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Deep Math 2025 call for papers
by Ahmed El Hady Aug. 17, 2025

Aug. 17, 2025

DeepMath 2025: Call for Abstracts We are pleased to announce *DeepMath 2025*: the 7th installment of the Conference for the Mathematical Theory of Deep Learning (www.deepmath-conference.com) This year DeepMath will be held at the *University of Michigan in Ann Arbor Michigan*. We have a stellar lineup of invited speakers including: * Laura Balzano (University of Michigan) * Rama Chellappa (Johns Hopkins University) * Jelena Diakonikolas (University of Wisconsin) * Surbhi Goel (University of Pennsylvania) * Thomas Icard (Stanford University) * Robert Nowak (University of Wisconsin) We are inviting researchers to present a poster during our poster session. Please submit your work no later than *August 31, 2025* on OpenReview using the following link: https://openreview.net/group?id=deepmath-conference.com/DeepMath/2025/Confe… <https://openreview.net/group?id=deepmath-conference.com/DeepMath/2025/Confe…> DeepMath is a highly interdisciplinary conference focused on understanding fundamental theory driving the success of Deep Learning. A principal goal of this conference is to bring together theoreticians working on deep learning from various disciplines and perspectives. We, therefore, encourage submissions from researchers from diverse disciplines including but not limited to * Statistics * Physics * Computer science * Neuroscience * Mathematics * Psychology * Engineering Topics may address any area of deep learning research such as: * Expressivity * Generalization * Optimization * Representations * Computation * Network architectures * Recurrent networks * Emergent abilities like in-context learning, reasoning To complement the many conferences with applications and theory the focus for DeepMath will be exclusively on the theoretical and mechanistic understanding of the underlying properties of neural networks. Abstracts will not be made public (i.e., no official proceedings), and will be doubly-blind reviewed and selected for quality. All poster submissions should be properly anonymized in order to allow for blind refereeing. *Submissions should be no more than 1 page* although a second page may be used for references. Authors should submit a pdf file prepared using the *Latex style file available **here* <https://storage.googleapis.com/wzukusers/user-23451351/documents/5c90d93c12…>and should adopt all formatting, subject headings, font sizes, etc. defined therein. Submissions that fail to meet the format requirements will not be reviewed. The first author listed on the abstract is considered to be the presenting author. Each presenting author may submit only one abstract.

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To Spike or Not to Spike: A neural network model of how neurons communicate
by Grossberg, Stephen Aug. 15, 2025

Aug. 15, 2025

Dear Comp-Neuro colleagues, I am writing to announce the publication of my new article that describes psychological and neurobiological properties of neural network models that are composed of spiking neurons. The article is: Grossberg, S. (2025). Spiking neural network models of neurons and networks for perception, learning, cognition, and navigation: A review. Brain Sciences, 15(8), 870. https://www.mdpi.com/2076-3425/15/8/870 The Abstract of the article summarizes some of its high points: This article reviews and synthesizes highlights of the history of neural models of rate-based and spiking neural networks. It explains that theoretical and experimental results about how all rate-based neural network models, whose cells obey the membrane equations of neurophysiology, also called shunting laws, can be converted into spiking neural network models without any loss of explanatory power, and often with gains in explanatory power. These results are relevant to all the main brain processes, including individual neurons and networks for perception, learning, cognition, and navigation. The results build upon the hypothesis that the functional units of brain processes are spatial patterns of cell activities, or short-term-memory (STM) traces, and spatial patterns of learned adaptive weights, or long-term-memory (LTM) patterns. It is also shown how spatial patterns that are learned by spiking neurons during childhood can be preserved even as the child’s brain grows and deforms while it develops towards adulthood. Indeed, this property of spatiotemporal self-similarity may be one of the most powerful properties that individual spiking neurons contribute to the development of large-scale neural networks and architectures throughout life. Get Outlook for Mac <https://aka.ms/GetOutlookForMac>

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Two tenure-track positions at University of Oregon
by James Murray Aug. 15, 2025

Aug. 15, 2025

Dear colleagues, The Department of Bioengineering at the University of Oregon’s Knight Campus for Accelerating Scientific Impact invites applications for two complementary tenure-track faculty positions in computational and experimental neuroengineering: 1. Computational & Data-Science Neuroengineering Examples include but are not limited to the following: neural signal processing & data analytics for feature extraction, decoding, and adaptive control, high-throughput behavior tracking and closed-loop perturbations (e.g. pose estimation, unsupervised behavior clustering, neural conditional feedback), neuromorphic computing & AI hardware or brain-inspired AI algorithm development, spatial analysis of multi-omics data. 2. Experimental & Translational Neuroengineering Examples include but are not limited to the following: clean-room micro- and nanofabrication methods for neural interfaces, neurophotonics methods for brain stimulation, recording, and imaging, pre-clinical models in bioelectric medicine or brain injury repair, brain organoid technology development, and disease models. We are particularly interested in applicants with a demonstrated track record of translating discoveries into real-world impact, including through entrepreneurial activities; a demonstrated commitment to mentoring and advancing inclusive participation in scientific training and career pathways; and success in pedagogical environments that employ evidence-based teaching practices. All ranks (Assistant, Associate, or Full Professor) with a track record of research excellence commensurate with their seniority will be considered. Further details and application instructions can be found here: https://careers.uoregon.edu/en-us/job/535571/assistantassociatefull-profess… Please pass along this announcement to any potential candidates you know who might be interested. Any inquiries regarding this search may be sent to jmurray9(a)uoregon.edu. -James -- James M Murray Assistant Professor Depts. of Biology and Mathematics and Institute of Neuroscience University of Oregon murraylab.uoregon.edu<https://murraylab.uoregon.edu>

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Super early bird tickets now available—AE Global Summit on Open Problems for AI, London (Oct 28-30th, 2025)
by Battleday, Ruairidh Aug. 15, 2025

Aug. 15, 2025

Super-early-bird registration is now open for the AE Global Summit on Open Problems for AI, taking place in London from 28–30th October 2025. Over three days, we will bring together more than 1,000 researchers, policymakers, engineers, entrepreneurs, and artists to discuss the most important open problems in AI, and how we might solve them. Programme highlights Day 1: New Algorithmic Breakthroughs and AI Infrastructure Featuring Dr David Silver <https://davidstarsilver.wordpress.com/>and Dr Raia Hadsell (DeepMind), <https://raiahadsell.com/index.html> Prof Jakob Foerster (Meta & Oxford), <https://www.jakobfoerster.com/> Dr Laura Gilbert (Tony Blair Institute) <https://www.linkedin.com/in/dr-laura-gilbert/>, Prof Emine Yilmaz (UCL) <https://www.linkedin.com/in/emine-yilmaz-978b937/>, and senior research leaders from NVIDIA <https://www.nvidia.com/en-gb/>, Thomson Reuters <https://www.thomsonreuters.com/en>, Bertelsmann <https://www.bertelsmann.com/#st-1>, Wayve <https://wayve.ai/>, and others. Day 2: AI Safety, and AI in Enterprise & Society Speakers include Prof Chris Summerfield (AISI & Oxford) <https://www.psy.ox.ac.uk/people/christopher-summerfield>, Dr Samuel Bell (Meta) <https://samueljamesbell.com/>, Dr Artemis Seaford (ElevenLabs <https://www.linkedin.com/in/artemisseaford/>), Dr Marius Hobbhahn (Apollo Research) <https://www.linkedin.com/in/marius-hobbhahn-128927175/?originalSubdomain=uk>, and leaders from ADVAI <https://www.advai.co.uk/>, Academy, Tony Blair Institute <https://institute.global/>, and Bernstein Insights <https://www.bernstein.com/our-insights/insights.html>. Day 3: AI Entrepreneurship & Application With Alexander Straub (Straub Ventures) <https://www.linkedin.com/in/alexanderstraub/?originalSubdomain=uk>, Dr Trias Gkikopoulos (Innovate UK) <https://www.linkedin.com/in/triantafyllosgkikopoulos/?original_referer=http…>, Erwann Le Lannou (XTX Markets) <https://www.linkedin.com/in/erwann-le-lannou/?originalSubdomain=uk>, Prof Rose Luckin (UCL & Educate Ventures) <https://www.linkedin.com/in/rose-luckin-5245003/?authType=&authToken=&trk=m…>, Dr Irina Jurenka (DeepMind) <https://www.linkedin.com/in/irina-jurenka-74455235/?originalSubdomain=uk>, and contributors from Google Health <https://health.google/>, Raspberry Pi Foundation <https://www.raspberrypi.org/>, and Newton’s Tree. <https://www.newtonstree.ai/> The conference will feature keynote talks, panels, breakout rooms, and an expo hall, alongside opportunities for informal discussion with colleagues from institutions including Oxford <https://www.ox.ac.uk/>, Harvard <https://www.harvard.edu/>, MIT <https://www.mit.edu/>, UCL <https://www.ucl.ac.uk/>, DeepMind <https://deepmind.google/>, Meta <https://www.meta.com/en-gb/about/?srsltid=AfmBOooyD76gNdU_z8E_JulzOLafvKow3…>, Microsoft <https://www.microsoft.com/en-gb/>, and NVIDIA <https://www.nvidia.com/en-gb/>. We’d love to see some of you there! Register via the link below: http://bit.ly/4ozMsdY -- Dr Ruairidh McLennan Battleday BMBCh (Oxon) PhD President Thinking About Thinking, Inc <https://thinkingaboutthinking.org> Postdoctoral Research Fellow Center for Brain Science, Harvard University Center for Brains, Minds, and Machines, MIT

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Asst. Prof in AI @ Göttingen, Germany
by Ecker, Alexander Aug. 15, 2025

Aug. 15, 2025

We have an opening for a tenure track assistant professor position (W1 t.t. W2) in AI in our CS dept @uni-goettingen.de, Germany: https://uni-goettingen.de/en/697924.html Application deadline: Sept 19 It's a deliberately broad call. Areas of interest include: RL; VR, AR & digital avatars; Embodied AI, NLP; HCI; Causal models; Time series models; Multimodal data integration; Image analysis and CV; Computational and simulation science; Visualization; HPC and Energy-efficient AI. The position is embedded in the recently founded Lower Saxony Center for AI and Causal Methods in Medicine (CAIMed; https://caimed.de/en/) as well as the Campus Institute Data Science (CIDAS; https://www.uni-goettingen.de/en/690135.html) Göttingen. The Göttingen Campus is highly collaborative, has a great variety of data-intensive research in natural and life sciences, social science and humanities, including top-notch places like MPIs (MPI for Multidisciplinary Sciences, MPI for Solar Systems Research, MPI for Dynamics and Self-Organization), the German Primate Center (DPZ) and the German Aerospace Center (DLR). Göttingen is located in the center of Germany and Europe, in a region known for its green hills, lovely small towns with half-timbered houses and the Harz Mountains. Well-connected through motorways and high-speed trains. It is a small university town (around 120k people) and very family friendly. Everything within the city can be reached by bike within 15 min. Touch base with me if you have any questions. I’m happy to chat!

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Assistant Professor position in human cognitive neuroscience at Princeton
by Kenneth Norman Aug. 14, 2025

Aug. 14, 2025

The Department of Psychology and the Princeton Neuroscience Institute at Princeton University invite applications for a tenure-track Assistant Professor position in the area of human cognitive neuroscience to be hired jointly in Neuroscience and Psychology. We seek a faculty member with a demonstrated record of excellence in research and a strong commitment to teaching and mentoring. Relevant research approaches include, but are not limited to, computational, clinical, and neuroimaging research. Applicants are expected to hold a Ph.D. in Psychology, Neuroscience, Computer Science, or a related discipline. The successful applicant will be expected to teach both undergraduate and graduate courses in Psychology and Neuroscience, and to establish an active, internationally-recognized research program. To support their research, the successful applicant will have access to the Scully Center for the Neuroscience of Mind and Behavior, which operates a suite of facilities to study the human brain including two 3T Siemens MR scanners, OPM-MEG, EEG, eye tracking, and TMS laboratories. They will also have access to Princeton's world-class computational infrastructure, including GPU systems capable of running large-scale AI workflows. Applicants should submit online at https://www.princeton.edu/acad-positions/position/39681 and include a cover letter, curriculum vitae, research statement, teaching statement, and contact information for three references. Review of applications will begin on October 15, 2025. Expected Salary Range: $135,000 - $145,000 The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly. The University also offers a comprehensive benefit program to eligible employees. Please see this link <https://hr.princeton.edu/benefits-overview-prospective-candidates> for more information.

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Göttingen Cognition Forum on "Curiosity and Interaction" - Oct 13-15, 2025
by Priesemann, Viola Aug. 13, 2025

Aug. 13, 2025

Dear colleagues, hereby, we would kindly like to draw your attention to the upcoming Göttingen Cognition Forum<https://events.gwdg.de/event/1099/> (Oct 13-15, 2025). It is organized jointly by the CRC 1690 Cognition of Interaction, the RTG Curiosity, the Bernstein Center for Computational Neuroscience, and the EKFZ. We kindly invite you to join us in Göttingen for this interactive workshop! The abstract submission deadline (for posters as well as for presentations) to the satellite workshops has been extended to August 17. Contributions can be submitted here<https://events.gwdg.de/event/1099/abstracts/>. Plenary speakers are Jacqueline Gottlieb Bahador Bahrami Judith Burkart Steve Chang Nachum Ulanovsky and Agostina Palmigiano Participation is free of charge. Please don’t hesitate to contact me in case of questions. Information are available on: https://events.gwdg.de/event/1099/ _____________________ Prof. Dr. Viola Priesemann Max Planck Institute for Dynamics and Self-Organization & Georg-August-University Göttingen Am Fassberg 17, 37077 Göttingen viola.priesemann(a)ds.mpg.de

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ICONIP2025 Early Registration Open till August 15
by Kenji Doya Aug. 8, 2025

Aug. 8, 2025

We are pleased to announce the opening of early registration for ICONIP 2025 till August 15 (AoE). https://iconip2025.apnns.org/registration/ This year ICONIP received more than 1,000 submissions and selected about 400 papers for single-track oral, spotlight, and poster presentations, We hope to see many of you in beautiful Okinawa. ***** The 32nd International Conference on Neural Information Processing (ICONIP) 2025 Date: November 20 to 24, 2025 Venue: Okinawa Institute of Science and Technology (OIST): https://www.oist.jp Web site: https://iconip2025.apnns.org Honorary Chairs: Shun-ichi Amari, Kunihiko Fukushima Keynote Lectures: Machine Learning for Robots: From Perception to Action: Asako Kanezaki Closing the gap: From Digital AI to Physically grounded intelligence: Yew Soon Ong Development of Higher Cognitive Mechanisms: Insights From Neurorobotics: Jun Tani Tutorials: Mathematical Theories of Deep Foundation Models: Taiji Suzuki Free-energy Principle for AI Researchers and Neuroscientists: Takuya Isomura AI for Human Neuroscience Research: Saori Tanaka, Okito Yamashita, Yu Takagi Improved Explainability with Spiking Neural Networks: Maryam Doborjeh, Nikola Kasabov Methodology for Designing Brain-Like AI Software: Yoshimasa Tawatsuji, Hiroshi Yamakawa, Yudai Suzuki Special Sessions: Sustainable Smart Villages – Harnessing Edge AI and TinyML for Low-Resource Communities Generative AI and Deep Learning for Advancing Affective Human-Robot Interaction Reliable, Robust and Secure Machine Learning Algorithms and 5 more Workshops: 18th International Workshop on Artificial Intelligence and Cybersecurity (AICS 2025) Quantifying and Simulating Multi-Neuromodulatory Dynamics in the Biological Brain and 5 more General Chairs: Kenji Doya, Maryam Doborjeh Program Chairs: Tadahiro Taniguchi, Andrew Chi Sing Leung Inquiry: iconip2025(a)apnns.org ---- Kenji Doya <doya(a)oist.jp> Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University 1919-1 Tancha, Onna, Okinawa 904-0495, Japan Phone: +81-98-966-8594; Fax: +81-98-966-2891 https://groups.oist.jp/ncu

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Postdoc position in the Unit on the Neural Computations in Learning, NIMH
by Langdon, Angela (NIH/NIMH) [E] Aug. 7, 2025

Aug. 7, 2025

We have an opening for a postdoctoral fellow to join my lab at the National Institute of Mental Health at the NIH campus in Bethesda, MD. Research in the lab is focused on the computational neuroscience of reward prediction and learning. Broadly, we study how timing, inference processes and goal selection modulate learning in reward-guided tasks in animals and humans, and how these processes are instantiated in neural activity across the reward learning circuits of the brain. Our goal is to understand how reward learning is altered in compulsive behaviors, addiction, and motivational deficits in disorders of mental health. We are looking for a postdoc who is interested in developing approaches from reinforcement learning, dynamical systems theory, and Bayesian inference to understand the online regulation of reward prediction and learning in neural activity and behavior. We work with a broad network of collaborating labs that span rodent, NHP and human studies, and the ideal candidate will be comfortable working in a highly interdisciplinary environment to pursue novel and translational insights into the neural basis of reward learning. This opening is an excellent opportunity for a computational neuroscientist who wishes to apply theoretical ideas to understand empirical data, with the opportunity to collaborate on novel paradigms to test computational models of reward-guided behavior and reward learning in the brain. An overview of research training at NIH can be found here: https://www.training.nih.gov/research-training/ Interested candidates should have strong quantitative and programming skills, a background in neuroscience, psychology, cognitive science or relevant quantitative discipline and a record of scientific contributions in an area relevant to research in the lab. Interested candidates should send a brief research statement (1-2 paragraphs) and a cv to Dr Angela Langdon (angela dot langdon at nih dot gov). Informal enquiries are welcome!

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Announcing SNUFA 2025: Nov 5–6 (online) – Abstract submission and registration now open!
by Friedemann Zenke Aug. 6, 2025

Aug. 6, 2025

We are happy to announce SNUFA 2025, taking place 5–6 November 2025 (online)—your friendly online focus meeting on spiking neural networks that compute. Abstract submission and registration are now open! See https://snufa.net/2025 for details. This year's invited speakers are Elisabetta Chicca (University of Groningen), Jason Eshraghian (UC Santa Cruz), Tomoki Fukai (OIST), and Chengcheng Huang (University of Pittsburgh). Like every year, the workshop brings together researchers in computational neuroscience, machine learning, and neuromorphic engineering to present their work and discuss how to translate these findings into a better understanding of neural circuits. Topics include artificial and biologically plausible learning algorithms and the dissection of trained spiking circuits toward understanding neural processing. We aim to have a manageable number of talks with ample discussion time. Attendance is free, but registration is required. Abstract submission deadline: September 26, 2025 (anywhere on earth) SNUFA 2025 is brought to you by David Kappel, Julijana Gjorgjieva, Dan Goodman, and Friedemann Zenke --- https://snufa.net/2025 Powered by www.world-wide.org/Neuro/

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