallego (Champalimaud) Erin Grant (U Alberta) Christine Grienberger (Brandeis) Laura Grima (Janelia) Bilal Haider (Georgia Tech) Yu Hu (ION, CAS Shanghai) Michele Insanally (U Pittsburgh) Kishore Kuchibhotla (JHU) Nina Kudryashova (U Edinburgh) Helena Liu (U Toronto) Laureline Logiaco (CU Anschutz) Thomas Zhihao Luo (U Utah) Paul Masset (McGill) Francesca Mastrogiuseppe (Champalimaud) Alexander Mathis (EPFL) Luca Mazzucato (U Oregon) Dan McNamee (Champalimaud) Cory Miller (UCSD) Wilten Nicola (U Calgary) Ramon Nogueira Manas (U Chicago) Gouki Okazawa (ION, CAS Shanghai) Agostina Palmigiano (UCL) Matt Perich (U Montreal) Rui Ponte Costa (Oxford) Lorenzo Posani (Paris Brain Institute) Dean Pospisil (UIUC) Isabeau Premont-Schwarz (U Laval) Carolina Rezaval (U Birmingham) Shreya Saxena (Yale) Evan Schaffer (Sinai) Heike Stein Weinan Sun (Cornell) Roxana Zeraati Chris Zimmerman (U Utah) Petr Znamenskiy (Crick) 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.

Oct. 12, 2026

University College London NeuroAI Annual Conference - 11th Nov

by Padraig Gleeson

Dear Colleagues, The 7th Annual UCL NeuroAI Conference will take place on Wednesday 11 November 2026 at the Kennedy Lecture Theatre, UCL Great Ormond Street Institute of Child Health, London. The event will feature leading speakers at the cutting edge of machine learning and neuroscience. The UCL NeuroAI initiative aims to be a central hub where researchers working in neuroscience, AI, machine learning, and related fields can interact and stay updated on the latest advancements in these intersecting areas. Our annual conference is an important opportunity for these communities to gather, make new connections, and benefit from insights in one another’s fields. *Keynote speakers* We are privileged to have a distinguished line-up of speakers and experts confirmed to date. Wolfgang Maass, Technische Universität Graz Agostina Palmigiano, Gatsby Computational Neuroscience Unit Bernardo Sabatini, Harvard Medical School Nicolas Skatchkovsky, Francis Crick Institute Eleni Vasilaki, University of Sheffield Ellie Pavlik, Brown University *Registration * Registration is required and the conference ticket is £5 but if the cost is a barrier, please email events(a)ucl.ac.uk for a complimentary ticket. Please register here <https://www.bloomsburytheatre.com/event/2026/11/neuroai-conference-2026>. *Poster and talks - Submissions are now open!* This year we will also be accepting abstract submissions for posters, short lightning presentations (3-4 mins), as well as longer submitted talks (15 mins) as part of the event. The deadline to submit your abstract for these is *Friday 16 October at 12pm*. Please remember to book your conference place as well as completing the abstract registration form if you would like to present. Submit your poster or talk abstract now here <https://forms.cloud.microsoft/Pages/ResponsePage.aspx?id=_oivH5ipW0yTySEKEd…>. *Sponsorship* We are immensely grateful for the support from the Sainsbury Wellcome Centre, Callosum Technologies and Google DeepMind. *About UCL NeuroAI* The last decade has seen phenomenal advances in the fields of machine learning (e.g. deep learning, reinforcement learning, and AI). While these changes have already had considerable impact on most areas of science they hold a particular resonance for neuroscience. Crucially, AI shares a common lineage with neuroscience and, fundamentally, machine learning and the brain employ similar computations to process and compress information. For these reasons AI provides a means to emulate neural functions and the circuits supporting them, providing insights to aid our understanding of the brain and cognition. Equally, AI tools provide a means to discover, segment, and track distinct neural and behavioural states, yielding more efficient experiments and accelerating the pace of discovery. In turn, this understanding feeds back into the design of more effective AI architectures and models. Essentially, AI problems posed in neuroscience both require and inspire further advances in AI. UCL NeuroAI has been set up to provide a forum where researchers in these areas can meet, exchange ideas, and move both fields forward. -- ----------------------------------------------------- Padraig Gleeson http://openneuroai.org Room 321, Anatomy Building Department of Neuroscience, Physiology & Pharmacology University College London Gower Street London WC1E 6BT United Kingdom +44 207 679 3214 p.gleeson(a)ucl.ac.uk -----------------------------------------------------

Oct. 12, 2026

Final Call for Papers: ACML 2026 (Encore Track)

by Levin Kuhlmann

ACML 2026 (the 18th Asian Conference on Machine Learning) is being held in Melbourne Australia on 1–4 December, just before NeurIPS in Sydney. The main conference, journal and workshop tracks have closed, but the Encore Track is still accepting submissions. It's a way to present work you've already had published or accepted at a leading venue (including NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, AAAI, JMLR, IEEE TPAMI) since 1 June 2025, through an encore talk in a topic-aligned session. Submission is lightweight: title, abstract, author details, PDF and publication URL (or evidence of acceptance if not yet published). Deadline: 18 October 2026, 11:59 PM AoE For more details visit https://www.acml-conf.org/2026/calls/papers/#encore-track If you have any questions, please contact Levin Kuhlmann ( levin.kuhlmann(a)monash.edu) Kind regards, Levin Kuhlmann Encore Track Chair, ACML 2026

Oct. 12, 2026

Two Postdoctoral Positions in Computational Neuroscience - Ruhr University Bochum, Germany

by Sen Cheng

Dear colleagues, We are inviting applications for *two postdoctoral positions in Computational Neuroscience* within the Collaborative Research Center *SFB 1280 "Extinction Learning"* at Ruhr University Bochum, Germany. SFB 1280 is an interdisciplinary research consortium investigating the neural, cognitive, and behavioral mechanisms underlying extinction learning. It brings together researchers from neuroscience, psychology, medicine, and computational modeling. The two positions are based in the Computational Neuroscience group and focus on different aspects of learning and memory: *1. Project Z02 – Computational Modeling of Learning Dynamics* Investigate learning dynamics across individuals, species, learning phases, and experimental paradigms. The successful candidate will develop computational models and analysis methods to characterize learning processes using behavioral, neural, and psychophysiological data collected within SFB 1280. The project involves close interdisciplinary collaboration with experimental researchers. *Application deadline: November 2, 2026* https://jobs.ruhr-uni-bochum.de/jobposting/ccfb73ccd824632cad67e3960105dc6e… *2. Project A14 – Spiking Neural Network Models of Hippocampal Memory Processes* Develop quantitative spiking neural network models to investigate the neural mechanisms of episodic memory and spatial navigation. The project focuses on how hippocampal sequences during sharp-wave ripples are generated and shaped by experience and neuromodulation to support memory consolidation. Computational models will be developed in close collaboration with experimental neuroscientists and validated against electrophysiological and behavioral data from rodents. *Application deadline: October 19, 2026 (will be extended to **November 2, 2026**)* https://jobs.ruhr-uni-bochum.de/jobposting/1a216242df7d11a68fb762a850c9d76a… *General information:* - *Starting date:* As soon as possible - *Duration:* Until June 30, 2029 - *Salary:* TV-L E13, 100% position - *Location:* Ruhr University Bochum, Germany We welcome applications from motivated researchers with a PhD in computational neuroscience, neuroscience, physics, computer science, mathematics, or related disciplines. Strong quantitative and programming skills, experience in computational modeling, and enthusiasm for interdisciplinary collaboration are particularly valued. For details about the positions, qualifications, and application procedures, please consult the respective job advertisements. We would appreciate it if you could forward this announcement to interested candidates. Best regards, Sen Cheng. --- Prof. Dr. Sen Cheng Ruhr-Universität Bochum Fakultät für Informatik Institut für Neuroinformatik Universitätsstr. 150 Postfach 110 44801 Bochum Büro: NB 3/33 | +49-234- 32 29486 <0234%203229486> | FAX: +49-234- 32 14210 <0234%203214210> sen.cheng(a)rub.de | rub.de/cns | for2812.rub.de

Oct. 10, 2026

Three PhD Positions in Computational Neuroscience and Episodic Memory – Ruhr University Bochum

by Sen Cheng

Dear colleagues, We are inviting applications for *three PhD positions* within the newly established Collaborative Research Center *CRC 1844 "Episodic Memory"* at Ruhr University Bochum, Germany, pending final funding approval. The CRC brings together researchers from computational neuroscience, psychology, neuroscience, and philosophy to investigate how episodic memories are encoded, reconstructed, and used in cognition and behavior. The three positions focus on different aspects of episodic memory research: *1. Project A07 – Computational Modeling of Episodic Memory Development* Develop computational models to investigate how episodic memory develops in children, using modern artificial neural networks and deep reinforcement learning. The project involves close collaboration with experimental researchers in psychology and neuroscience. https://jobs.ruhr-uni-bochum.de/jobposting/535055f07b13f29c9ad9ecf2809e56ae… *2. Project A10 – Episodic Memory and Spatial Navigation* Investigate the functional role of episodic memory in spatial navigation through computational modeling, including artificial neural networks and deep reinforcement learning. The project combines theoretical modeling with simulations of experimental tasks. https://jobs.ruhr-uni-bochum.de/jobposting/bb916076d7b6b55ac97d7e5b3a9872a0… *3. Project Z02 – Gamified Episodic Memory Research and Citizen Science* Investigate episodic memory using behavioral data collected through a digital serious game developed in collaboration with the Cologne Game Lab. The project focuses on computational and statistical analysis of large-scale memory data, connecting fundamental memory research with citizen science and public engagement. https://jobs.ruhr-uni-bochum.de/jobposting/fec7155cf49f90ef54729f1412129f5b… *General information:* - *Application deadline:* November 2, 2026 - *Starting date:* January 1, 2027 (subject to funding approval) - *Duration:* Until December 31, 2030 - *Salary:* TV-L E13, 75% position - *Location:* Ruhr University Bochum, Germany We welcome applications from motivated candidates with a Master's degree in computational neuroscience, computer science, physics, mathematics, or related disciplines. Strong programming and quantitative skills, an interest in memory research, and enthusiasm for interdisciplinary collaboration are particularly valued. For details about the positions, qualifications, and application procedures, please consult the respective job advertisements. We would appreciate it if you could forward this announcement to interested candidates. Best regards, Sen Cheng. --- Prof. Dr. Sen Cheng Ruhr-Universität Bochum Fakultät für Informatik Institut für Neuroinformatik Universitätsstr. 150 Postfach 110 44801 Bochum Büro: NB 3/33 | +49-234- 32 29486 <0234%203229486> | FAX: +49-234- 32 14210 <0234%203214210> sen.cheng(a)rub.de | rub.de/cns | for2812.rub.de

Oct. 10, 2026

Michael H. Goldstein speaking in Developing Minds Lecture Series on October 15

by Jochen Triesch

Dear colleagues, On October 15, the Developing Minds global online lecture series is proud to host Michael H. Goldstein, Cornell University, USA, speaking on „Mechanisms of socially guided vocal learning in human infants and songbirds: Connecting contingency to curiosity-driven learning“. His talk will take place at: 09:00 am EDT (Eastern Daylight Time, USA) 13:00 UTC (Universal Coordinated Time) 15:00 CEST (Central European Summer Time) 22:00 JST (Japan Standard Time) The talk will be hosted via zoom: https://uni-frankfurt.zoom-x.de/j/69608764770?pwd=gOHzVZ5y86Ic0MZFik6khLk0m… Meeting-ID: 696 0876 4770 Code: 401171 Abstract: The ability to learn a vocal repertoire is a rare phenomenon, emerging in only a handful of groups, including humans and songbirds. A key parallel in the vocal development of certain songbirds and human babies is the social function of immature vocalizations. The form and timing of adult-infant interactions facilitate real-time vocal learning and have strong influences on the development of mature birdsong and language. Specifically, contingent responses of adults to the plastic song of birds and the babbling of babies have strong influences on learning. What makes contingency effective? We will examine curiosity-driven learning (CDL) as a framework for a mechanistic understanding of learning from contingent social interactions. In CDL, intrinsic reward is generated by changes in the predictability of social interactions as a function of immature vocal behavior. We will discuss several tests of this idea at the behavioral and neural levels in songbirds and human infants. Taken together, my studies indicate that temporal characteristics of social interaction are rewarding to young songbirds and human infants, and reward pathways may drive learning in social contexts. Short Bio: Michael Goldstein is a Professor of Psychology and a Stephen H. Weiss Presidential Fellow at Cornell University. He received his PhD in developmental psychology and animal behavior from Indiana University. Michael studies the development and evolution of vocal communication and social learning. He takes a comparative approach, investigating vocal communication and social development in human infants and songbirds. His research on the developmental processes by which knowledge of speech and song are acquired has revealed new mechanisms by which the social environment influences the learning of species-typical adaptive skills. By studying social interaction and learning as it occurs in moment-to-moment interactions between infants and social partners, Michael’s research connects our knowledge of social influences on developmental outcomes with specific processes of learning. A major finding from his work is that immature vocal behavior, such as babbling in humans and plastic song in songbirds, has crucial functional significance for learning, but only when studied in a social context. Michael received the David Kucharski Young Investigator Award from the International Society for Developmental Psychobiology and the Distinguished Early Career Contribution Award from the International Society on Infant Studies. His research has been supported by grants from NICHD and NSF. 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…

Oct. 10, 2026

Scientist I, Theory of neural circuits, Allen Institute

by Ulises Pereira Obilinovic

Dear Colleagues, The Allen Institute, Neural Dynamics (a/ND) in Seattle is hiring a Scientist I to work in my team on data-driven theories of how circuit structure shapes neural dynamics and computation. a/ND produces brain-wide connectivity atlases, simultaneous spike recordings from thousands of neurons across multiple brain regions, and targeted optogenetic perturbations during behavior, from coarse to holographic. The Scientist will build statistical physics theories of recurrent circuit models constrained by these data, use them to explain how connectivity structure organizes neural dynamics and computation, and test their predictions in new perturbation experiments at the Institute. We are looking for candidates with strong expertise in applied mathematics and/or statistical physics, fluency in modern machine learning, and an interest in neuroscience. Salary range: $87,450 - $108,250. Visa sponsorship and relocation assistance are available. To apply: https://alleninstitute.org/careers/jobs?jobId=f4864596-9e85-bbf6-a1f6-9e880… Feel free to email me with questions. Best, Ulises Pereira-Obilinovic Senior Scientist Allen Institute, Neural Dynamics ulises.pereira.o(a)alleninstitute.org

Oct. 10, 2026

Postdoctoral position in computational modeling of education data

by Kou Murayama

Dear all, We are seeking a postdoctoral research fellow at the Hector Research Institute of Education Sciences and Psychology at the University of Tübingen, Germany. This is a joint project with Michiko Sakaki (Hector Research Institute) and Peter Dayan (Max Planck Institute for Biological Cybernetics). # Key points - Topic: computational modeling of large-scale digital education data with the focus on motivation, emotion, metacognition, self-control, etc. - Position: full-time (100%) - Duration: 3 years - Profile: Excellent research track record and proven expertise in computational modeling - Application deadline: Oct 30, 2026 Full details and application instructions: https://uni-tuebingen.de/universitaet/karriere/newsfullview-stellenangebote… Please feel free to contact me with informal inquiries, and I would be grateful if you could forward this to anyone who may be interested. Best wishes, Kou Murayama -- / Kou Murayama, Ph. D. / Hector Research Institute of / Education Sciences and Psychology / University of Tübingen / k.murayama(a)uni-tuebingen.de / https://motivationsciencelab.com/

Oct. 9, 2026

Request to circulate: PhD and PostDoc position: TDA + PDEs + Deep Learning of 3D+time microglia morphology (Prague and Warsaw)

by Hahn, Jooyoung

Dear colleagues, Please find below an announcement of PhD and postdoc positions on the Topological Data Analysis (TDA) + Partial Differential Equations (PDEs) + Deep Learning of 3D+time microglia morphology Regards, Jooyoung Hahn Assistant Professor, FNSPE, Czech Technical University in Prague ---------------------------------------------- Pre-announcement: PhD and postdoc positions in MIND-MAP What does it mean when a brain cell changes its shape? In MIND-MAP, we turn 3D + time microscopy of microglia into geometry, topology and a quantitative language for brain states. The project combines mathematical method development with real, challenging biological data: the goal is not merely to apply existing tools, but to develop new ones. Two groups are recruiting, within a three-year project (2027–2029): PhD position at CTU in Prague (FNSPE), with Jooyoung Hahn • Hybrid PDE + deep-learning segmentation, scale-aware 3D shape representations, tracking in 3D + time, and geometry-informed TDA • Master's degree in mathematics, applied mathematics, computer science, physics or a related field; strong numerical analysis; Python and/or C++ • Contact: jooyoung.hahn(a)fjfi.cvut.cz<mailto:jooyoung.hahn@fjfi.cvut.cz> by 20 November 2026 • Flyer: https://jooyounghahn.github.io/jobs/MIND-MAP_PhD_CTU_Prague.html<https://www.linkedin.com/safety/go/?url=https%3A%2F%2Flnkd%2Ein%2FdNTxyFAc&…> PhD and Postdoc positions at the University of Warsaw, with Pawel Dlotko • Topological descriptors of shapes that change in time, shape trajectories, Ball Mapper and interpretable visualization • PhD: master's degree in a quantitative field. Postdoc: PhD with experience in TDA, geometry or related methods • Contact: p.dlotko(a)uw.edu.pl<mailto:p.dlotko@uw.edu.pl> • Flyer: https://jooyounghahn.github.io/jobs/MIND-MAP_PhD_Postdoc_Warsaw.html<https://www.linkedin.com/safety/go/?url=https%3A%2F%2Flnkd%2Ein%2Fd3sRijmE&…> Both groups work closely with Sandra Siegert's lab at ISTA (Austria), with access to unique 3D and 3D + time microscopy data, and with conferences and research visits. Interested? Send a CV and a few lines about your research interests and what you can bring. This is a pre-announcement; the official calls with formal conditions will be published separately. Please share with anyone who might be interested. #PhD<https://www.linkedin.com/search/results/all/?keywords=%23phd&origin=HASH_TA…> #Postdoc<https://www.linkedin.com/search/results/all/?keywords=%23postdoc&origin=HAS…> #TopologicalDataAnalysis<https://www.linkedin.com/search/results/all/?keywords=%23topologicaldataana…> #AppliedMathematics<https://www.linkedin.com/search/results/all/?keywords=%23appliedmathematics…> #Neuroscience<https://www.linkedin.com/search/results/all/?keywords=%23neuroscience&origi…> #DeepLearning<https://www.linkedin.com/search/results/all/?keywords=%23deeplearning&origi…> #PartialDifferentialEquations<https://www.linkedin.com/search/results/all/?keywords=%23partialdifferentia…>

Oct. 9, 2026