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

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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Up to 6 PhD fellowships in Cognitive Neuroscience at SISSA, Trieste, Italy, to start Oct, 2020
by Alessandro Treves 12 Oct '22

12 Oct '22

SISSA is an elite postgraduate research institution located in Trieste, Italy, and focused on Maths, Physics and Neuroscience. It operates in English: many among its students and faculty are not Italian. The Cognitive Neuroscience Department hosts 6 research labs that study the neuronal bases of time and magnitude processing, visual perception, motivation and intelligence, language and reading, tactile perception and learning, and neural computation. The Department is very inter–disciplinary; our approaches include behavioural, psychophysics, and neurophysiological experiments with humans and animals, as well as computational and mathematical models. Students with diverse backgrounds (physics, math, medicine, psychology, biology) are most welcome to apply. The Department has an exceptional track record with highly competitive funds (recent funding includes 4 ERC and 3 Human Frontiers grants) and publication in top journals (Nature, Science, PNAS, Current Biology). Recent placements after PhD include Harvard, MIT, Columbia and Princeton in the US; the NTNU, Manchester and Radboud in Europe; and Sydney University, Australia. Our alumni have been awarded 4 ERC grants, the 2015 Kandel Young Neuroscientist Prize and the 2017 ICTP Prize. More information about the Department is available at our website https://phdcns.sissa.it. The selection procedure is now open; to learn how to apply, please visit https://phdcns.sissa.it/admission-procedure. Please contact the PhD Coordinator (davide.crepaldi(a)sissa.it) and/or your prospective supervisor for more information and informal enquiries. -- Alessandro Treves SISSA, Cognitive Neuroscience, http://people.sissa.it/~ale/limbo.html if in, rm 241, via Bonomea 265, 34136 Trieste, Italy: +39-040-3787623

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Postdoc in neural data analysis
by Mark Humphries 26 Jun '22

26 Jun '22

A 3 year postdoc post is available in the lab of Prof Mark Humphries, at the University of Nottingham (UK) In this project, our aim is to test the overarching hypothesis that movement transitions are encoded by the same neural population reconfiguring its joint activity, for both rhythmic and discrete movements. We will tackle this question using newly-available population recordings during rhythmic movement transitions in Aplysia and discrete arm movement transitions in monkeys, The Humphries’ group researches fundamental insights into how the joint activity of neurons encodes information about and actions in the world. For more see: https://www.humphries-lab.org Queries: mark.humphries(a)nottingham.ac.uk Deadline: 5th September Full details, and to apply: https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2 [http://jobs.nottingham.ac.uk/org/images/socialmedia.png]<https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2> Job Vacancy at the University of Nottingham: Research Associate/Fellow (Fixed term)<https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2> Applications are invited for a postdoctoral research fellow to join the Humphries’ group on the MRC-funded project “Uncovering the neural basis of movement transitions”. The Humphries’ group researches fundamental... jobs.nottingham.ac.uk Professor Mark Humphries | MRC Senior non-Clinical Fellow | Chair in Computational Neuroscience Lab: humphries-lab.org<https://www.humphries-lab.org/> Twitter: @markdhumphries Public blog: https://medium.com/the-spike This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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Neuro2022 in Okinawa: Abstract submission by January 20th
by Kenji Doya 26 Apr '22

26 Apr '22

NEURO2022 June 30 - July 3, 2022, Okinawa, Japan https://neuro2022.jnss.org/en/ Plenary Lectures: Anne Churchland, University of California, Los Angeles Martin Schwab, University of Zurich Erin M. Schuman, Max Planck Institute for Brain Research Brain Prize Lecture: Adrian Peter Bird, University of Edinburgh Neuro2022 is a joint conference of Japanese Neuroscience, Neurochemistry and Neural Networks Societies, held at Okinawa Convention Center and adjacent seaside facilities: https://www.oki-conven.jp The conference aims to be a forum for neuroscientists, clinical researchers, machine learning and AI engineers from around the world. All scientific programs will be in English and the conference will be in a hybrid format to allow online participation. Abstract submissions are open till January 20th, 8am UTC. Please visit the web site for details: https://neuro2022.jnss.org/en/abstract.html Neuro2022 is preceded by OIST Computational Neuroscience Course https://groups.oist.jp/ocnc and followed by the second edition of International Symposium on AI and Brain Science http://www.brain-ai.jp/symposium2020/ both held at Okinawa Institute of Science and Technology https://www.oist.jp https://groups.oist.jp/conference-venues We hope to see many of you on this beautiful semitropical island in this coming summer. Best wishes, Kenji Doya, Japan Neuroscience Society Kohtaro Takei, Japanese Society for Neurochemistry Kazushi Ikeda, Japanese Neural Network Society ---- 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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Explainable AI: Overcoming problems of Deep Learning problems with Adaptive Resonance
by Grossberg, Stephen 09 Apr '22

09 Apr '22

Dear Colleagues, There's currently a lot of interest in AI, notably Deep Learning, and in achieving autonomous adaptive intelligence. The following new article summarizes foundational problems of reliability and trustworthiness of Deep Learning, explains how Adaptive Resonance overcomes them, and outlines a blueprint for achieving autonomous adaptive intelligence: Grossberg, S. (2020). A path towards Explainable AI and autonomous adaptive intelligence: Deep Learning, Adaptive Resonance, and models of perception, emotion, and action. Frontiers in Neurobotics, June 25, 2020. https://doi.org/10.3389/fnbot.2020.00036 Best, Steve Grossberg

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Cerebellar computation postdoc
by Nicolas Brunel 31 Mar '22

31 Mar '22

A postdoc position is available to build and analyze network models of cerebellar cortex that incorporate the diversity of cell types and synaptic connections observed in this structure. The goal of this research is to better understand the functions of these diverse cell types and connections. Approaches from statistical physics, nonlinear dynamics and machine learning will be used, and models will be constrained by new electrophysiological, transcriptomic and connectomic data. The postdoc will be jointly supervised by Wade Regehr (Department of Neurobiology at Harvard Medical School) and Nicolas Brunel (Duke University). The position will be based in Wade Regehr's lab, but with frequent visits to the Brunel lab at Duke. Applicants should have a strong background in computational/theoretical neuroscience, machine learning, theoretical physics, and/or applied mathematics. We are committed to building a diverse intellectual community, and particularly encourage women and members of underrepresented groups to apply to this position. For more information on the labs: Regehr Lab: https://urldefense.com/v3/__https://regehrmedharvard.wordpress.com/__;!!OTo… Brunel Lab: https://www.neuro.duke.edu/research/faculty-labs/brunel-lab Please email a cover letter explaining background and interest in the position, a curriculum vitae, and names & email addresses of two references to: Kim McDaniels Kimberly_Mcdaniels(a)hms.harvard.edu<mailto:Kimberly_Mcdaniels@hms.harvard.edu> Please have the subject of the email: “Computational Postdoc Applicant:” Your Name

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Postdoctoral position in "Multiphysics Brain Aging Modeling" at Stevens Institute of Technology, New York City, USA
by Johannes Weickenmeier 21 Mar '22

21 Mar '22

Dear all. A postdoctoral position in “Multiphysics Brain Aging Modeling” is available in the group of Prof. Johannes Weickenmeier (www.weickenmeierlab.com<http://www.weickenmeierlab.com>). The Matter Biomechanics Lab combines experimental methods to biomechanically characterize brain tissue properties and various computational modeling techniques (e.g. finite element analysis, multiphysics modeling, medical image analysis) with the ultimate goal to better understand healthy brain aging and neurodegenerative diseases. Our constitutive aging and Alzheimer’s disease models couple neurobiology and mechanics (i.e. morphological shape changes and tissue loading) in order to identify abnormal aging patterns and brain regions at risk of developing secondary damage, such as white matter hyperintensities, hypoperfusion, traumatic injury, and vascular degeneration. We validate our models against longitudinal imaging data from databases such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We are looking for applications with prior experience in advanced medical image analysis, data analysis, and modeling. Knowledge in the biology of aging is a significant advantage. The research will be performed at the campus of Stevens Institute of Technology right outside of New York. The position is funded through a grant from the NIH. The position is available now until filled. To apply, please send a motivation letter, CV, and contact information for 2-3 references to Prof. Johannes Weickenmeier (johannes.weickenmeier (at) stevens.edu) Stay well, Johannes Weickenmeier _______________________________________ Johannes Weickenmeier, PhD, Assistant Professor and Director of the Center for Neuromechanics Stevens Institute of Technology | Department of Mechanical Engineering |phone: 201-216-5527 | pronouns: he/him/his | Soft Matter Biomechanics: www.weickenmeierlab.com<https://nam02.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.weicke…>

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Postdoc in Computational Neuroscience at NYU
by Cristina Savin 28 Feb '22

28 Feb '22

Postdoc in Computational Neuroscience at NYU We are seeking a creative and driven computational neuroscience postdoctoral fellow to work on a collaborative project between the labs of Dora Angelaki (https://angelakilabnyu.org/ <https://angelakilabnyu.org/>) and Cristina Savin (http://www.cns.nyu.edu/~csavin <http://www.cns.nyu.edu/~csavin>) at New York University. The project studies neural representations underlying foraging behavior in monkeys, comparing both freely-moving and head-restrained behaviors, funded by the NIH BRAIN Initiative. The position is initially for one year, with the possibility of renewal. The successful candidate will have: a strong quantitative background demonstrable interest in neuroscience obtained (or be close to the completion of) a PhD in computational neuroscience, physics, mathematics, computer science, machine learning, statistics, etc ability to work in a strongly collaborative and interdisciplinary setting Preference will be given to candidates with: expertise in probabilistic machine learning strong programming skills, ideally in python previous experience with neural data analysis To send your application please provide your cv, a brief statement of research interests, and the contact details for reference letters to <csavin(a)nyu.edu <mailto:csavin@nyu.edu>>. For informal queries, please contact Cristina Savin (csavin(a)nyu.edu <mailto:csavin@nyu.edu>) or Dora Angelaki(da93(a)nyu.edu <mailto:da93@nyu.edu>). We will be available for in person discussions at the upcoming Cosyne meeting.

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Assistant Professor in Computational Neuroscience (W1) with tenure track option (to W2) at the Institute for Cognitive Science, University of Osnabrück.
by Peter König 28 Feb '22

28 Feb '22

Great opportunity in Computational Neuroscience: Assistant Professor in Computational Neuroscience (W1) with tenure track option (to W2) at the Institute for Cognitive Science, University of Osnabrück. (apologies for multiple postings) Full details at: https://www.uni-osnabrueck.de/universitaet/stellenangebote/stellenangebote-… --- This tenure-track Professorship is funded by the German Federal Government and the Länder under its Program for the Promotion of Young Academics (Tenure-Track Program). Upon meeting the general administrative requirements, you will be employed as a civil servant on limited tenure for an initial period of three years. If you receive a positive evaluation after the initial three years, this period can be extended by up to three further years. If you meet Osnabrück University’s standards with respect to ability, competence and academic achievement, you will be offered a tenured W2 Professorship in accordance with the relevant legal provisions without further application. Tasks and Responsibilities: Research and teaching should be in the area of computational neuroscience. The professorship and research should be focused on understanding principles of neuronal information processing and cognitive processes. The professorship complements and cooperates with the existing research groups of the Institute of Cognitive Science at Osnabrück University. Further, the holder of the position should actively contribute to existing and future collaborative research projects (e.g. RTG Situated Cognition, RTG Computational Cognition) and should participate in the respective continuation research proposal of the Research Training Group Computational Cognition. In addition, the professorship should engage in teaching in all degree programs of Cognitive Science (BSc, MSc, PhD). Teaching is in English. Conditions of Employment: Condition of employment is: - Research experience in the field of neuronal information processing with the focus of understanding principles of neuronal information processing or cognitive processes. - Research focus on at least one of the two following topics: - Methods of Experimental cognitive neuroscience like EEG, MEG, fMRI, TMS, cell recordings, eyetracking, or virtual reality - Models of information processing in neurons, networks of neurons like for example deep neuronal networks and machine learning. - A coherent research profile, must be motivated by or explain experimental data and there must be a realistic perspective to implement all parts of the own research, including the experimental components or data collection, at the university of Osnabrück. - An excellent command of the English language. - Willingness to participate in university administrative processes and commission work. For non-German speaking applicants, willingness is expected to learn the German language with a sufficient proficiency within two years. In addition, it would be welcome: - Teaching experience in the field of the professorship - Experience with acquiring third party research funding. Legal Conditions of Employment: You will hold a first degree, have a strong commitment to teaching, and have demonstrated your ability to engage independently in advanced academic research, as a rule by obtaining an outstanding PhD (in accordance with Section 30 subsection 2 of the Lower Saxony Higher Education Act [NHG]) in a relevant subject. The time between the applicant’s final PhD examination or the completion of other equivalent qualifications which qualify the applicant for the position in accordance with Section 30 para. 2 sentence 1 No. 3 Lower Saxony Higher Education Act and the applicant’s application for the assistant professorship should be no longer than four years. This period of time does not include periods caring for a child or several children under 18 years of age or periods caring for a dependent relative and increases by up to two years per child or period of care to a maximum four years in multiple cases of care (Section 30 para. 5 Lower Saxony Higher Education Act). The position is available on a full-time or part-time basis. Osnabrück University is a family-friendly university and is committed to helping working/studying parents balance their family and working lives. Osnabrück University is actively seeking to increase the number of female Professors in its employ. Applications from women are therefore particularly welcome. If two candidates are equally qualified, preference will be given to the candidate with disability status. For further information, please contact Prof. Dr Gordon Pipa, Tel. +49 541-969-2277, E-Mail: gpipa(a)uni-osnabrueck.de. Please submit your application (including a resume with full details of your scholarly and scientific employment history, list of publications and courses taught as well as planned research) in electronic form (as one pdf file) together with the “Bewerbungsprofil” [“Applicant Profile”] (DOCX, 13,58 kB) to the Dean of the School of Human Sciences, Prof. Dr. Susanne Boshammer, Universität Osnabrück, 49069 Osnabrück (bewerbungfb08(a)uni-osnabrueck.de) to arrive by March 27, 2022. Please enter the code word "CNtt" in the subject of your e-mail. We look forward to receiving your application. -- Prof. Dr. Peter König, Institute of Cognitive Science, University Osnabrück

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Assistant Prof (W1) TT @ Uni Osnabrück, Germany
by Ulrich G. Hofmann 25 Feb '22

25 Feb '22

This open position may be of interest to Comp Neuro scientists: https://www.uni-osnabrueck.de/universitaet/stellenangebote/stellenangebote-… ulrich hofmann

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Announcing Okinawa/OIST Computational Neuroscience Course 2022
by Erik De Schutter 25 Feb '22

25 Feb '22

OKINAWA/OIST COMPUTATIONAL NEUROSCIENCE COURSE 2022 Methods, Neurons, Networks and Behaviors June 13 to June 29, 2022 Okinawa Institute of Science and Technology Graduate University, Japan https://groups.oist.jp/ocnc After two consecutive cancelations due to COVID-19, OCNC 2022 will take place on June 13-29, preceding Neuro2022 (https://neuro2022.jnss.org) in Okinawa. Depending on the immigration situation in June the course will be either pure on-site or hybrid: a mixture of on-site and remote. The aim of the Okinawa/OIST Computational Neuroscience Course is to provide opportunities for young researchers with theoretical backgrounds to learn the latest advances in neuroscience, and for those with experimental backgrounds to have hands-on experience in computational modeling. We invite graduate students and postgraduate researchers to participate in the course, held from June June 13 through June 29, 2022 at an oceanfront seminar house of the Okinawa Institute of Science and Technology Graduate University. Applications are through the course web page (https://groups.oist.jp/ocnc) only: January 26 - February 28, 2022. Applicants will receive confirmation of acceptance in April. The 17th OCNC will be a shorter course than in the past: a two-week course covering single neurons, networks, and behaviors with time for student projects. Teaching will focus on methods with hands-on tutorials during the afternoons, and lectures by international experts. The course has a strong hands-on component based on student proposed modeling or data analysis projects, which are further refined with the help of a dedicated tutor. Applicants are required to propose their project at the time of application. However in the case of a hybrid format course, only on-site students will receive support for student projects. There is no tuition fee. The sponsor will provide lodging and meals during the course and may provide partial travel support. We hope that this course will be a good opportunity for theoretical and experimental neuroscientists to meet each other and to explore the attractive nature and culture of Okinawa, the southernmost island prefecture of Japan. Invited faculty: • Michael Berry II (Princeton University, USA) • Anne Churchland, Cold Spring Harbor Labs, USA • Erik De Schutter (OIST) • Kenji Doya (OIST) • Gaute Einevoll, Norwegian University of Life Sciences (online) • Tomoki Fukai (OIST) • Boris Gutkin (Ecole Normale Supérieure, Paris, France) • Yukiyasu Kamitani, Kyoto University, Japan • Bernd Kuhn (OIST) • Sang Wan Lee, KAIST, South Korea • Devika Narain, Erasmus Medical Center, Rotterdam, Netherlands • Viola Priesemann, MPG Göttingen, Germany (online) • Ivan Soltesz, Stanford University, USA • Greg Stuart, Australian National University, Australia • Greg Stephens (OIST) • Saori Tanaka, (ATR, Japan) • Marylka Yoe Uusisaari (OIST)

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14ᵗʰ Advanced Scientific Programming in Python in Bilbao Spain, 5–11 September, 2022
by Jakob Jordan 23 Feb '22

23 Feb '22

ASPP2022: 14ᵗʰ Advanced Scientific Programming in Python ======================================================== a Summer School by the ASPP faculty and the Faculty of Engineering of the Mondragon University, Bilbao https://aspp.school Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are devised to be interactive and to give the students enough time to acquire direct hands-on experience with the materials. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game. We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. We show how clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization are driving Python to become a standard tool for the programming scientist. This school is targeted at Master or PhD students and Post-docs from all areas of science. Competence in Python or in another language such as Java, C/C++, MATLAB, or R is absolutely required. Basic knowledge of Python and of a version control system such as git, subversion, mercurial, or bazaar is assumed. Participants without any prior experience with Python and/or git should work through the proposed introductory material before the course. We are striving hard to get a pool of students which is international and gender-balanced. Date & Location =============== 5–11 September, 2022. Bilbao, Spain. Application =========== You can apply online: https://aspp.school Application deadline: 23:59 UTC, Sunday 1 May, 2022. There will be no deadline extension, so be sure to apply on time. Be sure to read the FAQ before applying: https://aspp.school/wiki/faq Participation is for free, i.e. no fee is charged! Participants however should take care of travel, living, and accommodation expenses by themselves. We are in the process of securing some funds for supporting students with accommodation and living costs. Program ======= • Version control with git and how to contribute to open source projects with GitHub • Best practices in data visualization • Testing and debugging scientific code • Advanced NumPy • Organizing, documenting, and distributing scientific code • Advanced scientific Python: context managers and generators • Writing parallel applications in Python • Profiling and speeding up scientific code with Cython and numba • Programming in teams Faculty ======= • Jakob Jordan, Department of Physiology, University of Bern Switzerland • Jenni Rinker, Department of Wind Energy, Technical University of Denmark, Roskilde Denmark • Lisa Schwetlick, Experimental and Biological Psychology, Universität Potsdam Germany • Nicolas Rougier, Inria Bordeaux Sud-Ouest, Institute of Neurodegenerative Diseases, University of Bordeaux France • Pamela Hathway, GfK, Nuremberg Germany • Pietro Berkes, NAGRA Kudelski, Lausanne Switzerland • Rike-Benjamin Schuppner, Institute for Theoretical Biology, Humboldt-Universität zu Berlin Germany • Tiziano Zito, Department of Psychology, Humboldt-Universität zu Berlin Germany • Zbigniew Jędrzejewski-Szmek, Red Hat Inc., Warsaw Poland Organizers ========== Head of the organization for ASPP and responsible for the scientific program: • Tiziano Zito, Department of Psychology, Humboldt-Universität zu Berlin Germany Organization team in Bilbao: • Aitor Morales-Gregorio, Theoretical Neuroanatomy, Institute of Neuroscience and Medicine (INM-6), Forschungszentrum Jülich, Germany • Carlos Cernuda, Data Analysis & Cybersecurity, Faculty of Engineering, Mondragon Unibertsitatea, Bilbao Spain Website: https://aspp.school Contact: info(a)aspp.school

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Call for proposals for workshops and tutorials at CNS*2022 Melbourne
by Thomas Nowotny 23 Feb '22

23 Feb '22

OCNS Organisation for Computational Neurosciences Dear com-neuro community, We are requesting proposals for workshops and tutorials at CNS*2022 from the international community of computational neuroscientists. The 31st Annual Computational Neuroscience Meeting, CNS*2022, will be held at Melbourne, Australia, 16-20 July 2022. Proposals from all levels of faculty as well as advanced postdoctoral fellows are welcome. Tutorials are to be held on the first day and workshops on the last two days of the CNS*2022 Meeting. This is an excellent opportunity to reach international audience of computational neuroscience researchers participating in this meeting. Please see the links below for detailed information. Questions regarding workshops and tutorials should be addressed to workshops(a)cnsorg.org<mailto:workshops@cnsorg.org> or tutorials(a)cnsorg.org<mailto:tutorials@cnsorg.org> as appropriate. We are looking forward to your submissions. CALL FOR WORKSHOPS: https://www.cnsorg.org/cns-2022-call-for-workshops Priority Deadline for proposals: April 15 Jorge Mejias, Workshops Chair for CNS*2022 CALL FOR TUTORIALS: https://ocns.memberclicks.net/cns-2022-call-for-tutorials Deadline for proposals: April 15 Anca Doloc-Mihu, Tutorials Chair for CNS*2022 With kind regards, Thomas Nowotny, Vice President, on behalf of The OCNS Board of Directors -- Prof Thomas Nowotny Head of AI Research Group School of Engineering and Informatics University of Sussex Falmer, Brighton BN1 9QJ, UK Phone: +44-1273-678593 FAX: +44-1273-877873

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Fully funded PhD position, University of Groningen/NL
by Michael Biehl 23 Feb '22

23 Feb '22

*Last reminder, j**ust a few days left to apply! * A *fully funded PhD position* (4 years) in the *Statistical **Physics of Neural Networks* is available at the University of Groningen, The Netherlands, see https://www.rug.nl/about-ug/work-with-us/job-opportunities/?details=00347-0… for details and application details. Applications *(before March 1)* are only possible through this webpage. The title of the project is "The role of the activation function for feedforward learning systems (RAFFLES)". For further information please contact Michael Biehl. -- ---------------------------------------------------------- Prof. Dr. Michael Biehl Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence P.O. Box 407, 9700 AK Groningen The Netherlands Tel. +31 50 363 3997 https://www.cs.rug.nl/~biehl m.biehl(a)rug.nl

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NEUROTECH: Call for tutorials on Neuromorphic Computing
by Elisa Donati 23 Feb '22

23 Feb '22

Dear Colleagues, Given the success of last year’s NEUROTECH educational program, we have planned a new tutorial series for 2022! We are happy to announce a call for tutorials on the different aspects of the neuromorphic field. These tutorials will cover an aspect of active research in Neuromorphic Technology, with the aim of enabling a non-expert audience to get started on it. They will be held online via zoom, should be about 45 minutes in length, including a discussion session. Tutorials could be given by experienced researchers as well as emerging leaders who seek to disseminate their research methods to a wider audience. Presenters will benefit from the high visibility of the tutorial sessions within the NEUROTECH programme, and from the wider dissemination of their research methods and potential impact generated by other researchers. Proposals should not exceed 1 page (A4 or letter) in length. The proposal should outline the topic and indicate how the audience will benefit from it. Send your proposal by 07.03.2022 to educational(a)neurotechai.eu with the subject "Proposal for NEUROTECH Educational Tutorial". For more information: Call for Tutorials About NEUROTECH: The NEUROTECH project is committed to community building around Neuromorphic Technology. The educational programme is an essential pillar of our activities. Last year we have built a strong educational programme around a series of talks by leaders in the field (https://neurotechai.eu) Kind Regards, The NEUROTECH Educational Team

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Survey of the Allen Institute modeling software
by Anton Arkhipov 23 Feb '22

23 Feb '22

Dear Colleagues, We are conducting a survey about the Allen Institute’s neuroscience modeling software: https://forms.gle/R1ThdxBE98FhG1uQ6 The survey covers the Brain Modeling ToolKit, the SONATA file format, and the Visual Neuronal Dynamics visualization tool. It only takes several minutes, and we will appreciate to hear from you! Whether you are using our software, may be interested in using it, or are happily using something else, we will be glad to hear your opinion about our tools and modeling software in neuroscience in general. Please let us know what works, what doesn’t, and what new features would be helpful. Results of the survey will be used to improve our modeling software at the service of the community. This work is conducted under the NIH grant U24NS124001. Thank you, and we are looking forward to hearing from you! Anton. Anton Arkhipov Associate Investigator T: 206.548.8414 E: antona(a)alleninstitute.org<mailto:antona@alleninstitute.org> [Text Description automatically generated] alleninstitute.org<https://alleninstitute.org> brain-map.org

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[Meetings] CRNS Talk Series (3) - Live Talk by Dr. Séverin Lemaignan - PAL Robotics, Spain
by Amir Aly 22 Feb '22

22 Feb '22

Dear All * Apologies for cross-posting* The *Center for Robotics and Neural Systems* (CRNS) is pleased to announce the talk of *Dr. Séverin Lemaignan* who is a senior scientist at *PAL Robotics*, Spain on Wednesday, March 2nd from *11:00 am* to *12:30* *pm* (*London time*) over *Zoom*. >> *Events*: The CRNS talk series will cover a wide range of topics including social and cognitive robotics, computational neuroscience, computational linguistics, cognitive vision, machine learning, AI, and applications to autism. More details are available here: https://www.plymouth.ac.uk/research/robotics-neural-systems/whats-on <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…> >> *Link for the next event (No Registration is Required)*: Join Zoom Meeting https://plymouth.zoom.us/j/97451532624?pwd=ZmVSUzkrT3lUNWdXNmFEekNYSjRQUT09… >> *Title of the talk*: Teaching robots autonomy in social situations *Abstract*: Participatory methodologies are now well established in social robotics to generate blueprints of what robots should do to assist humans. The actual implementation of these blueprints, however, remains a technical challenge for us, roboticists, and the end-users are not usually involved at that stage. In two recent studies, we have however shown that, under the right conditions, robots can directly learn their behaviours from domain experts, replacing the traditional heuristic-based or plan-based robot controllers by autonomously learnt social policies. We have derived from these studies a novel 'end-to-end' participatory methodology called LEADOR, that I will introduce during the seminar. I will also discuss recent progress on human perception and modeling in a ROS environment with the emerging ROS4HRI standard. >> If you have any questions, please don't hesitate to contact me, Regards ---------------- *Dr. Amir Aly* Lecturer in Artificial Intelligence and Robotics Center for Robotics and Neural Systems (CRNS) School of Engineering, Computing, and Mathematics Room B332, Portland Square, Drake Circus, PL4 8AA University of Plymouth, UK

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9th Iberian Conference on Perception, Barcelona, June 2022
by Xavier Otazu Porter 22 Feb '22

22 Feb '22

Dear colleague, perception researcher, We are pleased to invite you to attend the 9th Iberian Conference on Perception (CIP 2022), which will be held on June 27th-29th, 2022, in Barcelona, Catalonia, Spain (https://www.cip2022.org<https://www.cip2022.org/>). CIP focuses on perception, with an emphasis on, but no limitation to, several aspects of perception such as motion perception, spatial vision, stereopsis, colour, perception and action, attention and cognition, audition, multisensory integration, reading and speech, brain imaging, art and aesthetics, perception in clinical populations and computational modelling. In addition to talks on this broad range of topics, the conference will include five symposia, poster sessions, and two keynote lectures from young internationally renowned scientists, Dr Iris Groen, from the University of Amsterdam, and Prof Manuel Spitschan, from the Max Planck Institute in Tübingen.. The event will take place at the Casa Convalescència<https://uab-casaconvalescencia.org/es/> in the modernist historical complex of Hospital de la Santa Creu i Sant Pau <https://www.santpaubarcelona.org/> in Barcelona, which was declared a UNESCO World Heritage Site in 1997. The COVID-19 pandemic forced us to break with the biennial organisation of CIP and to cancel the 2021 edition. For this year's edition, the health and safety of our speakers, attendees and staff will be a top priority. We designed the conference around this premise. The venue and program will allow social distancing while on site and regular ventilation of the conference room. All attendees will be asked to continue to wear face masks (unless medically exempt) during the conference and throughout all the premises of the Casa Convalescència. These policies will continue to be reviewed in line with government and local authority updates. We look forward to an exciting scientific programme and rely on the renewed eagerness of the research community to submit abstracts on their recent studies. Abstracts deadline: 15th April Registration: From February 15th to 1st June The Organising Committee Dr Xavier Otazu Dr Xim Cerda-Company Dr C. Alejandro Parraga Dr Olivier Penacchio Computer Vision Center<http://www.cvc.uab.cat> CONFIDENTIALITY WARNING<http://www.cvc.uab.es/?page_id=7475>

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Postdoctoral position in natural language processing and neuroscience, University of Geneva, Switzerland
by Timothée Proix 21 Feb '22

21 Feb '22

Dear all, a postdoctoral position is available under the supervision of Prof. Pierre Mégevand (https://www.unige.ch/medecine/neucli/en/groupes-de-recherche/1034megevand/) and Timothée Proix (https://ndlab.ch/) at the University of Geneva, Switzerland. The project lies at the interface between natural language processing and intracranial EEG data analysis. The goal of the project is to understand the neural representations of speech production and perception in conversations. The candidate will contribute to acquisition and analysis of intracranial EEG data and speech recordings. Applicants should have prior experience with machine learning methods for natural language processing, as well as in advanced data analysis techniques. Experience in electrophysiological recordings and knowledge in neuroscience is a significant advantage. The research will be performed at the campus Biotech in the university of Geneva, in collaboration with the Geneva University Hospital. The positions are funded by the private foundation of the Geneva University Hospital, and salaries are in compliance with guidelines of the University of Geneva. The ideal start is May 2022, with some flexibility. To apply, send a motivation letter, CV, and contact information for 2-3 references, as well as any other relevant documents to the Prof. Pierre Mégevand (pierre.megevand (at) unige.ch) as well as Timothée Proix (timothee.proix (at) unige.ch). Screening of applications will start by March 2022 and will continue until the position is filled. Timothée Proix

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NSF Neuronex Big Brain Imaging Hybrid Workshop @ Boston University - April 7-8, 2022
by Chen, Jerry 21 Feb '22

21 Feb '22

We are proud to announce the 2022 Big Brain Imaging Workshop hosted jointly by the NSF NeuroNex Nemonic Hub as well as the Boston University Neurophotonics Center! This two-day hybrid workshop will take place at Boston University and online on Thursday, April 7th and continue on Friday, April 8th, 2022. The 2022 Big Brain Imaging Workshop is an opportunity to join in the discussion on optical approaches for cellular resolution imaging of neuronal populations that have been highly instrumental for uncovering the principles of neural circuit function. To date, the microscope technology development for imaging the nervous system has largely been focused on applications on a subset of model species with smaller, optically accessible brains (ex. c. elegans, zebrafish, mice). The ability to translate these technologies to species with brains that are both physically larger and less optically accessible remains a challenge. The topic of the workshop is focused on advancing cellular resolution brain imaging techniques in "larger" brains of mammalian species (ex. rats, cats, ferrets, marmosets, macaques). The goal is to bring neuroscientists and optical engineers together to discuss challenges and come up with potential solutions that will pave the way for the next generation of microscopes that can be applied to a greater number of model organisms. Invited Speakers Daniel Aharoni - University of California, Los Angeles Adam Charles - Johns Hopkins University Anna Devor - Boston University David Fitzpatrick - Max Planck Institute Florida Emily Gibson - University of Colorado Anschutz Prakash Kara - University of Minnesota Jerome Mertz - Boston University Kristina Nielsen - Johns Hopkins University Anitha Pasupathy - University of Washington Bijan Perasan - New York University Nicholas Priebe - University of Texas, Austin Eyal Seidemann - University of Texas, Austin Lei Tian - Boston University Alipasha Vaziri - Rockefeller University Chris Xu - Cornell University In addition to the invited speakers, spots are available for short talks by visiting the registration page and submitting a brief abstract: For more information and free registration, visit: https://nemonic.ece.ucsb.edu/index.php/Big_Brain Jerry Chen, PhD Assistant Professor Department of Biology Boston University www.chen-lab.org<http://www.chen-lab.org> jerry(a)chen-lab.org<mailto:jerry@chen-lab.org> Jerry Chen, PhD Assistant Professor Department of Biology Boston University www.chen-lab.org<http://www.chen-lab.org> jerry(a)chen-lab.org<mailto:jerry@chen-lab.org>

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postdoc in Computational Neuroscience, Cambridge-Columbia collaboration
by Máté Lengyel 18 Feb '22

18 Feb '22

Postdoc in Computational Neuroscience, Cambridge-Columbia collaboration We are seeking a highly creative and motivated postdoctoral fellow to work on a collaborative project between the labs of Guillaume Hennequin and Máté Lengyel at the Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, and Daniel Wolpert at the Zuckerman Mind Brain Behavior Institute, Columbia University. The project studies neural network mechanisms underlying the context-dependent (continual) learning of motor repertoires and ties together several threads of research recently developed in our labs, based on the following key publications (note that several are collaborative between our groups): - JB Heald, M Lengyel, DM Wolpert (2021) Contextual inference underlies the learning of sensorimotor repertoires. Nature 600:489-493. - TC Kao, MS Sadabadi, G Hennequin (2021). Optimal anticipatory control as a theory of motor preparation: a thalamo-cortical circuit model. Neuron 109:1567-1581. - TC Kao, KT Jensen, GM van de Ven, A Bernacchia, G Hennequin (2021) Natural continual learning: success is a journey, not (just) a destination. NeurIPS, https://tinyurl.com/2jfyss8c - Echeveste R, Aitchison L, Hennequin G, Lengyel M (2020) Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference. Nature Neuroscience 23:1138-1149. The postdoc will be based in Cambridge, with an opportunity for regular visits to Columbia. The successful candidate will have - a strong quantitative background - demonstrable interest in theoretical neuroscience - obtained (or be close to the completion of) a PhD or equivalent in computational neuroscience, physics, mathematics, computer science, machine learning or a related field Preference will be given to candidates with - previous experience in computational neuroscience, especially with the dynamics of recurrent neural network, and function-optimized neural networks - sufficient programming skills to run numerical simulations and to use large scale optimization packages - expertise with advanced data analysis and Bayesian techniques For further details and to send your application, please go to https://www.jobs.cam.ac.uk/job/33691/. For informal queries, please contact Guillaume Hennequin <g.hennequin(a)eng.cam.ac.uk>, Máté Lengyel <m.lengyel(a)eng.cam.ac.uk> or Daniel Wolpert <wolpert(a)columbia.edu>. Máté Lengyel -- Professor of Computational Neuroscience Computational and Biological Learning Lab Cambridge University Engineering Department Trumpington Street, Cambridge CB2 1PZ, UK tel: +44 (0)1223 748 532, fax: +44 (0)1223 765 587 email: m.lengyel(a)eng.cam.ac.uk web: lengyellab.org

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KogWis2022 | 15th Biannual Conference of the German Cognitive Science Society +++ The call for symposia is open
by Constantin Rothkopf 18 Feb '22

18 Feb '22

Event: The 15th Biannual Conference of the German Cognitive Science Society, KogWis2022 Theme: Understanding Minds Date: 5.-7. September 2022 Location: Freiburg im Breisgau, Germany Host: Albert-Ludwigs University Freiburg Web: https://www.kogwis2022.uni-freiburg.de/ Abstract: The 15. biannual Conference of the German Cognitive Science Society (KogWis2022) will take place from 5.-7. September 2022 in Freiburg i.Br., Germany, organized by the Center for Cognitive Science. The theme “Understanding Minds” reflects two perspectives: The conference provides a forum for all topics in the study of how minds – both human and artificial – operate. The theme also puts a specific spotlight on how cognitive systems make sense of the world, in particular in language comprehension and communication. The Call for Symposia for the 15th Biannual Conference of the German Cognitive Science Society, KogWis2022, is now open! https://www.kogwis2022.uni-freiburg.de/ Confirmed keynote speakers are: Dedre Gentner, Northwestern University, Illinois Seana Coulson, University of California, San Diego Marcel Brass, Humboldt University, Berlin Matthew Crocker, Saarland University, Saarbrücken For any inquiries please use the conference e-mail-address kogwis2022(a)cognition.uni-freiburg.de. Further information is available on the conference website: www.kogwis2022.uni-freiburg.de. Organising Committee: Evelyn Ferstl, Lars Konieczny, Rul von Stülpnagel, Lisa Zacharski, Judith Beck

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MBL Methods in Computational Neuroscience Course
by Stephen A. Baccus 18 Feb '22

18 Feb '22

Applications are open for the Methods in Computational Neuroscience course at the Marine Biology Laboratory in Woods Hole, MA. The course will run from July 28 to August 24, 2022, and the online application form can be found at: https://www.mbl.edu/education/courses/methods-in-computational-neuroscience/<https://ws2.mbl.edu/studentapp/studentapp.asp?courseid=MCN> The course application deadline is *March 30*. The course covers a range of topics in computational neuroscience including neuronal biophysics, neural coding & information processing, circuit dynamics, learning & memory, motor control, and cognitive processing & disease. In addition, numerous tutorials and problem sets will cover a broad range of computational and mathematical modeling methods. The course strongly emphasizes the collaboration between theory and experiment in solving neuroscience problems, and lectures will be given by a mixture of theorists and experimentalists. The final weeks of the course are primarily reserved for work on projects that students design in collaboration with the resident faculty. Further information can be found on the MCN website: http://www.mbl.edu/mcn/ 2022 Course Directors: Stephen Baccus, Stanford University Xiao Jing Wang, New York University 2022 Faculty: Larry Abbott, Columbia University Tim Behrens, Univ. College London Emery Brown, MIT Randy Buckner, Harvard University Anne Churchland, UCLA Claudia Clopath, Imp. College London Albert Compte, IDIBAPS Shaul Druckmann, Stanford University Uri Eden, Boston University Bard Ermentrout, U. of Pittsburgh Adrienne Fairhall, U. of Washington Michale Fee, MIT James Fitzgerald, Janelia Res., HHMI Loren Frank, UCSF Stefano Fusi, Columbia University Surya Ganguli, Stanford University Paul Glimcher, New York University Mark Goldman, UC Davis Nancy Kopell, Boston University Eve Marder, Brandeis University Yiota Poirazi, IMBB-FORTH David Redish, U. Minnesota Terry Sejnowski, Salk Institute Reza Shadmehr, Johns Hopkins Univ. Sara Solla, Northwestern University Haim Sompolinsky, Hebrew University Nelson Spruston, Janelia Res., HHMI Josh Tenenbaum, MIT Nao Uchida, Harvard University Greg Wayne, DeepMind

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[jobs] Phd opportunity in Lille, France - Spiking Neural Networks for Video Analysis
by Ioan Marius BILASCO 17 Feb '22

17 Feb '22

The FOX team from the CRIStAL laboratory (UMR CNRS), Lille France is looking to recruit a PhD student starting as soon as possible on the following subject : Spiking Neural Networks for Video Analysis The FOX research group is part of the CRIStAL laboratory (University of Lille, CNRS), located in Lille, France. We focus on video analysis for human behavior understanding. Specifically, we develop spatio-temporal models of motions for tasks such as abnormal event detection, emotion recognition, and face alignment. We are also involved in IRCICA (CNRS), a research institute promoting multidisciplanary research. At IRCICA, we collaborate with computer scientists and experts in electronics engineering to create new models of neural networks that can be implemented on low-power hardware architectures. Recently, we designed state-of-the-art models for image recognition with single and multi-layer unsupervised spiking neural networks. We were among the first to succesfully apply unsupervised SNNs on modern datasets of computer vision. We also developed our own SNN simulator to support experiments with SNN on computer vision problems. Our work is published in major journals (Pattern Recognition, IEEE Trans. on Affective Computing) and conferences (WACV, IJCNN) in the field. Abstract: Spiking Neural Network have recently been evaluated on classical image recognition tasks [1]. This work has highlighted their promising performances in this domain and have identified ways to improve them to be competitive with comparable deep learning approaches. In particular, it demonstrated the ability of SNN architectures to learn relevant patterns for static pattern recognition in an unsupervised manner. However, dealing with static images is not enough, and the computer vision community is increasingly interested in video analysis, for two reasons. First, video data is more and more common and corresponds to a wide range of applications (video surveillance, audio-visual productions, autonomous vehicles...). Second, this data is richer than isolated static images, and thus offers the possibility to develop more effective systems, e.g. using motion information. Thus, it is recognized in the community that modeling motion in videos is more relevant than studying visual appearance alone for tasks such as action or emotion recognition. The next step for SNNs is therefore to study their ability to model motion rather than, or in addition to, image appearance. The goal of the Ph.D. candidate will be to explore the use of SNNs for space-time modeling in videos. This work will be targeted towards applications in human behavior understanding and especially action recognition. More specifically, the Ph.D. candidate is expected to: * identify what issues may prevent space-time modeling with SNNs and how they can be circumvented; * propose new supervised and unsupervised SNN models for motion modeling, which are compatible with hardware implementations on ultra-low power devices; * evaluate the proposed models on standard datasets for video analysis. Detailed subject: https://bit.ly/stssnnfox <https://bit.ly/stssnnfox> Candidates must hold a Master degree (or an equivalent degree) in Computer Science, Statistics, Applied Mathematics or a related field. Experience in one or more of the following is a plus: • image processing, computer vision; • machine learning; • bio-inspired computing; • research methodology (literature review, experimentation…). Candidates should have the following skills: • good proficiency in English, both spoken and written; • scientific writing; • programming (experience in C++ is a plus, but not mandatory). This PHD thesis will be funded in the framework of the ANVI-Luxant industrial chair. The general objective of the Chair is to make a scientific and technological progress in the mastery of emerging information processing architectures such as neuromorphic architectures as an embedded artificial intelligence technique. The use-case studies will come from video protection in the context of retail and transportation. The candidate will be funded for 3 years; he/she is expected to defend his/her thesis and graduate by the end of the contract. The monthly gross salary is around 2000€, including benefits (health insurance, retirement fund, and paid vacations). The position is located in Lille, France. With over 110 000 students, the metropolitan area of Lille is one France's top education student cities. The European Doctoral College Lille Nord-Pas de Calais is headquartered in Lille Metropole and includes 3,000 PhD Doctorate students supported by university research laboratories. Lille has a convenient location in the European high-speed rail network. It lies on the Eurostar line to London (1:20 hour journey). The French TGV network also puts it only 1 hour from Paris, 35 mn from Brussels, and a short trips to other major centres in France such as Paris, Marseille and Lyon. For application, please send the following information in a single PDF file to Dr. Marius Bilasco (marius.bilasco(a)univ-lille.fr <mailto:marius.bilasco@univ-lille.fr>) with subject [PhD_Luxant-ANVI]: * A cover letter. * A curriculum vitae, including a list of publications, if any. * Transcripts of grades of Master's degree. * The contact information of two references (and any letters if available). We look forward to receiving your application as soon as possible, but no later than 26.3.2022

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[jobs] PhD opportunity - Spatio-temporal augmentation models for motion pattern learning - AI_PhD@Lille, France
by Ioan Marius BILASCO 17 Feb '22

17 Feb '22

The FOX team from the CRIStAL laboratory (UMR CNRS), Lille France is looking to recruit a PhD student starting on October 1st 2022 on the following subject : Spatio-temporal data augmentation models for motion pattern learning using deep learning: applications to facial analysis in the wild The FOX research group is part of the CRIStAL laboratory (University of Lille, CNRS), located in Lille, France. We focus on video analysis for human behavior understanding. Specifically, we develop spatio-temporal models of motions for tasks such as abnormal event detection, emotion recognition, and face alignment. Our work is published in major journals (Pattern Recognition, IEEE Trans. on Affective Computing) and conferences (WACV, IJCNN). Abstract: Facial expression analysis is a well-studied field when dealing with segmented and constrained data captured in lab conditions. However, many challenges must still be addressed for building in-the-wild solutions that account for various motion intensities, strong head movements during expressions, the spotting of the subsequence containing the expression, partially occluded faces, etc. In recent years, learned features based on deep learning architectures were proposed in order to deal with these challenges. Deep learning is characterized by neural architectures that depend on a huge number of parameters. The convergence of these neural networks and the estimation of optimal parameters require large amounts of training data, especially when dealing with spatio-temporal data, particulary adequate for facial expression recognition. The quantity, but also the quality, of the data and its capacity to reflect the addressed challenges are key elements for training properly the networks. Augmenting the data artificially in an intelligent and controlled way is an interesting solution. The augmentation techniques identified in the literature are mainly focused on image augmentation and consist of scaling, rotation, and flipping operations, or they make use of more complex adversarial training. These techniques can be applied at the frame level, but there is a need for sequence level augmentation in order to better control the augmentation process and ensure the absence of temporal artifacts that might bias the learning process. The generation of dynamic frontal facial expressions has already been addressed in the literature. The goal of this Ph.D. is to conceive new space-time augmentation methods for unconstrained facial analysis (involving head movements, occultations, etc.). Attention should be paid in assessing the quality standards related to facial expression requirements: stability over time, absence of facial artifacts, etc. More specifically, the Ph.D. can didate is expected to conceive augmentation architectures that address various challenges (motion intensities, head movements) while maintaining temporal stability and eliminating facial artifacts. More details are available here : https://bit.ly/staugm_motion <http://bit.ly/st_augm_motion> Candidates must hold a Master degree in Computer Science, Statistics, Applied Mathematics or a related field. Experience in one or more of the following is a plus: • image processing, computer vision; • machine learning; • research methodology (literature review, experimentation…). Candidates should have the following skills: • good proficiency in English, both spoken and written; • scientific writing; • programming (experience in C++ is a plus, but not mandatory). This PHD thesis will be funded in the framework of the AI_PhD@Lilleprogram. http://www.isite-ulne.fr/index.php/en/phd-in-artificial-intelligence/ <http://www.isite-ulne.fr/index.php/en/phd-in-artificial-intelligence/> The candidate will be funded for 3 years; he/she is expected to defend his/her thesis and graduate by the end of the contract. The monthly gross salary is around 2000€, including benefits (health insurance, retirement fund, and paid vacations). Additional financial support is expected in the framework of the AI_PhD@Lille program. The position is located in Lille, France. With over 110 000 students, the metropolitan area of Lille is one France's top education student cities. The European Doctoral College Lille Nord-Pas de Calais is headquartered in Lille Metropole and includes 3,000 PhD Doctorate students supported by university research laboratories. Lille has a convenient location in the European high-speed rail network. It lies on the Eurostar line to London (1:20 hour journey). The French TGV network also puts it only 1 hour from Paris, 35 mn from Brussels, and a short trips to other major centres in France such as Paris, Marseille and Lyon. We look forward to receiving your application as soon as possible, but no later than 26.03.2021.

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job: staff scientist/team leader at NIMH
by Francisco Pereira 17 Feb '22

17 Feb '22

The National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), is recruiting for a Staff Scientist/Team Leader position to direct the Scientific and Statistical Computing Core/AFNI Team (https://afni.nimh.nih.gov).The primary function of this group is to support multimodal neuroimaging research in the intramural research program (IRP) at NIH. This includes (i) applying, extending, and developing new and existing software tools and techniques to conduct pioneering analyses on a diverse array of neuroimaging modalities (e.g. MRI, DTI, fMRI, MEG, PET, and EEG), (ii) advising and training IRP researchers on neuroimaging analysis methods, and (iii) leading the future growth and development of the AFNI code base ( https://github.com/afni/afni) Primary responsibilities of the Team Leader will include serving as a partner in and facilitator of neuroimaging research within the NIMH IRP; providing guidance on study design; and ensuring that appropriate standards of quality, rigor, and transparency are maintained. They will also act in coordination with the leaders of the Data Science and Sharing ( https://cmn.nimh.nih.gov/dsst) and Machine Learning Teams ( https://cmn.nimh.nih.gov/mlt) Finally, they will be responsible for management and supervision of approximately 9 full time staff members including software engineers, statisticians, and other biomedical science professionals. The successful candidate must be committed to scientific excellence and highly collaborative research, ensuring an immense impact on the fields of brain imaging and mental health research. Candidates must have earned a Ph.D. or M.D. and demonstrate experience as an outstanding scientist. Applicants must possess the ability to analyze, prioritize, and delegate resources while managing multiple projects. Expertise and experience should include demonstration of positive and collegial interactions with staff at all levels and the ability to communicate and promote their research, software, and scholarly contributions. Applicants should also have knowledge and experience in software engineering, including writing, distributing, maintaining, and supporting scientific software for a large user base while adhering to community recognized standards and practices. Please see the official posting https://cmn.nimh.nih.gov/compcore-job for more details, including instructions on how to apply.

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new Open Access Perspective
by Daniel Gardner 17 Feb '22

17 Feb '22

What do brains compute, and how do they do it? Has evolution conserved a small canonical set of computations performed by neural circuitry? In a just-published invited Perspective for the Journal of Computational Neuroscience, I present arguments for (and against) these fundamental questions. The title, Where are the cores in this thing? …and what are they computing? (with apologies to Larry Abbott) is of course an homage to Larry's 'Where are the switches on this thing?' It's Open Access and freely downloadable (tell your students and friends) at: https://link.springer.com/content/pdf/10.1007/s10827-021-00809-1.pdf The very first sentence is: "Evolution conserves neural components and connectivity—does this extend to computations and circuitry?" I go on to note that independent of specific microcircuit connectivity, some key neuronal and network properties, conserved across all nervous systems, may be essential for computation. Candidates include irregular firing, stochastic plastic synapses, alternate A/D PSPs/spikes, nonlinear f-I, cellular longevity, dynamic but stable networks with both fixed and adaptive features, and local processing linked by distant connectivity for coherence and modulation. Collegially, I invite discussion. I also urge neuroscientists to add these questions to those that guide their own research, and I offer community efforts to widen the scope. ...Daniel Gardner, Ph.D. dan(a)med.cornell.edu dg458(a)columbia.edu Head, Laboratory of Neuroinformatics Professor Physiology & Biophysics/Neurology/Neuroscience Weill Medical College of Cornell University lab: (212) 746-6373 cell: (917) 902-0654

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NEST Conference 2022 - registration is open
by Hans Ekkehard Plesser 17 Feb '22

17 Feb '22

Dear Colleagues, The NEST Initiative is excited to invite everyone interested in Neural Simulation Technology and the NEST Simulator to the NEST Conference 2022. The NEST Conference provides an opportunity for the NEST Community to meet, exchange success stories, swap advice, learn about current developments in and around NEST spiking network simulation and its application. We particularly encourage young scientists to participate in the conference! This year's conference will again take place as a virtual event on Thursday/Friday 23/24 June 2022. Register now! For more information please visit the conference website https://nest-simulator.org/conference We are looking forward to seeing you all in June! Hans Ekkehard Plesser and colleagues -- Prof. Dr. Hans Ekkehard Plesser Head, Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

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Postdoctoral Researcher in Medical Interactive Technologies
by Mastaneh Torkamani 17 Feb '22

17 Feb '22

The University of Eastern Finland is inviting applications for a Postdoctoral Researcher position in Medical Interactive Technologies on the Joensuu Campus. The position will be filled for a 2-year term from 1.3.2022 (or as agreed). Please find more information below and submit your application no later than 25.2.2022. We are looking for a highly motivated and self-driven Postdoctoral Researcher to work full-time on an interdisciplinary research project funded by the Academy of Finland: "Next generation sensory monitoring for improving microsurgical skills and performance" led by Associate Professor Roman Bednarik (https://www.uef.fi/en/web/int) As our new Postdoctoral Researcher in Medical Interactive Technologies, you will be working in the School of Computing at the Faculty of Science and Forestry, Joensuu. The project is in collaboration with Kuopio University Hospital, Department of Neurosurgery and Microsurgery Training Center, https://www.microsurgerycenter.com/. The research will focus on deep understanding of sensorimotor perception and action in image-guided surgeries. A large part of the research evolves around the visual and tactile perception that underlies surgeon’s high-level skills, i.e. eye-hand coordination, action planning, and decision making. Situated in bimanual surgical tasks, our research combines human factors, human-robot interaction, computational modeling, machine learning, and computer vision for intelligent skill monitoring and interaction with robotic assistance in surgical procedures. For more information, please see the job advert at https://rekry.saima.fi/certiahome/open_job_view.html?did=5600&jc=16&id=0000… Please submit your application by using our electronic application form no later than 25.2.2022 (by 24.00 hours Finnish time). For further information on the position, please contact associate Professor Roman Bednarik, e-mail roman.bednarik(a)uef.fi, tel. +358 29 4453621 For further information on the application procedure, please contact HR-secretary Noora Hämäläinen, e-mail noora.hamalainen(a)uef.fi, tel. +358 29 4458 302 Best regards, Mastaneh Torkamani Azar, Ph.D. Postdoctoral Researcher Interactive Technologies Research Group School of Computing University of Eastern Finland Email: mastaneh.torkamani(a)uef.fi https://sites.uef.fi/int/

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Postdoc position at UTSA
by Fidel Santamaria 16 Feb '22

16 Feb '22

As part of a collaboration with the AFRL, the laboratory of Dr Santamaria at UTSA is looking for a talented postdoc to computationally study how fast thermal gradients impact synaptic mechanisms in dendritic spines. This will be part of a collaborative project between UTSA, AFRL, and other universities where experiments and simulations will combine to understand fundamental plasticity processes in neuronal synapses. The results will have important practical implications in neuroscience and biomedical engineering. The selected person will work on developing deterministic and stochastic models of how biochemical signals, involved in synaptic plasticity, are affected by thermal gradients. Interested individuals should send a CV and cover letter to Dr. Santamaria (fidel.santamaria(a)utsa.edu) The position is for one year, with the possibility of renewal. This position is only open to American citizens. Applicants must have experience with Python or Matlab and a background in physics or engineering is preferred. _______________________________________________________________________________ Fidel Santamaria, PhD Professor Department of Neuroscience, Development, and Regenerative Biology University of Texas at San Antonio www.utsa.edu/SantamariaLab<http://www.utsa.edu/SantamariaLab> Office: BSB 1.03.30 Tel +1(210) 458 6910

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Special issue of SIAP on the life sciences
by Kresimir josic 14 Feb '22

14 Feb '22

SIAM Journal on Applied Mathematics (SIAP) invites contributions for a special section on the life sciences to highlight the use and development of mathematical models and analysis tools to address life sciences issues that are of true biological, medical, or industrial relevance. Papers submitted to this special section will be peer-reviewed, subject to the review criteria of SIAP. Papers will initially be handled by guest editors. The window for submissions runs from February 15 to June 30, 2022. For information about this issue please see: https://bit.ly/3LsPxcw <https://bit.ly/3LsPxcw>

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Third session of the Brains Through Time Reading Club
by manuel molano 14 Feb '22

14 Feb '22

Dear all, I would like to bring to your attention the third session of the Brains Through Time Reading Club<https://sites.google.com/view/bbtreadingclub/home>! It will be on February 23rd (4pm CEST / 10 EST) and will include the participation of Leonard Maler<https://www.uottawa.ca/brain/people/maler-leonard>, Idoia Quintana-Urzainqui<https://twitter.com/idoiaeu>, Luis Puelles<https://scholar.google.com/citations?user=nIoLKVAAAAAJ&hl=en> and Paul Cisek<https://cisek.org/pavel/>. We will discuss the main ideas of the third chapter of the book: The origin of jaws and paired fins. You can register HERE<https://www.crowdcast.io/e/brains-through-time-3>. And in case you missed the previous sessions, you can watch them HERE<https://www.youtube.com/channel/UCDWFS3MBL9OhmpmL6mFmxsg/featured>.

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Computational Neuroscience Summer school in South Africa, DEADLINE TOMORROW
by Tim Vogels 14 Feb '22

14 Feb '22

Dear all, This is a reminder that the application DEADLINE for the next IMBIZO is TOMORROW. If you, or anyone you know who would benefit from this opportunity please consider applying: IBRO-SIMONS COMPUTATIONAL NEUROSCIENCE IMBIZO #isiCNI2022 12 August - 4 September 2022, Noordhoek Beach, Cape Town, South Africa http://imbizo.africa/ <http://imbizo.africa/> Application deadline: 15th February 2022 The #isiCNI2022 is a southern hemisphere summer school aiming to promote computational neuroscience in Africa. It will bring together international and local students under the tutelage of the world's leading experts in the field. Like its international sister courses, this four-week summer school aims to teach central ideas, methods, and practices of modern computational neuroscience through a combination of lectures and hands-on project work. Mornings will be devoted to lectures on topics across the breadth of computational neuroscience, including experimental underpinnings and machine learning analogues. The rest of the day will be spent working on research projects under the close supervision of expert tutors and faculty. Individual research projects will focus on the modelling of neurons, neural systems, behaviour, the analysis of state-of-the-art neural data, and the development of theories to explain experimental observations. New this year is a week focused on neuroscience-inspired machine learning! Who should apply? This course is aimed at Masters and early-PhD level students though Honours or advanced undergraduates may also apply. Postdoctoral students who can motivate why the course would benefit them are also encouraged to apply, Students should have sufficient quantitative skills, (e.g. a background in mathematics, physics, computer science, statistics, engineering or related field). Some knowledge of neural biology will be useful but not essential. Experimental neuroscience students are encouraged to apply, but should ensure that they have a reasonable level of quantitative proficiency (i.e. at least second-year level mathematics or statistics and have done at least one course in computer programming). Please distribute this information as widely as you can. Essential details * Fee (which covers tuition, lodging, and meals): 1100 EUR Thanks to our generous sponsors, significant financial assistance is available to reduce and waiver fees for students, particularly for African applicants. We also hope to provide some travel bursaries for international students. If you are in need of financial assistance to attend the Imbizo, please state so clearly in the relevant section of your application. The Imbizo is planned to be hosted in person, with everyone following our COVID policy <https://imbizo.africa/covid-policy/>. If it is unsafe to hold the summer school, we will follow up with further information at the appropriate time. * Application deadline: 15th February 2022 * Notification of results: late April 2022 Information and application https://imbizo.africa/ <https://imbizo.africa/> Questions? isicn.imbizo(a)gmail.com <mailto:isicn.imbizo@gmail.com> What is an Imbizo? \ɪmˈbiːzɒ\ | Xhosa - Zulu A gathering of the people to share knowledge. FACULTY Demba Ba - Harvard University Adrienne Fairhall - University of Washington Peter Latham - University College London Daphne Bavelier - University of Geneva Timothy Lillicrap - DeepMind Jonathan Pillow - Princeton University Joseph Raimondo - University of Cape Town Mackenzie Mathis - EPFL Lausanne Athanassia Papoutsi - IMBB-FORTH Evan Schaffer - Columbia University Henning Sprekeler - Technical University of Berlin Thomas Tagoe - University of Ghana Tim Vogels - Institute of Science and Technology Austria Blake Richards - McGill University Alex Pouget - University of Geneva TUTORS Mohamed Abdelhack - Krembil Centre for Neuroinformatics Annik Carson - McGill University Spiros Chavlis - IMBB-FORTH Christopher Currin - Institute of Science and Technology Austria Sanjukta Krishnaopal - University College London Marjorie Xie - Columbia University ORGANISERS Demba Ba (Harvard University) Christopher Currin (Institute of Science and Technology Austria) Peter Latham (Gatsby Unit for Computational Neuroscience) Joseph Raimondo (University of Cape Town) Emma Vaughan (Imbizo Logistics) Tim Vogels (Institute of Science and Technology Austria) Sponsors The isiCNI is made possible by the generous support from the Simons Foundation <https://www.simonsfoundation.org/> and the International Brain Research Organisation (IBRO) <https://ibro.org/>, as well as the Wellcome Trust <https://wellcome.org/>, Deep Mind <https://deepmind.com/> and Wits University <https://www.wits.ac.za/> Organizational Affiliates University of Cape Town, University College London, Institute of Science and Technology Austria, TReND in Africa <http://trendinafrica.org/>, Neuroscience Institute <http://www.neuroscience.uct.ac.za/>, Gatsby Foundation <http://www.gatsby.org.uk/>, IBRO African Center for Advanced Training in Neurosciences at UCT

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[Jobs] Available Position: Professor in Artificial Intelligence (AI) at the University of Plymouth, UK
by Amir Aly 12 Feb '22

12 Feb '22

Dear All, *Apologies for cross-posting* *The School of Engineering, Computing, and Mathematics (SECaM)*, at the University of Plymouth has a unique opportunity for an outstanding academic and their team to join the School and strengthen our research, leadership, and collaboration in *Artificial Intelligence*. This is an opportunity to establish senior academic direction and growth in this core area of Artificial Intelligence and to build on multi-disciplinary collaboration, supporting the School’s strategic objectives to create a critical mass of expertise in the area of Artificial Intelligence aligning directly with Industry 4.0 and future national and international research opportunities and skills development needs. You will work together with colleagues to create a vision for our existing Centre for Robotics and Neural Systems (CRNS), which builds on the world-leading and international excellence performance in the field of computer science, social and cognitive robotics, neural computation, and others. You will join a community of over 100 staff and 2000 students who work alongside one another in world-leading facilities. This synergistic mix of academic disciplines has research strength aligned with challenges of the fourth Industrial Revolution, clean growth, digitalization, autonomy, and health technology, helping to develop pioneering, innovative solutions to real-world problems that have a genuinely positive impact upon society. The deadline is 25th February. For more information and to apply, please visit: https://hrservices.plymouth.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.o… <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fhrservice…> Regards ---------------- *Dr. Amir Aly* Lecturer in Artificial Intelligence and Robotics Center for Robotics and Neural Systems (CRNS) School of Engineering, Computing, and Mathematics Room B332, Portland Square, Drake Circus, PL4 8AA University of Plymouth, UK

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Running your new lab: tips and tricks - Panel discussion - 10th March 2022, 12h GMT / 13h CET
by Sidarus, Nura 11 Feb '22

11 Feb '22

Running your new lab: tips and tricks 10th March 2022 12h GMT / 13h CET Online To commemorate International Women's Day, we are delighted to host this practical panel discussion to provide support and inspiration for starting and running a lab. Save the date and do not miss the opportunity to share experiences with leading women scientists in cognitive sciences across Europe. Details and registration: https://www.eventbrite.co.uk/e/running-your-new-lab-tips-and-tricks-tickets… Our panel: * Prof Nivedita Mani, Professor of Psychology of Language, Georg-August-Universität Göttingen, Germany * Dr Jessie Ricketts, Reader in Psychology, Department of Psychology, Royal Holloway, University of London, UK * Prof Agnieszka Wykowska, Professor in Social Cognition in Human-Robot Interaction, Istituto Italiano di Tecnologia (IIT), Genova, Italy Organised and facilitated by Nura Sidarus (Royal Holloway University of London) & co-facilitated by María Jesús Maraver (Universidade de Lisboa). Supported by Women in Cognitive Science - Europe (WiCS-E) & Royal Holloway University of London. __________________________________________________________ Dr Nura Sidarus (she/her) Lecturer | Department of Psychology Royal Holloway University of London | Egham | Surrey | TW20 0EX Office: Wolfson 248 | Tel: +44 (0) 1784 44 3717 Affiliate Member | Institute of Cognitive Neuroscience, UCL nura.sidarus(a)rhul.ac.uk<mailto:%20nura.sidarus@rhul.ac.uk> | www.nurasidarus.com<http://www.nurasidarus.com/> __________________________________________________________ This email, its contents and any attachments are intended solely for the addressee and may contain confidential information. In certain circumstances, it may also be subject to legal privilege. Any unauthorised use, disclosure, or copying is not permitted. If you have received this email in error, please notify us and immediately and permanently delete it. Any views or opinions expressed in personal emails are solely those of the author and do not necessarily represent those of Royal Holloway, University of London. It is your responsibility to ensure that this email and any attachments are virus free.

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crowd-sourcing COSYNE post-review score sheet
by PERRINET Laurent 11 Feb '22

11 Feb '22

Dear community COSYNE is a great conference which plays a pivotal role in our field. Raw numbers we were given are * 881 submitted abstracts * 215 independent reviewers * 2639 reviews If you have submitted an abstract (or several) you have recently received your scores. I am not affiliated to COSYNE - yet I would like to contribute in some way and would like to ask one minute of your time to report the raw scores from your reviewers: https://forms.gle/p7eG1p6dJAkr4Cyg7 (Do one form per abstract.) For this crowd-sourcing effort to have a most positive impact, I will share the results and summarize in a few lines them in one week time (11/02). The more numerous your feedbacks, the higher the precision of results! Thanks in advance for your action, Laurent PS: if any similar initiative already exists, I'll be more than willing to receive feedback -- Laurent Perrinet - INT (UMR 7289) AMU/CNRS https://laurentperrinet.github.io/

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12 Postdoctoral positions - Ruhr University Bochum
by Vinita Samarasinghe 11 Feb '22

11 Feb '22

*12 postdoctoral positions (min. 3 years) in Neuroscience, Psychology, and Philosophy of Mind*** The Ruhr University Bochum and the University of Duisburg-Essen are among Germany’s leading research universities. They draw their strength from both the diversity and the proximity of natural sciences, humanities, and engineering disciplines on coherent campuses. These highly dynamic settings enable researchers to work across traditional boundaries of academic subjects and faculties. *We are searching for advanced postdocs who ideally already have ca. 2 years of research experience*and want to continue their careers in an inspiring environment that fosters interdisciplinary approaches. We aim to install an outstanding group of postdocs, starting on 1^st of April 2022 at the earliest, who are tightly integrated with the research focus “THINK@Ruhr”. Details of this research program as well as all further procedural details are outlined on the website: _*www.thinkatruhr.de* <http://www.ThinkAtRuhr.de/>_. Deadline of application is February 27, 2022. *Applicants should have *an excellent PhD in a research topic related to neuroscience, psychology, or philosophy of mind and should already have published in high-ranking peer-reviewed journals. The postdoc positions offer a focus on research only (no teaching or administration). It is expected that the successful candidate will submit a grant proposal to establish her/his own research group (e.g. ERC Starting Grant, Emmy Noether Research Grant, Sofja Kovalevskaja Award, etc.) during the postdoctoral period. Candidate selection will be based on whether submission of such a proposal is a realistic goal in addition to usual measures of scientific excellence. The candidates will be associated with faculty members who are named on the website thinkatruhr.de. THINK@Ruhr will foster and support any research activities of the postdocs. Our universities offer attractive academic career track options and family friendly conditions. For more information including application procedure and contact information please visit https://thinkatruhr.de/what-we-offer/

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PostDoc position in Göttingen: Retina research and computational neuroscience
by Gollisch, Tim 11 Feb '22

11 Feb '22

An exciting full-time postdoc position is available in the lab of Tim Gollisch at the University Medical Center Göttingen, Germany. The project centers on investigating information processing and neural coding in the neural network of the vertebrate retina, using a combination of experimental recordings with computational modeling and data analysis. The postdoc will contribute to our ongoing work under the ERC Consolidator Grant project CODE4Vision (https://www.retina.uni-goettingen.de/code4vision/) The work includes participation in recordings from the isolated retina (mostly mouse) with multielectrodes, using both wild-type retinas and optogenetic retina models of vision restoration therapy. Patch-clamp recordings are also a possibility. A strong focus will then be to combine these experiments with novel tools for data analysis and mathematical modeling, using cascade-type models (linear-nonlinear models and beyond), artificial neural networks, or machine-learning techniques to analyze the retinal network. Our research group is integrated into the strong and lively neuroscience research community of Göttingen, including the university, several Max Planck Institutes, the German Primate Center, and the European Neuroscience Institute. We are also part of the Bernstein Center for Computational Neuroscience Göttingen and of the Collaborative Research Centers "Cellular Mechanisms of Sensory Processing" (http://sfb889.uni-goettingen.de/) and "Mathematics of Experiment" (https://www.uni-goettingen.de/en/628179.html) For more information about the research group, please visit the group's website: https://www.retina.uni-goettingen.de/. We are looking for a highly motivated scientist with a good background in electrophysiology or computational/theoretical neuroscience. Experience in both of these areas is a bonus, but not required. Experience in computer programming or in scripting of data analysis routines is also a plus. The position is for 2 years initially with the possibility for renewal. Please send your application to Tim Gollisch (tim.gollisch(a)med.uni-goettingen.de<mailto:tim.gollisch@med.uni-goettingen.de>), including a CV, a statement of what interests you about the group's work, and contact details for two references. The University Medical Center Göttingen is an equal opportunities employer, and women are especially encouraged to apply. Applicants with disabilities and equal qualifications will be given preferential treatment.

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Groningen Spring School on Cognitive Modelling (4 to 8 April 2022)
by Thomas 11 Feb '22

11 Feb '22

Date: 4 to 8 April 2022 Location: Groningen, the Netherlands Fee: € 300 (late fee after March 7 will be € 350) www.cognitive-modeling.com/springschool After an enforced two-year covid break, we are excited to announce the fifth Groningen Spring School on Cognitive Modeling (4 to 8 April 2022), with a great lineup of speakers. The Spring School will cover four different modeling paradigms: ACT-R, Nengo, PRIMs, and discriminative learning. It thereby offers a unique opportunity to learn the relative strengths and weaknesses of these approaches. In addition, this year we are offering a lecture series on dynamical systems, which should be interesting for anyone looking into modeling cognitive dynamics at some or other level of abstraction. We recommend this lecture series as an excellent combination with Nengo, for those interested in neuromorphic computing. The first day will provide an introduction to all five topics. From day two, spring school students will be asked to commit to one topic, for which they will attend lectures as well as hands-on tutorials to get practical experience at working with the paradigm. In addition, students can sign up for a second topic, for which they will attend lectures only. All students are invited to join a series of plenary research talks on the different paradigms. Please feel free to forward the information to anyone who might be interested in the Spring School. The Spring School team PS: Please note that, due to its interactive character, the spring school will be held as an offline-only event. We will not offer the option for hybrid or online teaching. In case the spring school needs to be cancelled at the last minute after all, participants will receive a full reimbursement. ______________ ACT-R Teachers: Jelmer Borst, Stephen Jones, & Katja Mehlhorn (University of Groningen) Website: http://act-r.psy.cmu.edu. ACT-R is a high-level cognitive theory and simulation system for developing cognitive models for tasks that vary from simple reaction time experiments to driving a car, learning algebra, and air traffic control. ACT-R can be used to develop process models of a task at a symbolic level. Participants will follow a compressed five-day version of the traditional summer school curriculum. We will also cover the connection between ACT-R and fMRI. Nengo Teacher: Terry Stewart and Andreas Stöckel (University of Waterloo) Website: http://www.nengo.ca Nengo is a toolkit for converting high-level cognitive theories into low-level spiking neuron implementations. In this way, aspects of model performance such as response accuracy and reaction times emerge as a consequence of neural parameters such as the neurotransmitter time constants. It has been used to model adaptive motor control, visual attention, serial list memory, reinforcement learning, Tower of Hanoi, and fluid intelligence. Participants will learn to construct these kinds of models, starting with generic tasks like representing values and positions, and ending with full production-like systems. There will also be special emphasis on extracting various forms of data out of a model, such that it can be compared to experimental data. PRIMs Teacher: Niels Taatgen (University of Groningen) Website: https://www.ai.rug.nl/~niels/prims/index.html How do people handle and prioritize multiple tasks? How can we learn something in the context of one task, and partially benefit from it in another task? The goal of PRIMs is to cross the artificial boundary that most cognitive architectures have imposed on themselves by studying single tasks. It has mechanisms to model transfer of cognitive skills, and the competition between multiple goals. In the tutorial we will look at how PRIMs can model phenomena of cognitive transfer and cognitive training, and how multiple goals compete for priority in models of distraction. Discriminative learning and the lexicon: NDL and LDL Harald Baayen, Yu-Ying Chuang, and Maria Heitmeier University of Tuebingen NDL and LDL are simple computational algorithms for lexical learning and lexical processing. Both NDL and LDL assume that learning is discriminative, driven by prediction error, and that it is this error which calibrates the association strength between input and output representations. Both words’ forms and their meanings are represented by numeric vectors, and mappings between forms and meanings are set up. For comprehension, form vectors predict meaning vectors. For production, meaning vectors map onto form vectors. These mappings can be learned incrementally, approximating how children learn the words of their language. Alternatively, optimal mappings representing the endstate of learning can be estimated. The NDL and LDL algorithms are incorporated in a computational theory of the mental lexicon, the ‘discriminative lexicon’. The model shows good performance both with respect to production and comprehension accuracy, and for predicting aspects of lexical processing, including morphological processing, across a wide range of experiments. Since mathematically, NDL and LDL implement multivariate multiple regression, the ‘discriminative lexicon’ provides a cognitively motivated statistical modeling approach to lexical processing. In this course, we will show how comprehension and production of morphologically complex words can be modeled successfully with the "Discriminative Lexicon" model for a range of languages (Hebrew, Maltese, English, German, Dutch, Mandarin Chinese, Korean, Kinyarwanda, Estonian, and Finnish). We will discuss the kinds of form and meaning representations that can be set up, including form features derived from the speech signal for auditory comprehension and semantic features grounded in distributional semantics. Furthermore, we will provide a survey of the measures that can be derived from the model mappings to predict empirical response variables such as reaction times in primed and unprimed lexical decision, spoken word duration, and tongue movements during speaking. Finally, participants will receive some training in using the JudiLing package for Julia. This package provides optimized code for implementing and evaluating components of a "discriminative lexicon" for a given language. Dynamical Systems: a Navigation Guide Teacher: Herbert Jaeger (University of Groningen) This lecture series gives a broad overview over the zillions of formal models and methods invented by mathematicians and physicists for describing “dynamical systems”. Here is a list of covered items: Finite-state automata (with and without input, deterministic and non-deterministic, probabilistic), hidden Markov models and partially observable Markov decision processes, cellular automata, dynamical Bayesian networks, iterated function systems, ordinary differential equations, stochastic differential equations, delay differential equations, partial differential equations, (neural) field equations, Takens’ theorem, the engineering view on “signals”, describing sequential data by grammars, Chomsky hierarchy, exponential and power-law long-range interactions, attractors, structural stability, bifurcations, phase transitions, topological dynamics, nonautonomous attractor concepts. In the lectures I work out the connecting lines between these different models and methods, aiming at drawing the "big picture". — Thomas Tiotto, PhD Candidate, CogniGron - Groningen Cognitive Systems and Materials University of Groningen Nijenborgh 9, 9747 AG Groningen, The Netherlands Email: t.f.tiotto(a)rug.nl Profile: https://www.rug.nl/staff/t.f.tiotto/ Office: 5161 0318

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Postdoctoral Fellowship in Machine Learning for Brain Connectivity in Clinical Neuroscience
by Paolo Avesani 11 Feb '22

11 Feb '22

A postdoctoral fellowship in Machine Learning for Brain Connectivity in Clinical Neuroscience We are pleased to announce the opening of one Postdoctoral Fellowship at the Neuroinformatics Lab, an interdisciplinary initiative between the Center for Mind/Brain Sciences (CIMeC) of the University of Trento, and the Center for Digital Health of Fondazione Bruno Kessler. The position is part of the “Neusurplan” project, an integrated approach to neurosurgery planning based on multimodal and longitudinal data. The goal is to pursue an integrated approach to pre-operative neurosurgical planning, combining structural and functional characterization of brain connectivity. The data driven strategy will take advantage of a unique dataset of intra-operative points of directed electrical stimulation and the related functional responses. In this project, the candidate will pursue research on machine learning methods for neuroimaging data analysis to study and characterize brain connectivity, with applications to longitudinal studies and clinical practice. The ideal candidate should have a mixed background in neuroimaging techniques and numerate disciplines, like computer science, engineering, physics, or mathematics. This project is in collaboration with the Division of Neurosurgery, S. Chiara Hospital, Trento (IT). The position is for a 2 year Postdoc Fellowship (May, 2022 - April, 2024). We welcome expressions of interest for this position, please contact Paolo Avesani (paolo.avesani@ <avesani(a)fbk.eu>unitn.it) and/or Emanuele Olivetti ( olivetti(a)fbk.eu) with your CV and a statement of intent. The University of Trento ranks among top Italian Universities ( https://www.unitn.it/en/ateneo/1636/rankings) Fondazione Bruno Kessler ranks first among the Italian research centers in Engineering and Computer Science ( https://magazine.fbk.eu/en/news/fbk-ranks-1st-in-italy-for-scientific-excel… ). To also consider a work/life balance, there is more than our passion for translational research. You can check these pointers for a flavor of life quality in Trentino: https://www.visittrentino.info/en; https://www.discovertrento.it/en A few papers related to the project are below: Bertò G,et al., (2021) Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation, Neuroimage, 224 https://doi.org/10.1016/j.neuroimage.2020.117402 Sarubbo S, et al., (2020) Mapping critical cortical hubs and white matter pathways by direct electrical stimulation: an original functional atlas of the human brain, Neuroimage, 205 https://doi.org/10.1016/j.neuroimage.2019.116237 Astolfi P, et al., (2020) Tractogram filtering of anatomically non-plausible fibers with geometric deep learning, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) LNCS, vol 12267. Springer https://doi.org/10.1007/978-3-030-59728-3_29 Sarubbo S, et al., (2021) Planning brain tumor resection using a probabilistic atlas of cortical and subcortical structures critical for functional processing: a proof of concept, Operative Neurosurgery, 20(3), 175-183 https://doi.org/10.1093/ons/opaa396 -- -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

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Postdoc position - Computational Neuroscience - Ruhr University Bochum
by Vinita Samarasinghe 10 Feb '22

10 Feb '22

Deadline Extended! Prof. Sen Cheng, Institute for Neural Computation at the Ruhr University Bochum, invites applications for a full time *Postdoctoral position* (TV-L E13) in Computational Neuroscience. The position starts on July 1, 2022 and is funded for three years. The successful applicant will work on a collaborative project (within the Collaborative Research Center “Extinction Learning” (SFB 1280 <https://sfb1280.ruhr-uni-bochum.de/en/home/>)), together with experimentalists to: * analyze learning dynamics in behavioral, neural, and psychophysiological data, which will be collected by other projects within the SFB 1280, * compare the learning dynamics between individuals, species, learning phases and learning paradigms, * develop algorithms to analyze the learning dynamics, * develop and study computational models of learning dynamics, * coordinate research with other participating projects. Candidates must have: * a doctorate degree in neuroscience, physics, mathematics, electrical/biomedical engineering or a closely related field, * relevant experience in mathematical modeling, * excellent programming skills (e.g., Python, C/C++, Matlab), * excellent communication skills in English, * the ability to work well in a team. Research experience in neuroscience would be a further asset. The position is third party funded and does not have any formal teaching duties attached. The research group is highly dynamic and uses diverse computational modeling approaches including biological neural networks, cognitive modeling, and machine learning to investigate learning and memory in humans and animals. For further information see www.rub.de/cns. The Ruhr University Bochum is home to a vibrant research community in neuroscience and cognitive science. The Institute for Neural Computation is an independent research unit and combines different areas of expertise ranging from experimental and theoretical neuroscience to machine learning and robotics. The Institute for Neural Computation focuses on the dynamics and learning of perception and behavior on a functional level but is otherwise very diverse, ranging from neurophysiology and psychophysics over computational neuroscience to machine learning and technical applications. Please send your application, including CV, transcripts and research statement electronically, as a *single PDF file*, to *samarasinghe(a)ini.rub.de*. In addition, at least two academic references must be sent independently to the above email address. The deadline for applications is *February 20, 2022*. Travel costs for interviews will not be reimbursed. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. We are committed to providing a supportive work environment for female researchers, in particular those with young children. Our university provides mentoring and coaching opportunities specifically aimed at women in research. We have a strong research network with female role models and will provide opportunities to network with them. Wherever possible, events will be scheduled during regular childcare hours. Special childcare will be arranged if events have to be scheduled outside of regular hours, in case of sickness and during school or daycare closures. Where childcare is not an option parents will be offered a home office solution. If you have any questions please feel free to get in touch with Vinita Samarasinghe (contact below) -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/73 Postfachnummer 110 Universitätstr. 150 D-44801 Bochum Tel: +49 (0)234 32 27996 Email:samarasinghe@ini.rub.de

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4 PhD/postdoc positions in ML for neuroscience, cognitive science and physics
by Ecker, Alexander 09 Feb '22

09 Feb '22

We have four open positions for PhD students or postdocs in the Neural Data Science Lab at the Campus Institute Data Science (University of Göttingen) and the Max Planck Institute for Dynamics and Self-Organization in Göttingen, Germany. If you want to work with us on exciting projects developing machine learning methods for neuroscience, cognitive science and physics, please check out the three short project descriptions below and apply now. Details can also be found on our website: https://eckerlab.org/applications/ Application documents including a short motivation letter, CV, transcript of records (PhD students) and the contact details of two references should be sent to Alexander Ecker: ecker(a)cs.uni-goettingen.de<mailto:ecker@cs.uni-goettingen.de> We value diversity and equality. We therefore particularly encourage international and female applicants as well as applications from underrepresented groups or candidates with disabilities. ============ *(1) Data-driven multi-modal discovery of cell types in the neocortex* Understanding the relationship between structure and function of cortical neurons and circuits is one of the key challenges in neuroscience. In this project, we develop deep learning methods for data-driven identification of excitatory cell types in the visual cortex and to understand how a neuron’s morphology relates to its function. We will harness a unique large-scale functional anatomy dataset: a combination of electron-microscopy reconstructions at sub-micrometer resolution with two-photon functional imaging of nearly all excitatory neurons in one cubic millimeter of the mouse visual cortex. Role: Postdoc (preferred) or PhD student Your profile: Background in systems / computational neuroscience or machine learning (deep learning in particular). Experience with both is a strong plus, but not a requirement. This project is funded by the European Research Council through an ERC Starting Grant and in tight collaboration with Andreas Tolias' lab at Baylor College of Medicine, Houston, TX, USA. Regular visits at our collaborator’s lab in Houston are possible/encouraged. ============ *(2) Action Capture Platform: Deep learning for movement analysis and action classification* Studying social interactions and the underlying cognitive processes in humans and nonhuman primates requires observing and quantifying their behaviour, including body and head orientation, both in interactive lab settings and in the wild. The long-term goal of this project is to develop methods for automated, video-based recognition, motion tracking, and pose estimation of individual nonhuman primates as well as recognition of action types and inter-agent interactions in groups of primates freely moving primaates. We strive for generalisation across a range of primate species and varying real-world environmental conditions without the need to acquire detailed keypoint annotations in every context. The automated behavioural analysis tools developed in this project constitute a key enabling technology for a Collaborative Research Center focused on studying the Cognition of Interaction. Role: Postdoc (preferred) or PhD student Your profile: Strong background in machine learning (deep learning in particular) and/or computer vision. Experience with congitive science is a strong plus, but not a requirement. This project is funded by the German Research Foundation (DFG) as part of Collaborative Research Center SFB 1528 – Cognition of Interaction and in collaboration with several groups at the German Primate Center: Julia Ostner, Claudia Fichtel, Julia Fischer ============ *(3) Holography reconstruction using deep learning* Digital in-line holography is a very powerful method to investigate particles in turbulent fluid flows such as atmospheric clouds, aerosols, etc. using the diffraction patterns of the particles illuminated by coherent light. Currently, wider use of the technique is held back both by a data processing bottleneck and the degradation in hologram quality in field measurements compared to laboratory experiments due to the physical environment. In this project, we will train machine learning algorithms to reconstruct holograms using a combination of real holograms from the lab and the field and simulated datasets. We will start with simple idealized Lorenz-Mie theory, but later extend to full wave-equation calculations including non-flat and non-Gaussian beams, realistic defects in the optical components, dirty optics, camera micro-lens arrays, pixel cross-talk and digitization errors, non-spherical particles including ice crystals, aggregate particles with different indices of refraction, non-perfect collimation, non-perfect alignment, spatial variation in the index of refraction of the air in the view volume due to temperature gradients, multi-scattering from multiple particles, etc. Role: Postdoc (preferred) or PhD student Your profile: Strong background in physics. Experience with machine learning (deep learning in particular) and computer vision is a strong plus, but not a requirement. This project is in collaboration with the lab of Eberhard Bodenschatz and funded by the Max Planck Institute for Dynamics and Self-Organization. ============ -- Alexander Ecker Professor of Data Science Department of Computer Science • Campus Institute Data Science University of Göttingen • Max Planck Inst. for Dynamics and Self-Organization Goldschmidtstr. 1 • room 2.137 • 37077 Göttingen https://eckerlab.org • @alxecker • +49 551 39-21272

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On behalf of Michele Ferrante: New Funding Opportunity: Neuro-Glia Computational Mechanisms Governing Complex Behaviors
by Reinoud Maex 09 Feb '22

09 Feb '22

Begin forwarded message: From: Michele Ferrante <mferran1(a)gmu.edu<mailto:mferran1@gmu.edu>> Subject: New Funding Opportunity: Neuro-Glia Computational Mechanisms Governing Complex Behaviors Date: 4 February 2022 at 11:04:45 GMT To: <comp-neuro-owner(a)neuroinformatics.be<mailto:comp-neuro-owner@neuroinformatics.be>> New Funding Opportunity: Neuro-Glia Computational Mechanisms Governing Complex Behaviors https://grants.nih.gov/grants/guide/notice-files/NOT-MH-22-090.html Purpose Background and Rationale This Notice of Special Interest (NOSI) encourages projects to experimentally test mechanistic hypotheses on the role of neuro-glia activity coupling in modulating complex behaviors. The human brain regulates complex behavior by processing information across ~170 billion cells, including ~86 billion neurons and ~84 billion glial cells. The influence of glial cell types (i.e., astrocytes, oligodendrocytes, and microglia) on neural activity may explain behavioral processes across broad spatio-temporal scales and hierarchies. For example, astrocytes may regulate cognitive functions by releasing gliotransmitters that activate hundreds of neuronal synapses at once, regulating system-level short-/long-term plasticity. Activity changes in neuro-oligodendrocytes networks may dynamically regulate myelin axon-sheathing, which in turn may affect action potential conduction, neuronal spike timing, and oscillations linked to cognitive/social/affective processes. Finally, microglia activity-dependent synaptic pruning may alter behaviorally activated neural networks over long time scales. Discovering how mechanistic dysfunctions in neuro-glia interactions may alter behavioral phenotypes relevant to mental health is a challenge with potentially high translational impact. Studying how neuro-glia activity coupling affects complex behavior has been challenging in part due to technical barriers. For example, until recently, the field lacked reliable and selective tools to manipulate glial cells. Biotechnology is now expanding the range of possible investigations into glial function by providing new methods necessary to record and manipulate glial cells with mouse lines and viral methods expressing designer reporters, sensors, and actuators of glial activity. Advances in metabolic imaging and genetically encoded activity measurements allow for simultaneous observation of interactions in neurons and glial activity. Tools are also available for selectively stimulating and silencing glia cells’ calcium signaling in-vivo through designer receptors exclusively activated by designer drugs (DREADDs) and optogenetics. In parallel, basic behavioral neuroscience has been rapidly advanced by integrating system-level neurotechnology with computational modeling. Computational models (e.g., reinforcement learning, drift-diffusion, Bayesian, biophysically realistic, dynamical systems, and deep neural networks) have directly linked behavioral parameters and the neural substrates that compute them, but the role of non-neuronal cells in these computations have been largely ignored. Thus, the integration of computational modeling approaches to investigate neuro-glia interactions could provide new perspectives on how they enable complex behavior and how they become altered in mental illnesses. Combining newly developed experimental methods for recording and controlling neuro-glia activity with rigorous computational approaches may inform mechanistic models of how neuro-glia interactions may compute or fail to compute cognitive and socio-affective functions relevant to neuropsychiatric disorders. Responsive Areas of Research Examples of research areas that may be included in applications submitted under this NOSI include, but are not limited to, the application of existing or novel: * Experimental methods to measure or control glial activity in behaving animals to elucidate the role of neuro-glia activity in cognitive or socio-affective behaviors. * Biologically inspired computational approaches to provide a mechanistic explanation of the consequences of neuro-glia interactions during cognitive or socio-affective behaviors. * Computational models able to map fine-grained cognitive or socio-affective behavioral parameters onto neuro-glia computations. * Neuro-glia computational principles or mechanistic knowledge derived from animal experiments in Basic Experimental Studies Involving Humans (BESH). Applications must include both: * A well-conceived scientific rationale, question, and/or hypothesis grounded in cognitive or socio-affective science, where neuro-glia activity may mechanistically explain a complex behavior. * Measurement or control neuro-glia activity during complex behavior. Applications proposing to exclusively investigate the effects of glial cells on behavior will be considered responsive to this NOSI, but applications including measurement and/or manipulation of both glia and neurons will be given higher priority. Applications Not Responsive to this NOSI * Applications that do not include all the items contained in the “applications must include” section above are not responsive to this NOSI and will not be reviewed. * Applications exclusively focused on in-vitro preparations - without an in-vivo behavioral component - are not responsive to this NOSI and will not be reviewed. * Applications proposing to apply animal models of mental disorders or use broad batteries of behavioral tests in animals to address constructs that are accessible only in humans by self-report, such as “depression” or “anxiety,” are non-responsive to this NOSI. For additional information on NIMH’s guidelines and priorities for animal neurobehavioral approaches applicants are strongly encouraged to review NOT-MH-19-053<https://grants.nih.gov/grants/guide/notice-files/NOT-MH-19-053.html>. Note: NIMH only accepts mechanistic studies that meet NIH's definition of a clinical trial through PA-20-183<https://grants.nih.gov/grants/guide/pa-files/PA-20-183.html> and PA-20-184<https://grants.nih.gov/grants/guide/pa-files/PA-20-184.html>. Applications directed to NIMH for intervention development must be submitted through PAR-21-130<https://grants.nih.gov/grants/guide/pa-files/PAR-21-130.html>. For further information on NIMH clinical trial policies, see NOT-MH-20-105<https://grants.nih.gov/grants/guide/notice-files/NOT-MH-20-105.html> and NOT-MH-19-006<https://grants.nih.gov/grants/guide/notice-files/NOT-MH-19-006.html>. Application and Submission Information This notice applies to due dates on or after June 5, 2022 and subsequent receipt dates through May 8, 2025. Submit applications for this initiative using one of the following funding opportunity announcements (FOAs) or any reissues of these announcement through the expiration date of this notice. * PA-20-184<https://grants.nih.gov/grants/guide/pa-files/PA-20-184.html> - Research Project Grant (Parent R01 Basic Experimental Studies with Humans Required) * PA-20-185<https://grants.nih.gov/grants/guide/pa-files/PA-20-185.html> - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed) * PA-20-196<https://grants.nih.gov/grants/guide/pa-files/pa-20-196.html> - NIH Exploratory/Developmental Research Grant Program (Parent R21 Basic Experimental Studies with Humans Required) * PA-21-219<https://grants.nih.gov/grants/guide/pa-files/pa-21-219.html> - Joint NINDS/NIMH Exploratory Neuroscience Research Grant (R21 Clinical Trial Optional) * PA-21-235<https://grants.nih.gov/grants/guide/pa-files/pa-21-235.html> - NIMH Exploratory/Developmental Research Grant (R21 Clinical Trial Not Allowed) * PAR-21-175<https://grants.nih.gov/grants/guide/pa-files/PAR-21-175.html> - Understanding and Modifying Temporal Dynamics of Coordinated Neural Activity (R01 Clinical Trial Optional * PAR-21-176<https://grants.nih.gov/grants/guide/pa-files/PAR-21-176.html> - Understanding and Modifying Temporal Dynamics of Coordinated Neural Activity (R21 Clinical Trial Optional) All instructions in the SF424 (R&R) Application Guide<https://grants.nih.gov/grants/how-to-apply-application-guide.html> and the funding opportunity announcement used for submission must be followed, with the following additions: * For funding consideration, applicants must include “NOT-MH-22-090” (without quotation marks) in the Agency Routing Identifier field (box 4B) of the SF424 R&R form. Applications without this information in box 4B will not be considered for this initiative. Applications nonresponsive to terms of this NOSI will not be considered for the NOSI initiative. Inquiries Please direct all inquiries to the contacts in Section VII of the listed funding opportunity announcements with the following additions/substitutions: Scientific/Research Contact(s) Michele Ferrante, Ph.D. National Institute of Mental Health (NIMH) Telephone: 301-435-6782 Email: ferrantem(a)nih.gov<mailto:michele.ferrante@nih.gov> Andrew Breeden, Ph.D. National Institute of Mental Health (NIMH) Telephone: 301-443-1576 Email: andrew.breeden(a)nih.gov<mailto:andrew.breeden@nih.gov>

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PostDoc position at UCL: endogenous brain fluctuations and decision making
by Tobias U. Hauser 08 Feb '22

08 Feb '22

PostDoc position in real-time fMRI at Max Planck UCL Centre for Computational Psychiatry We are looking for a PostDoc to work on an exciting project investigating the role of endogenous brain fluctuations on decision making, funded by my ERC Starting Grant. In this project, we will investigate how endogenous, spontaneous fluctuations (aka resting-state fluctuations) influence behaviour. In our previous work (https://pnas.org/content/116/37/18732.short) we showed that moment-to-moment fluctuations affect risk taking behaviour. Here, we want to build on this and see how wide-reaching these effects are, and what the pharmacological bases of these effects are. We are looking for someone with expertise in advanced functional neuroimaging and preferably experience in real-time fMRI. We think that a postdoc with advanced understanding of time-series analyses and in-depth fMRI experience would be best suited for this position. Even though the general topic is set, own ideas and project ideas will very much appreciated & encouraged! The position is for 2 years (at the first instance) and will be based at the Max Planck UCL Centre for Computational Psychiatry and Ageing Research and the Wellcome Centre for Human Neuroimaging, located in Central London. If you have further questions, please contact Tobias Hauser (t.hauser(a)ucl.ac.uk) To read more about the research group, please see https://devcompsy.org/ Job advert here: https://atsv7.wcn.co.uk/search_engine/jobs.cgi?SID=amNvZGU9MTg4MjA4NSZ2dF90… -- Play smartphone games and help us understand the brain: www.brainexplorer.net Dr Tobias U. Hauser Sir Henry Dale Fellow, Principal Research Fellow Developmental Computational Psychiatry lab Max Planck UCL Centre for Computational Psychiatry & Ageing Research Wellcome Centre for Human Neuroimaging University College London 10-12 Russell Square London WC1B 5EH +44 207 679 5264 (internal: 45264) t.hauser(a)ucl.ac.uk www.tobiasuhauser.com www.devcompsy.org

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14 Open positions in neurotechnology R&D
by Eduardo López-Larraz 07 Feb '22

07 Feb '22

Bitbrain is a neurotechnology company that combines neuroscience, artificial intelligence, and hardware to develop innovative products. We are currently looking for 14 highly talented and enthusiastic individuals to join our R&D team. The profiles vary across the entire R&D pipeline of neurotechnology applications in healthcare: neuro/biomedical engineering, electronic engineering, software engineering, computer science, data science, project management, clinical neuropsychology, neuroscience lab assistants. More information and application procedure: https://www.bitbrain.com/careers -- Eduardo López-Larraz, PhD Research Scientist R&D Department eduardo.lopez(a)bitbrain.com Twitter <https://twitter.com/Edu_Lo_L> Scholar <https://scholar.google.com/citations?user=wLM67tAAAAAJ> LinkedIn <https://www.linkedin.com/in/edulop> www.bitbrain.com +34 931 444 823 info(a)bitbrain.com Facebook <https://www.facebook.com/BitbrainEN> Twitter <https://twitter.com/Bitbrain_EN> LinkedIn <https://www.linkedin.com/company/2070341>

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Fully funded PhD position (4 years)
by Michael Biehl 07 Feb '22

07 Feb '22

Apologies for multiple postings *Three weeks left to apply! * A *fully funded PhD position* (4 years) in the *Statistical **Physics of Neural Networks* is available at the University of Groningen, The Netherlands, see https://www.rug.nl/about-ug/work-with-us/job-opportunities/?details=00347-0… for details and application details. Applications (before March 1) are only possible through this webpage. The title of the project is "The role of the activation function for feedforward learning systems (RAFFLES)". For further information please contact Michael Biehl. ------------------------------------------------------------ Michael Biehl Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence P.O. Box 407, 9700 AK Groningen The Netherlands Tel. +31 50 363 3997 www.cs.rug.nl/~biehl m.biehl(a)rug.nl

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Cognitive & Computational Neuroscience postdoc
by Peter Dayan 05 Feb '22

05 Feb '22

Cognitive and Computational Neuroscientist Postdoctoral position to understand the function of long range connectivity in human cognition We are seeking a new colleague to work on a collaborative project studying human cognition between the laboratories of Professor Linda Richards<https://neuroscience.wustl.edu/people/linda-richards-phd/> at Washington University in St. Louis and Professor Peter Dayan<https://www.mpg.de/12309370/biological-cybernetics-dayan> at Max Planck Institute for Biological Cybernetics in Tubingen. The position will be based at Washington University in St. Louis. We are studying how people with corpus callosum dysgenesis, a major change in their global brain wiring connectivity, are able to process and integrate information during tasks involving decision making, social intelligence and memory. We are seeking a creative scientist with a background in cognitive neuroscience and computational neuroscience to develop analysis tools and pipelines and new models of cognitive function that will help guide our experimental approaches. Applicants should submit their CV and a cover letter explaining their background and interest in the position and working in both laboratories by April 4th, 2022. Please see job posting<https://wustl.wd1.myworkdayjobs.com/en-US/External/job/Washington-Universit…> for additional information. Linda J. Richards AO, FAA, FAHMS, PhD Edison Professor and Chair, Department of Neuroscience Director, McDonnell Center for Cellular & Molecular Neurobiology Washington University School of Medicine MSC 8108-12-8, 660 S. Euclid Avenue, St. Louis, MO 63110 Office Phone +1 314 362 4198; Cell Phone +1 314 532 7187 Linda.Richards(a)wustl.edu<mailto:Linda.Richards@wustl.edu> (My pronouns<https://www.mypronouns.org/>: she, her, hers)

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Assistant Professor / Postdoc Researcher in computational neuroscience and/or developmental robotics at the University of Tokyo
by nagai.yukie＠mail.u-tokyo.ac.jp 04 Feb '22

04 Feb '22

Dear colleagues, The International Research Center for Neurointelligence (IRCN) at the University of Tokyo is looking for highly motivated full-time Assistant Professor / Postdoc researchers in the field of computational neuroscience and/or developmental robotics. The selected candidates will join Cognitive Developmental Robotics Laboratory head by Prof. Yukie Nagai and investigate the underlying mechanisms of human cognitive development and disorders by means of computational approaches. Please send the required documents if you are interested in. Assistant Professor / Postdoc Researcher at IRCN, the University of Tokyo https://ircn.jp/wp-content/uploads/2021/12/20211220_IRCN_Nagai_lab_2EN.pdf Cognitive Developmental Robotics Laboratory (Nagai Lab) http://developmental-robotics.jp ---------- 1. Job title / Number of positions Project Research Associate or Project Researcher (Postdoctoral Fellow) / One or two 2. Employment period Starting Date: Negotiable Contract duration: until March 31, 2022 3. Renewable The contract is renewable on a fiscal year basis (from April 1 to March 31; every year) according to research budget, research activity, and research achievements. Contract duration is until March 31, 2026. 4. Place of work International Research Center for Neurointelligence, The University of Tokyo 7-3-1 Hongo, Bunkyo-ku Tokyo, 113-0033 JAPAN 5. Description Successful applicants will work in the fields of computational neuroscience, cognitive developmental robotics, machine learning, and relevant topics. They will investigate the principle of human cognitive development and disorders by modeling computational neural networks inspired by the human brain and/or analyzing human cognitive behaviors. Please see the lab homepage (https://developmental-robotics.jp/en/) for more details. 6. Salary and benefits Salary: To be determined in accordance with the University of Tokyo Regulations Commuter allowance: JPY55,000 per month at maximum No retirement benefits or bonuses 7. Qualifications - PhD in engineering, computer science, cognitive science, neuroscience, or relevant fields - Communication skills in English - Programming skills - Experiences in computational neuroscience and/or cognitive developmental robotics are preferred 8. Application documents (1) Cover letter (A4 1 page) (2) Curriculum vita (3) Publication list (4) Research plan (A4 2-3 pages) (5) Name, affiliation, and email address of two references, one of which should be a previous employer or supervisor 9. Submission Please send the application documents (PDF) to yukie(a)ircn.jp 10. Application deadline / Selection process When the position is filled All applications will be screened, and only those qualified will be scheduled for an interview (on-site or online). 11. Inquiries Please contact Prof. Yukie Nagai at IRCN, the University of Tokyo yukie(a)ircn.jp — Yukie Nagai, Ph.D. Project Professor, The University of Tokyo nagai.yukie(a)mail.u-tokyo.ac.jp | https://developmental-robotics.jp CREST Cognitive Mirroring: https://cognitive-mirroring.org CREST Cognitive Feeling: https://cognitive-feeling.jp

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Postdoc Position In Austin Texas
by Franco Pestilli 03 Feb '22

03 Feb '22

Dear Friends and colleagues We are looking for an enthusiastic you fellow to join us on a 2-year project funded by an NIH R01 by the BRAIN initiative. The project focuses on open science and data sharing standards. We are set to extend the Brain Imaging Data Structure (BIDS) to cover brain connectivity data. Here you can find a full description of the project. BIDS has become an exciting standard and the community is growing large: https://bids.neuroimaging.io/ A few papers relevant to the project are below: https://www.nature.com/articles/sdata201644 https://www.nature.com/articles/s41597-019-0104-8 https://www.nature.com/articles/sdata2018110 https://www.nature.com/articles/s41597-019-0105-7 https://www.biorxiv.org/content/10.1101/2021.06.16.448390v1 https://www.medrxiv.org/content/10.1101/2021.10.22.21265382v3 We would appreciate it if you could share this email with your trainees and younger colleagues. The project has a broad reach and could be a great base for developing further projects related to human neuroscience, neuroinformatics, computer science and machine learning depending on the interest of the applicant. Best regards, Project Leader Franco Pestilli co-Investigators Russ Poldrack, Stanford University, California, USA Ariel Rokem, University of Washington Seattle, Washington USA Theodore Satterthwaite, University of Pennsylvania, Pennsylvania, USA Other Personnel. Franklin Feingold, Stanford University, California, USA Eugene Duff, Imperial College, London, UK Cyril Pernet, Neurobiology Research Unit, Denmark Robert Smith, Florey Institute, Australia Oscar Esteban, Lausanne, Switzerland Matt Cieslak, University of Pennsylvania, Pennsylvania, USA *FRANCO PESTILLI*, *Ph.D.* | *Associate Professor* Department of Psychology <https://liberalarts.utexas.edu/psychology/index.php> | College of Liberal Arts <https://liberalarts.utexas.edu/> | The University of Texas at Austin <https://www.utexas.edu/> he/him | pestilli(a)utexas.edu | web <https://liberalarts.utexas.edu/psychology/faculty/fp4834> | GitHub <https://github.com/francopestilli> | brainlife.io CONFIDENTIALITY NOTICE: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message.

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CRNS Talk Series (2) - Live Talk by Dr. Rachid Alami - CNRS, France
by Amir Aly 02 Feb '22

02 Feb '22

Dear All * Apologies for cross posting* The *Center for Robotics and Neural Systems* (CRNS) is pleased to announce the talk of *Dr. Rachid Alami* who is a research director and team leader at the *National Center for Scientific Research* (CNRS), France on Wednesday, February 9th from *11:00 am* to *12:30* *pm* (*London time*) over *Zoom*. >> *Events*: The CRNS talk series will cover a wide range of topics including social and cognitive robotics, computational neuroscience, computational linguistics, cognitive vision, machine learning and AI, and applications to autism. More details are available here: https://www.plymouth.ac.uk/research/robotics-neural-systems/whats-on >> *Link for the next event (No Registration is Required)*: Join Zoom Meeting https://plymouth.zoom.us/j/98559430652?pwd=aDBpNWtZd3FZKzNVQ0FMbndxWjdWdz09… >> *Title of the talk*: Models and Decisional issues for Human-Robot Joint Action *Abstract*: This talk will address some key decisional issues that are necessary for a cognitive and interactive robot which shares space and tasks with humans. We adopt a constructive approach based on the identification and the effective implementation of individual and collaborative skills. The system is comprehensive since it aims at dealing with a complete set of abilities articulated so that the robot controller is effectively able to conduct in a flexible and fluent manner a human-robot joint action seen as a collaborative problem solving and task achievement. These abilities include geometric reasoning and situation assessment based essentially on perspective-taking and affordances, management and exploitation of each agent (human and robot) knowledge in a separate cognitive model, human-aware task planning and interleaved execution of shared plans. We will also discuss the key issues linked to the pertinence and the acceptability by the human of the robot behaviour, and how this influence qualitatively the robot decisional, planning, control and communication processes. >> If you have any questions, please don't hesitate to contact me, Regards ---------------- *Dr. Amir Aly* Lecturer in Artificial Intelligence and Robotics Center for Robotics and Neural Systems (CRNS) School of Engineering, Computing, and Mathematics Room B332, Portland Square, Drake Circus, PL4 8AA University of Plymouth, UK

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Entropy Special Issue : Formal Analysis of Deep Artificial Neural Networks
by Friedhelm Schwenker 01 Feb '22

01 Feb '22

Dear Researchers, The Entropy Journal (https://www.mdpi.com/journal/entropy) is currently running a Special Isuue on Formal Analysis of Deep Artificial Neural Networks <https://www.mdpi.com/journal/entropy/special_issues/DANN> (Deadline: *31 May 2022) *This Special Issue welcomes original research papers on the analysis of ANNs based on mathematically founded methods in general. Review articles describing the current state of the art of ANNs in the aforementioned contexts are highly encouraged. All submissions to this Special Issue must include substantial theoretical aspects of ANN research.* * Keywords * ANN architectures and learning in approximation and complexity theories * Cost functions and constraints in information-theoretic learning algorithms for ANNs * Complexity of deep, recurrent, or quantum ANN learning * Information-theoretic principles for sampling and feature extraction * Analysis of learning based on information-theoretic methods (e.g., information bottleneck approach) in deep, recurrent, or quantum ANNs * Applications of ANNs based on information-theoretic principles or quantum computing * Theoretical advances in quantum ANNs Please contact us: Edmondo Trentin <trentin(a)dii.unisi.it> or Friedhelm Schwenker <friedhelm.schwenker(a)uni-ulm.de> if you are interested in submitting your work. A number of waivers / discounts is available for interested authors. Best wishes, Friedhelm Schwenker Edmondo Trentin -- Prof. Dr. Friedhelm Schwenker University of Ulm Institute of Neural Information Processing D-89069 Ulm, Germany phone: +49-731-50-24159 fax: +49-731-50-24156 email:friedhelm.schwenker@uni-ulm.de www:http://www.uni-ulm.de/in/neuroinformatik/mitarbeiter/f-schwenker.html

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FLAIRS-35 May 15-18, 2022, Jensen Beach, Florida, Paper Deadline
by David B 01 Feb '22

01 Feb '22

FLAIRS-35 Special Track on Neural Networks and Data Mining The Florida Artificial Intelligence Research Symposium (FLAIRS) is an interdisciplinary conference which features double-blind reviewing, free tutorials, and a warm and sunny venue. Abstract Due Date: February 7, 2022 Submission Due Date: February 14, 2022 Conference: May 15-18, 2022 Jensen Beach, Florida Website: https://sites.google.com/view/flairs-35-nn-dm-track/home URL: https://www.flairs-35.info/call-for-papers Papers are being solicited for a special track on Neural Networks and Data Mining at the 35th International FLAIRS Conference (https://www.flairs-35.info/home) This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Papers and contributions are encouraged for any work related to neural networks, data mining, or the intersection thereof. Topics of interest may include (but are in no way limited to): applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Telecommunications, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy; algorithms such as new developments in Back Propagation, RBF, SVM, Deep Learning, Ensemble Methods, Kernel Approaches; hybrid approaches such as Neural Networks/Genetic Algorithms, Neural Network/Expert Systems, Causal Nets trained with Backpropagation, and Neural Network/Fuzzy Logic applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy; modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches; graph modeling, pattern discovery, and anomaly detection; feature extraction and selection; post-processing techniques such as visualization, summarization, or trending; preprocessing and data reduction; and knowledge engineering or warehousing. Questions regarding the track should be addressed to: David Bisant at bisant(a)umbc.edu, Steven Gutstein at s.m.gutstein(a)gmail.com, or Bill Eberle at weberle(a)tntech.edu.

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