April 2026 - Comp-neuro - lists.cnsorg.org

Online Workshop: Introduction to Neuronal Modeling | April 28, 2026
by Spiros Chavlis April 7, 2026

April 7, 2026

Dear colleagues and friends, PhD candidate Roman Makarov and Dr. Michalis Pagkalos from our lab are organizing a free online workshop on neuronal modeling! You will learn how to build, validate, and analyze neuronal models with active dendrites. We will begin with foundational concepts, including neuronal structure, biophysical properties, and input integration. We will then move to hands-on model implementation using DendroTweaks and Dendrify, two modeling tools developed in the Poirazi Lab (https://dendrites.gr/) Participation is free and open to everyone. No prior modeling experience is required, but some familiarity with Python might be helpful. When: Tuesday, April 28, 2026 | 10:00 AM CET Register here: https://forms.gle/txUzajvPBzDc1EvWA More info: workshop(a)dendrites.gr Best regards, Spiros Chavlis, PhD

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DEADLINE EXTENSION - 12th April - Conference on Artificial Life (ALIFE 2026)
by Stavros Anagnou [Student-PECS] April 1, 2026

April 1, 2026

Dear colleagues, We warmly invite you to submit your work to the annual Conference on Artificial Life (ALIFE 2026), taking place in Waterloo, Canada, and online from 17–21 August 2026. Full Papers & Summaries submission deadline: 30 March 12th April 2026 (EXTENDED) This year’s theme, “Living and Lifelike Complex Adaptive Systems”, welcomes contributions exploring the simulation and synthesis of life, complex adaptive systems, and life as it could be in other media or environments, and we encourage submissions across the full spectrum of Artificial Life research, including embodied intelligence, synthetic biology, artificial chemistry, evolutionary systems, robotics, sustainability, ethics, and more. Full Papers (3–8 pages) will be peer reviewed and published open access in the official ALIFE 2026 Proceedings by MIT Press. Summaries (max. 2 pages) should report on previously published, peer-reviewed work. Accepted summaries will be presented at the conference but will not be included in the MIT Press proceedings. All submission types, formatting templates (Overleaf, LaTeX, MS Word), and detailed guidelines are available at:https://2026.alife.org/call-for-papers<https://2026.alife.org/call-for-papers> We kindly ask you to share this call within your networks and institutions. You can also support the conference by following, sharing, and engaging with ALIFE 2026 updates on social media. We look forward to your submissions and to welcoming you to ALIFE 2026. Sincerely, The ALIFE 2026 Organizing Committee https://2026.alife.org<https://2026.alife.org> ----------------------------------------------------- Follow us on social media for conference updates, and don’t forget to like and share. Help us spread the word and reach as many colleagues as possible — feel free to share within your networks and communities. https://www.linkedin.com/company/alifeconf<https://www.linkedin.com/company/alifeconf> https://bsky.app/profile/alifeconf.bsky.social<https://bsky.app/profile/alifeconf.bsky.social> https://www.facebook.com/ALIFEconf<https://www.facebook.com/ALIFEconf> https://x.com/ALifeConf<https://x.com/ALifeConf>

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Call for applications: 2026 School on Analytical Connectionism
by I-Chun Lin April 1, 2026

April 1, 2026

Topical focus: Language Acquisition August 17–28 2026; Chalmers University of Technology, Gothenburg https://www.analytical-connectionism.net/school/2026/ Apply by 17 April 2026 We are delighted to announce the 4th edition of the School on Analytical Connectionism. This 2-week course will focus on analytical theories of cognition, bringing together ideas from connectionism, cognitive science, and modern theories of machine learning. This course is appropriate for graduate students, postdoctoral fellows and faculty in fields from psychology and neuroscience, to physics, computer science, and mathematics. This year we will discuss questions like: - How can structured linguistic knowledge emerge from learning? - What theoretical principles govern generalisation, compositionality, and representation in neural systems? - How can we move beyond empirical demonstrations toward mechanistic, mathematically grounded explanations of cognitive phenomena like language acquisition? The course will bring together neuroscience, psychology, and machine-learning communities, introducing participants to connectionist theories of higher-level cognition and psychology as well as analytical methods for neural-network analysis. Participants will work in teams, mentored by course lecturers and organisers, to develop novel research projects on topics related to analytical connectionism. Participants will present the research proposals in Week 1 and interim results at the end of the course. Confirmed Faculty: - Michael Biehl (University of Groningen) - Caroline Rowland (Max Planck Institute for Psycholinguistics) - Paul Smolensky (Microsoft Research & Johns Hopkins) - Marco Baroni (ICREA & Pompeu Fabra University) - Francesco Cagnetta (SISSA) - Alex Cristia (ENS & CNRS) - Bruno Loureiro (ENS & CNRS) - Kanishka Misra (UT Austin) - Isabel Papadimitriou (University of British Columbia) - Luca Saglietti (Bocconi University) - Asad Sayeed (Gothenburg University) - Larissa Samuelson (University of East Anglia) - Kenny Smith (University of Edinburgh) - Chris Summerfield (Oxford University) Organisers: SueYeon Chung, Erin Grant, Flavio Nicoletti, Stefano Sarao Mannelli, Andrew Saxe

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Research Position in Optical Quantum Neural Networks: OIST Neural Computation Unit
by Kenji Doya April 1, 2026

April 1, 2026

Neural Computation Unit at Okinawa Institute of Science and Technology Graduate University (Prof. Kenji Doya) has research positions open for developing learning algorithms and use cases for the optical quantum neural networks developed by the Moonshot R&D Project in optical quantum computers (lead by Prof. Akira Furusawa): https://optical-quantum-computers.jp/en/ While most quantum computers today resort to error correction of qubits, which is highly costly, this project aims to achieve efficient system-level computation despite noisy elements, like the brain appears to be doing. The specification of the current machine is described in this preprint (https://arxiv.org/abs/2506.16147) and the software development kit is open in GitHub (https://github.com/HidehiroYonezawa/mqc3) The machine is being upgraded to allow nonlinear (non-Gaussian) operations. Applicants should have strong background in mathematics, computer science, and/or machine learning. Experiences in quantum physics and/or computational neuroscience are welcome. If you are interested, please send your CV, publication list, research statement, and referees (up to three names with e-mail) using the application form from our web page: https://www.oist.jp/ncu ---- 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://www.oist.jp/ncu

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