- Comp-neuro - lists.cnsorg.org

Final reminder for participating in the Special Issue for the 15th Granada Seminar in Neurocomputing Journal (IF 4.072)
by Prof. Dr. Joaquín J. Torres Feb. 5, 2020

Feb. 5, 2020

Dear Colleague This is the final reminder for paper submission to the 15th Granada Seminar Special Issue we are editing in Neurocomputing journal (Q1, IF 4.072). If still you are interested to submit your contribution to this special issue, I would like to remember you that the final deadline for submissions has been extended to February 29th. Please follow the link below to submit your original contribution to this special issue: https://www.journals.elsevier.com/neurocomputing/call-for-papers/emergent-e… Once your are in the system in the "article type" choose "VSI: emergent effects in SNN" and continue the regular submission process Submission Final Deadline: February 29th 2020 Sincerely yours Joaquin J. Torres Guest Editor of the Special Issue -- Prof. Dr. Joaquín J. Torres Department of Electromagnetism and Physics of the Matter. Institute "Carlos I" for Theoretical and Computational Physics. University of Granada.

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Two PhD Positions at The University of Melbourne and Monash University, Australia
by David Grayden Feb. 5, 2020

Feb. 5, 2020

Creating subject-specific mathematical models to understand the brain The brain is a complex machine and brain function remains yet to be fully understood. This project works at the intersection of dynamical modelling, statistical signal processing, statistical inference and machine learning to develop subject specific mathematical models of the brain that can be used to infer brain states and monitor and image the brain. This work is centred around a neurophysiological variable estimation framework we have been developing that can be applied to all kinds of brain activity recordings. There are two projects to be completed under this program and we are looking for a different student for each of these projects. Project 1: specifically extend our neurophysiological variable estimation framework to different classes of neural population models validated from microscopic data. Project 2: specifically extend our neurophysiological estimation framework to coupled networks of neural population models applied to in vivo human recordings. These projects are critical for applications of our estimation framework to all kinds of neuroscientific studies (e.g. of rest, sensation, cognition, movement or abnormal behaviour) where different models and networks are more appropriate and parsimonious for different kinds of situations and will open new ways to understanding brain function. Please contact me directly if you are interested in applying. Regards, David Professor David B. Grayden Clifford Chair of Neural Engineering Dept of Biomedical Engineering Melbourne School of Engineering The University of Melbourne, Victoria 3010 Australia http://www.bme.unimelb.edu.au<http://www.bme.unimelb.edu.au/> | https://www.linkedin.com/in/dgrayden This email and any attachments may contain personal information or information that is otherwise confidential or the subject of copyright. Any use, disclosure or copying of any part of it is prohibited. The University does not warrant that this email or any attachments are free from viruses or defects. Please check any attachments for viruses and defects before opening them. If this email is received in error please delete it and notify us by return email.

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Two Research Fellow Positions at The University of Melbourne, Australia
by David Grayden Feb. 5, 2020

Feb. 5, 2020

Two postdoctoral research fellow positions are available at The University of Melbourne, Australia. Research Fellow in Neural Modelling - 2 year position (may be extended) at Junior (Level A) or Senior (Level B) Postdoc Salary Applications close: 27 Feb 2020 11:55 PM Australian Eastern Daylight Time (UTC+11) http://jobs.unimelb.edu.au/caw/en/job/902154/research-fellow-in-neural-mode… We are seeking a highly motivated Research Fellow to undertake a project aiming to develop mathematical frameworks bridging different scales of brain activities to provide a new tool for understanding the brain. This project will provide a framework to enable the creation of subject-specific neural circuit diagrams. The activities of microscopic neurons will be linked to macroscopic brain behaviour, providing a novel technique for neuroimaging. This technique will enable insights into brain function and provide potential benefits for understanding and treating neurological disorders as well as for the development of artificial intelligence (AI) technologies. The outcomes will have a significant impact on the treatment of neurological conditions in the future through greater understanding of diseases, improved diagnostics, and subsequent treatments. Rejane Langlois Postdoctoral Fellowship - 3 year position at Junior (Level A) or Senior (Level B) Postdoc Salary Applications close: 20 Feb 2020 11:55 PM Australian Eastern Daylight Time (UTC+11) http://jobs.unimelb.edu.au/caw/en/job/902038/rejane-langlois-postdoctoral-f… The Rejane Langlois Postdoctoral Fellowship seeks to further enhance Melbourne School of Engineering research at the interface of science, engineering and medicine. The Fellow will have the opportunity to undertake independent research as well as engage in broader collaborations within the Department of Biomedical Engineering. We are looking for outstanding candidates within one of our key research areas: biomaterials and tissue engineering; biomechanics and mechanobiology; bionics, biomedical imaging and neuroengineering or systems and synthetic biology. Regards, David Professor David B. Grayden Clifford Chair of Neural Engineering Dept of Biomedical Engineering Melbourne School of Engineering The University of Melbourne, Victoria 3010 Australia http://www.bme.unimelb.edu.au<http://www.bme.unimelb.edu.au/> | https://www.linkedin.com/in/dgrayden This email and any attachments may contain personal information or information that is otherwise confidential or the subject of copyright. Any use, disclosure or copying of any part of it is prohibited. The University does not warrant that this email or any attachments are free from viruses or defects. Please check any attachments for viruses and defects before opening them. If this email is received in error please delete it and notify us by return email.

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MBL Methods in Computational Neuroscience Course
by Stephen A. Baccus Feb. 4, 2020

Feb. 4, 2020

Applications are open for the Methods in Computational Neuroscience course at the Marine Biology Laboratory in Woods Hole, MA. The course will run from August 2 to August 28, 2020, and the online application form can be found at: https://ws2.mbl.edu/studentapp/studentapp.asp?courseid=MCN The course application deadline is *March 16*. 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/ 2020 Course Directors: Stephen Baccus, Stanford University Xiao Jing Wang, New York University 2020 Faculty: Larry Abbott, Columbia University Emery Brown, MIT Randy Buckner, Harvard University Dmitri Chklovskii, Simons Institute Claudia Clopath, Imperial College London Shaul Druckmann, Stanford University Uri Eden, Boston University Bard Ermentrout, U. of Pittsburgh Adrienne Fairhall, U. of Washington Ila Fiete, University of Texas Austin James Fitzgerald, Janelia Res., HHMI Loren Frank, UCSF Michale Fee, MIT Stefano Fusi, Columbia University Surya Ganguli, Stanford University Juliana Gjorgjieva, Max Planck Institute Mark Goldman, UC Davis Nancy Kopell, Boston University Eve Marder, Brandeis University Bartlett Mel, Univ. of Southern California David Redish, U. Minnesota Robb Rutledge, Yale University Terry Sejnowski, Salk Institute Mike Shadlen, Columbia U. Reza Shadmehr, Johns Hopkins Univ. Sara Solla, Northwestern University Haim Sompolinsky, Hebrew University Nelson Spruston, Janelia Research Campus Josh Tenenbaum, MIT Nao Uchida, Harvard University David Van Essen, Washington University Greg Wayne, DeepMind

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Doctoral Position at the Institute for Neural Computation - Ruhr University Bochum
by Vinita Samarasinghe Feb. 4, 2020

Feb. 4, 2020

Prof. Sen Cheng, Institute for Neural Computation at the Ruhr University Bochum, invites applications for a *Doctoral position (TV-L E13, 65%) in Computational Neuroscience. * The position starts as soon as possible and is funded for three years. *Job description* The research group is highly dynamic and uses diverse computationalmodeling approachesincludingbiological neural networks, cognitive modeling, and machine learning to investigatelearning and memory in humans and animals. For further information see www.rub.de/cns <http://www.rub.de/cns>. The successful candidate will develop and study computational models of episodic memory and spatial navigation. The models will be based on biologically plausible spiking neurons and will account for the generation and learning of complex behaviors. The research focus will be on modeling the influence of neuro- and psychopathologies on observable behavior. The candidate mayenrollin a doctoral program in neuroscience, psychology, physics, or electrical engineering – subject to enrollment requirements of the particular program. *Your Profile: * Candidates must have * an excellent university degreein neuroscience, psychology, physics, computer science, electrical/biomedical engineering or a related field, * relevant experience modeling biological neural networks, * excellent communication skills in English, and * the ability to work well in a team. Experience with research in neuro- and psychopathologieswould be a further asset. The Ruhr University Bochum is home to a vibrant research community in neuroscienceand cognitive science. The Institute for Neural Computation is an independent research unit and combines different areas of expertise ranging from experimental and theoretical neuroscienceto machine learning androbotics. Please send your application, including CV, transcripts and research statement electronically, as a single PDF file, to samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de>. In addition, at least two academic references mustbe sent independently to the above email address. The deadline for applications is February 29^th , 2020. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. Contact person: Vinita Samarasinghe, samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de> -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Postfachnummer 110 Universitätstr. 150 D-44801 Bochum Tel: +49 (0)234 32 27316 Email: samarasinghe(a)ini.rub.de

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PhD opportunities in Bristol University
by Conor Houghton Feb. 3, 2020

Feb. 3, 2020

The Bristol Computational Neuroscience Unit, University of Bristol is looking to recruit to a number of EPSRC-funded PhD studentships for a Sept/Oct 2020 start: the research areas considered include Computational Neuroscience and Machine Learning. We have a vibrant Computational Neuroscience group with strong collaborative links with local and international groups working in experimental neuroscience, in machine learning and cognitive science. We have interesting projects to offer in the areas of synaptic plasticity, neural data analysis, neural coding, reinforcement learning, neurolinguistics, cortical circuit and credit assignment. More details here: https://bristolcnu.github.io/research/ http://www.bristol.ac.uk/engineering/postgraduate/funding/sceem-studentship… Bristol is a great place to live and work and so we urge you to apply or to recommend this opportunity to suitable students. Anyone interested should contact one of us to discuss potential project and their application; there are notes on the application process below; the application would need to be submitted by 21st Feb 2020. All the best, Conor, Nathan, Cian, Rui and Laurence ___________ Note that unfortunately these studentships are subject to a UK residency requirement: (https://epsrc.ukri.org/skills/students/help/eligibility/) either home students, or EC nationals who have lived in the UK for three years prior to starting the PhD; if the three years have been spent in higher education, then they have to have been resident in the EEA or Switzerland immediately before this. Students should contact one of us before applying. The selection itself goes through a two step process, students are first accepted as PhD students and are then considered for funding. Applicants should apply via http://www.bristol.ac.uk/study/postgraduate/apply/ and selecting "Computer Science PhD", ensuring they submit a short research proposal outlining the research question or area they intend to focus on and a CV by the deadline.

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Undergraduate computational neuroscience research position
by Neymotin, Samuel (NKI) Jan. 31, 2020

Jan. 31, 2020

A new paid opportunity for an Army Research Office (ARO) sponsored undergraduate research apprenticeship program (URAP) position is available for the summer of 2020 at the Nathan Kline Institute for Psychiatric Research in Orangeburg, NY (https://www.nki.rfmh.org/) The research will be conducted under the mentorship of Samuel Neymotin, Haroon Anwar, and Salvador Dura-Bernal to help achieve the goals of an ARO grant (PI: Neymotin) that aims to train detailed thalamocortical circuit models to play video games using biologically-plausible learning rules, and to compare the models’ performance against commonly used deep reinforcement learning algorithms. Students will have the opportunity to learn cutting edge methods in computational neuroscience, machine learning, and Python software development, and potentially publish their research results. Candidates will be considered based on their experience in computational neuroscience, machine learning, and Python programming. Candidates must be located within commuting distance to Nathan Kline Institute during the apprenticeship period. To be considered, please click the link to “Apply Now” at https://www.usaeop.com/program/urap/ Make sure to use code U803 (Nathan Kline Institute for Psychiatric Research , NY). For questions, email Samuel.Neymotin(a)nki.rfmh.org<mailto:Samuel.Neymotin@nki.rfmh.org> For more information about the URAP visit: http://www.usaeop.com/<https://protect2.fireeye.com/v1/url?k=1b10bbdd-47344dbc-1b1242e8-0cc47a6d17…> ________________________________ IMPORTANT NOTICE: This e-mail is meant only for the use of the intended recipient. It may contain confidential information which is legally privileged or otherwise protected by law. If you received this e-mail in error or from someone who was not authorized to send it to you, you are strictly prohibited from reviewing, using, disseminating, distributing or copying the e-mail. PLEASE NOTIFY US IMMEDIATELY OF THE ERROR BY RETURN E-MAIL AND DELETE THIS MESSAGE FROM YOUR SYSTEM. Thank you for your cooperation.

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5th EADM Summer School: Learning and decision making, 8-15 July, 2020
by Hrvoje Stojic Jan. 31, 2020

Jan. 31, 2020

SAVE THE DATE! Date: 8-15 July, 2020 Location: Universitat Pompeu Fabra, Barcelona, Spain Theme: Learning and decision making Eligible: Early career researchers Applications open: 15 February, 2020 Further details available at: https://ldmss.org The 5th EADM Learning and Decision Making summer school will take place from the 8th to the 15th of July and will cover a wide range of topics related to learning and decision making, including reinforcement learning, sampling biases, decisions from experience, function learning, category learning and social learning. Participants will receive advanced training and hands-on tutoring on various computational modeling approaches in learning and decision making from experts in the field and will get feedback on their latest research ideas in poster sessions. The academic syllabus will be complemented with social activities in and around Barcelona. Applications will open on the 15th of February! Confirmed faculty include: Mirta Galesic (Santa Fe Institute) Maarten Speekenbrink (University College London) Johannes Müller-Trede (IESE Business School) Henrik Olsson (Santa Fe Institute) G. Elliot Wimmer (University College London) Mehdi Keramati (City University) Elizaveta Konovalova (Max Planck Institute for Human Development) More coming soon! The organization team: Gael Le Mens (Universitat Pompeu Fabra) Emmanouil Konstantinidis (University of Warwick) Hrvoje Stojic (University College London) Pantelis P. Analytis (University of Southern Denmark) Mikhail Spektor (Universitat Pompeu Fabra) Feel free to contact us at: ldmss(a)protonmail.com or on Twitter @ldmsschool ----------------------------- Hrvoje Stojic, PhD Postdoctoral researcher University College London Website: http://hstojic.re/

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3 Year PhD or Postdoc position in Computational Neuroscience, Charles University, Prague
by Jan Antolik Jan. 31, 2020

Jan. 31, 2020

The newly formed Computational System Neuroscience Group is inviting applications for several fully funded PhD or Postdoc positions in Computational Neuroscience and Neuroinformatics at the Faculty of Mathematics and Physics, Charles University, Prague, starting September 2020 The studentships are ideal for students who want to apply their computational and analytical skills to problems in neuroscience and related fields. Successful candidates will have a strong background in numerical sciences, such as computer science, math or physics, and a keen interest in shaping the future of neuroscience. For the PhD positions no previous experience in neuroscience is required. A broad range of topics is available (see http://antolik.net/research) including but not limited to: large-scale spiking models of the early and higher visual system, machine learning techniques in visual neuroscience, developmental models of early sensory systems and development of tools for computational modelling. We encourage applicants to explore the work of the group <http://antolik.net/projects.html> by looking at its past and present projects. Interested candidates are invited to send their CV and a brief description of their interest in this position to antolikjan(a)gmail.com, to initiate discussions about potential PhD or Postdoc projects of interest.

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Ten Years Reproducibility Challenge / June 22, 2020 in Bordeaux, France
by Nicolas Rougier Jan. 31, 2020

Jan. 31, 2020

Dear all, There are two months left if you want to take up the "Ten Years Reproducibility Challenge” whose goal is to try to compile / run your old code (> 10 years) that accompanied one of your published article or preprint (see below). More information at: https://github.com/ReScience/ten-years/ Deadline: 01/04/2020 (https://github.com/ReScience/submissions) Workshop: 22/06/2020 (Bordeaux, France) List of declared participants: https://github.com/ReScience/ten-years/issues/1 Three papers already submitted (one published): https://github.com/ReScience/submissions/issues?q=is%3Aissue+is%3Aopen+labe… Nicolas Rougier --- Did you ever try to run an old code that you wrote for a scientific article you published years ago? Did you encounter any problems? Were you successful? We are curious to hear your story. This is the reason why we are editing a special issue of ReScience to collect these stories. The ten years reproducibility challenge is an invitation for researchers to try to run the code they've created for a scientific publication that was published more than ten years ago. This code can be anything (statistical analysis, numerical simulation, data processing, etc.), can be written in any language and can address any scientific domain. The only mandatory condition to enter the challenge is to have published a scientific article before 2010, in a journal or a conference with proceedings, which contains results produced by code, irrespectively of whether this code was published in some form at the time or not. Note that we do not ask you to write a new version of your old code. We ask you instead to try to make your old code to run on modern hardware/software (with minimal modifications) in order to check if you can obtain the exact same results that were publised at least ten years ago. Sounds easy? We have good reasons to think this might be more difficult than you think. And maybe the first problem you'll have to solve is to find your own source code. More information at: https://github.com/ReScience/ten-years/

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