October 2022 - Comp-neuro - lists.cnsorg.org

Python Package: SER model
by Fabrizio Damicelli 08 Aug '24

08 Aug '24

Dear Computational Neuroscience Community, I would like to point you to a potentially useful Python Package that might be of interest for your research, especially in the realm dynamical models and spreading dynamics on networks. "ser": S(usceptible)E(xcited)R(efractory) model on graphs, a dynamical model of spreading excitations. Code Repository: https://github.com/fabridamicelli/ser As of today, a few people already trust it and the package registers >11K total downloads, ~500/month (pypi.org) and has been used already in a few research projects. A few interesting features: - It is light-weight and fast (`numba` accelerated), i.e. many experiments can be simply run on a laptop - Installation and getting started is easy: `pip install ser` - Example notebooks: https://github.com/fabridamicelli/ser/blob/main/examples The SER model is a classical cellular automaton model used to study all sorts of complex systems, ranging from forest fire dynamics to self-organized criticality in the brain. Despite of the simplicity of its setup, it is capable of generating complex emergent dynamics with absolutely non-trivial higher-order statistical properties. To learn more about the SER model and its applications, you might want to check out these references: - Messe et al. (2018). Toward a theory of coactivation patterns in excitable neural networks. doi.org/10.1371/journal.pcbi.1006084 - Haimovici et al. (2013). Brain Organization into Resting State Networks Emerges at Criticality on a Model of the Human Connectome. doi.org/10.1103/PhysRevLett.110.178101 - Damicelli et al. (2019). Topological reinforcement as a principle of modularity emergence in brain networks. doi.org/10.1162/netn_a_00085 Check it out and any feedback/suggestions/bug reports are more than welcome (simply open an issue: https://github.com/fabridamicelli/ser/issues) All the best, Fabrizio Damicelli

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Call for Visiting Scholars in Theoretical Sciences at OIST (Application by August 15)
by Kenji Doya 21 Oct '23

21 Oct '23

We are pleased to announce Visiting Scholars in Theoretical Sciences at OIST for a flexible term of 1 to 12 months as below. ***** As part of an initiative to develop a vibrant program in theoretical sciences, OIST invites applications for Visiting Scholars in the Theoretical Sciences. The Okinawa Institute of Science and Technology (OIST) is a research institution with a Ph.D. program. Outstanding graduate students and faculty are being attracted internationally. OIST is beautifully situated on the tropical island of Okinawa, Japan. Applicants should have a Ph.D. in a relevant field and be independent researchers, i.e., should have an academic standing equivalent to senior postdoc, junior group leader, or faculty member at a research-intensive institution. The position has a flexible term of 1 to 12 months taken continuously starting between October 2021 and March 2022 with a preference for longer-term visitors. The appointment may be taken while on leave or sabbatical from another university and comes with housing, research funds, and moving allowance. Successful candidates will be eligible to apply for support with salary, where this is necessary to facilitate the visit. No teaching duties come with the position. OIST is an institution with no departments, aiming to eliminate barriers between people working in different fields. It provides a family-friendly working environment including the multilingual Child Development Center and has proactive policies designed to promote a culture of diversity. OIST is an equal opportunity, affirmative action educator, and employer. Further details can be found at https://www.oist.jp/. Applicants should submit a CV including a list of publications, a brief description of their research to date and proposed research while visiting OIST, and the desired period of visit. All visits are subject to the availability of funding. Applications received by August 15, 2021, are guaranteed full consideration. If you have any questions, please send inquiries to: tsvp(a)oist.jp To apply, please go to our Interfolio page, http://apply.interfolio.com/88541 ---- 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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ANNOUNCEMENT: comp-neuro has moved to new host
by Erik De Schutter 07 Jan '23

07 Jan '23

Dear comp-neuro subscriber, I am glad to announce that the comp-neuro mailing list has moved to a new home. This was necessary because the previous set-up became increasingly hard to maintain since I left the University of Antwerp. As a consequence it became difficult for aspirant members to subscribe and mails were sometimes delayed. The mailing list has now moved to a cloud based home and runs a more recent version of the software. I expect this will provide a stable solution with a better service. Appropriately, it is now managed by the Organization for Computational Neurosciences. Please encourage your colleagues, collaborators, students, etc who are not member yet to subscribe to comp-neuro, now that the website works again. From now on please use: - Email to post to mailing list: comp-neuro(a)lists.cnsorg.org - Email to contact admin/moderators: comp-neuro-owner(a)lists.cnsorg.org - Webpage of mailing list (to subscribe / unsubscribe / view archives): https://www.cnsorg.org/comp-neuro-mailing-list Erik De Schutter Okinawa Institute of Science and Technology

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Fully funded Phd position in the intersection of neuroscience and AI
by Guozhang Chen 30 Oct '22

30 Oct '22

We (the group of Prof. Wolfgang Maass) accept applications for a fully funded Phd position for research in the intersection of neuroscience and AI. This Phd student will work with our team on reverse engineering data-based models for cortical microcircuits and their learning capabilities, as for example in --Analysis of visual processing capabilities and neural coding strategies of a detailed model for laminar cortical microcircuits in mouse V1 (G. Chen, F. Scherr, W. Maass).Science Advances (Nov. 2, 2022), https://www.biorxiv.org/content/10.1101/2021.12.07.471653v3?versioned=t <https://www.biorxiv.org/content/10.1101/2021.12.07.471653v3?versioned=t> --A solution to the learning dilemma for recurrent networks of spiking neurons (Bellec, G., Scherr, F., Subramoney, A., Hajek, E., Salaj, D., Legenstein, R., & Maass, W.) Nature Communications 2020, 11(1), 1-15. In addition, the Phd student will work on the development of brain-inspired architectures and algorithms for AI, like in --Local prediction-learning enables neural networks to plan (C. Stoeckl, W.Maass) https://www.biorxiv.org/content/10.1101/2022.10.17.512572v1 <https://www.biorxiv.org/content/10.1101/2022.10.17.512572v1>, and for highly energy-efficient neuromorphic hardware, as in --A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware (A Rao, P Plank, A Wild, W Maass), Nature Machine Intelligence 4 (5), 467-479. https://igi-web.tugraz.at/PDF/261.pdf <https://igi-web.tugraz.at/PDF/261.pdf> In order to qualify for this Phd-position you need to have a master degree in computer science or related areas, very good skills in mathematics/theory, and programming experience for GPUs. You should also have an excellent record,demonstrations of your research potential, and be strongly motivated to collaborate with us on understanding “how the brain works”. If you qualify, please send me your CV, transcripts, names of referees, as well as links to your master thesis, papers, and other pertinent documents to email:<maass(a)igi.tugraz.at> Guozhang Chen on behalf of Prof. Dr. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b , A-8010 Graz, Austria http://www.igi.tugraz.at/maass/Welcome.html <http://www.igi.tugraz.at/maass/Welcome.html>

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Faculty position in computational neuroscience/machine learning at Stony Brook University
by Giancarlo La Camera 29 Oct '22

29 Oct '22

Stony Brook University is currently running a faculty search for a computational neuroscientist. The position will be in the Department of Neurobiology and Behavior and will be filled at the Assistant or Associate Professor level. A competitive recruitment package will include state-funded salary and benefits, newly renovated lab space and competitive start-up funding. The ideal candidate is an outstanding scientist in theoretical neuroscience, neuro-AI or in statistics/machine learning approaches to investigate topical questions in neuroscience. Candidates from diverse and underrepresented backgrounds are especially encouraged to apply. The successful candidate will join a vibrant, collaborative and diverse group of neuroscientists at Stony Brook University and its affiliated institutions, and will actively contribute to the Department’s mission in research as well as undergraduate, graduate and medical student education. Applications should be submitted at the following URL: https://apply.interfolio.com/111422. Review of applications will begin by Nov 15th, 2022 and continue until the position is filled. -- Giancarlo La Camera <https://www.stonybrook.edu/commcms/neurobiology/people/faculty_Giancarlo_La…>, PhD Associate Professor of Neurobiology and Behavior Stony Brook University

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PhD program in Systems/Computational/Cognitive neuroscience at U of Oregon
by Luca Mazzucato 28 Oct '22

28 Oct '22

We are accepting applications to the Interdepartmental Neuroscience Graduate Program (INGP) <https://ion.uoregon.edu/training-programs/graduate-fellows> at the Institute of Neuroscience, a robust graduate training in Neuroscience across departments at the University of Oregon. The goal of INGP is to train students to think independently, creatively, and critically about problems in neuroscience. We aim to train students in a variety of skills that will prepare students for successful research, teaching, policy, or industry career. Students can enter INGP through the departments of biology, human physiology, psychology, mathematics, physics, computer and information science, and the Knight Campus, depending on their interests. The majority of our students enter through the department of biology, which allows students to complete three rotations during their first year, in order to help students identify a laboratory in which to do their dissertation research. Students who enter through psychology, physiology, and mathematics begin in their dissertation labs immediately. Regardless of how students enter INGP, they are provided with a set of mentors at the peer and faculty levels. All graduate students are required to teach for at least one academic year during their graduate career; at least a portion of this teaching takes place the first year. *Training Program* Students typically fall into a defined training program, however, training can be tailored to fit a student’s need and research interest. We offer two training tracks: Systems, Cognitive and Theoretical - Courses: cellular neuroscience, systems neuroscience, cognitive neuroscience, computational neuroscience, combinatorics, stochastic processes, neural networks. - Journal clubs: systems neuroscience, theoretical neuroscience. - Meetings: neural circuits and behavior, zebrafish groupie, joint theory lab meetings.

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Doctoral studies in Computational/Theoretical Neuroscience at NYU
by Eero Simoncelli 28 Oct '22

28 Oct '22

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://neuroscience.nyu.edu/program.html, and https://as.nyu.edu/cns/DoctoralProgram.html] * SueYeon Chung - NeuroAI and geometry. * Andre A. Fenton - Molecular, neural, behavioral, and computational aspects of memory. * Paul W. Glimcher - Decision-making in humans and animals. Neuroeconomics. * 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. * Bijan Pesaran - Neuronal dynamics and decision-making. * 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 - Computational vision and audition. * Xiao-Jing Wang - Computational neuroscience, decision-making and working memory, neural circuits. * Alex Williams - Statistical analysis of neural data. Neuroscience Institute, School of Medicine (deadline: 1 December) [https://neuroscience.nyu.edu/program.html, and https://med.nyu.edu/departments-institutes/neuroscience/] * Gyorgy Buzsaki - Rhythms in neural networks. * Dmitri Chklovskii (also in the Simons Foundation) - Neural computation and connectomics. * Biyu He - Large-scale brain dynamics underlying human cognition. * Dmitry Rinberg - Sensory information processing in the behaving animal. * 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. * Brenden Lake (also in the Center for Data Science) - Computational modeling of cognition, deep learning. * Michael Landy - Computational approaches to vision. * Laurence Maloney - Mathematical approaches to psychology and neuroscience. * Denis Pelli - Visual object recognition. * Jonathan Winawer - Visual perception and memory. Mathematics (deadline: 18 December) [https://gsas.nyu.edu/admissions/arc/programs/mathematics.html] * David McLaughlin - Nonlinear wave equations, computational visual neuroscience. * 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. Data Science (deadline: 12 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. * Grace Lindsay (also in Psychology) - Machine learning models of the brain/mind. * Mengye Ren (also in Computer Science) - Machine learning, computer vision, representation learning. Physics (deadline: 30 December) [https://as.nyu.edu/physics/programs/graduate.html] * Marc Gershow - Perception, decision-making, and learning in neural circuits. 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.

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EPFL - Faculty position at the intersection of computational and life sciences
by Mathis Alexander 26 Oct '22

26 Oct '22

Dear colleagues, The Schools of Computer and Communication Sciences (IC) and Life Sciences (SV) at EPFL invite applications for a faculty position at the intersection of computational and life sciences. We seek candidates who use machine learning and/or other original computational approaches to solve challenges in life sciences. The appointment could be either at the assistant professor or tenured level. Candidates must have an outstanding academic record, a compelling vision, demonstrated impact, and a strong commitment to excellence in teaching and mentoring students. EPFL attracts top students from all over the world and offers competitive salaries, generous research funding and excellent research infrastructure. Switzerland has an exceptionally high human development index and consistently ranks highly in quality of life, economic competitiveness, and innovation. Applicants must submit a cover letter, a curriculum vitae including a publication list, brief statements of research and teaching interests, and contact information of at least 3 references (5 for tenured positions) who are ready to supply a letter upon request. To apply, go to: https://facultyrecruiting.epfl.ch/position/40599570 Screening will start on December 1, 2022, but applications submitted after this date will also be considered. Questions can be addressed to: Profs. George Candea and Matteo Dal Peraro Co-chairs of the Faculty Recruiting Committee E-mail: recruiting.icsv(a)epfl.ch<mailto:recruiting.icsv@epfl.ch> For more information on our schools, please visit https://sv.epfl.c<https://sv.epfl.ch/>h<https://sv.epfl.ch/> and https://ic.epfl.ch<https://ic.epfl.ch/> EPFL is an equal opportunity employer and family-friendly university. It is committed to increasing the diversity of its faculty. It strongly encourages women to apply.

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EPFL AI4Science Postdoctoral Fellowship: Deadline Oct 31st.
by Mathis Alexander 26 Oct '22

26 Oct '22

Dear colleagues, The EPFL AI4Science Fellowship gives outstanding and highly motivated young researchers the chance to collaborate with a broad range of EPFL faculty on accelerating the use and furthering the understanding of machine learning methods in the scientific discovery process. The Fellowship focuses on excellence and interdisciplinarity. Therefore fellows will work with several laboratories at EPFL and will be granted ample freedom to develop their own research agenda. We expect fellows to contribute to a vibrant and multidisciplinary community of researchers passionate about the transformation of science with new data-driven methods. Initial appointments will be made for one year, with the expectation of renewal for at least a second year, upon agreement of the AI4Science scientific committee. The salary follows the generous scale for EPFL post-doctoral researchers. Starting date is flexible. Application deadline: October 31st 2022 More details are available at https://www.epfl.ch/research/domains/cis/epfl-ai4science/call-for-fellows/ Best wishes, Alexander Mathis [cid:clip_image001.png] Alexander Mathis Tenure Track Assistant Professor people/alexander.mathis mathislab.org<http://mathislab.org>

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Neuroscience Gateway (NSG) Virtual workshop as a part of Society for Neuroscience Annual meeting, San Diego Nov 2022
by Majumdar, Amitava 26 Oct '22

26 Oct '22

Hello, We are happy to announce that the Neuroscience Gateway (NSG) will host a Virtual workshop as a part of the Society for Neuroscience Annual Meeting in San Diego, November 2022. Date and time of the virtual NSG workshop: November 12, 8:30 AM - 12:30 PM USA Pacific Time Zone. We have distinguished speakers who are early career researchers to senior researchers. They will present their work, many of which utilize NSG or are neuroscience software projects and are available on NSG for neuroscientists to use on high performance computing resources. Registration is free but required by November 9th. Please register if you plan to attend. Title of the virtual workshop: Neuroscience Gateway - Enabling Large Scale Modeling, Data Processing and Dissemination of Software Details about the list of speakers, abstract of talks and registration are available here: http://www.nsgportal.org/NSG_HPAC_SfN2022_Wkshop.web.htm Thank you. Regards. NSG Team

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