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Call for papers : Special Issue on Brain Simulation and Spiking Neural Networks ( Cognitive Computation - Springer)
by Vassilis Cutsuridis Oct. 16, 2020

Oct. 16, 2020

*Call For Papers:Journal : Cognitive ComputationSpecial Issue : Brain Simulation and Spiking Neural Networks* https://www.springer.com/journal/12559/updates/18336610 *Scope and Motivation* During the past 10 years, many experiments have been implemented with the aim of improving our understanding on the brain’s structure and function. Alongside, simulation neuroscience has become an important strategy to investigate how the brain works. The Human Connectome Project in the US started in 2009 and aimed to provide a big human brain mapping dataset on which many brain models have already been tested. In the Human Brain Project in the EU, a large-scale virtual rodent brain simulation is being built with the purpose of revealing various brain activities. In Japan, whole human-scale brain simulations on the Fugaku supercomputer are being established to investigate how neural networks develop their learning process. On the other hand, the foundation of cognitive computing and control mechanism can be revealed from the simulations of brain circuits and the neural dynamics. Moreover, these are also critical to improve current artificial intelligent systems and for building brain intelligence level algorithms. In this special issue, we invite researchers to present their state-of-the-art approaches, introduce recent advances and therefore show the potential of brain-simulation-related technologies. *Guest Editors* Jordi Solé-Casals (jordi.sole(a)uvic.cat) Cesar F. Caiafa (ccaiafa(a)fi.uba.ar) Zhe Sun (zhe.sun.vk(a)riken.jp) Vassilis Cutsuridis (vcutsuridis(a)lincoln.ac.uk) *Topics* Topics include but are not limited to: • Brain Connectivity mapping and functional mapping • Data analysis methods for connectome data • Multi-scale neural system simulation • Neuromorphic hardware • High-performance computing system for large scale simulations • Neural system inspired spiking neural network • Neuro-robotics systems • Sensorimotor learning model *Deadlines* *Submissions Deadline*: *April 1, 2021* First notification of acceptance: June 1, 2021 Submission of revised papers: August 1, 2021 Final notification to the authors: Oct 1, 2021 Submission of final/camera-ready papers: Nov 1, 2021 Publication of special issue: Nov 22, 2021 *Submission Instruction:* Prepare your paper in accordance with the Journal guidelines: www.springer.com/12559. Submit manuscripts at: http://www.editorialmanager.com/cogn/. Select “SI: Brain Simulation and Spiking Neural Networks” for the special issue under “Additional Information.” Your paper must contain significant and original work that has not been published nor submitted to any journals. All papers will be reviewed following standard reviewing procedures of the Journal. *Author Resources* Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals. All papers will be reviewed following standard reviewing procedures for the Journal. Papers must be prepared in accordance with the Journal guidelines: www.springer.com/12559 Springer provides a host of information about publishing in a Springer Journal on our Journal Author Resources <https://www.springer.com/gp/authors-editors/journal-author> page, including FAQs <http://www.springer.com/gp/authors-editors/journal-author/frequently-asked-…> , Tutorials <https://www.springer.com/gp/authors-editors/journal-author/journal-author-a…>along with Help and Support. <https://support.springer.com/en/support/home> Other links include: - editorial policies <https://www.springer.com/gp/authors-editors/journal-author/journal-author-h…> - publication policies <https://www.springer.com/gp/open-access/publication-policies> - copyright transfer <https://www.springer.com/gp/open-access/publication-policies/copyright-tran…> - self-archiving <https://www.springer.com/gp/open-access/publication-policies/self-archiving…> - OA funding <https://www.springernature.com/gp/open-research/funding> - open choice <https://www.springer.com/gp/open-access/springer-open-choice> - funder compliance <https://www.springer.com/gp/open-access/publication-policies/funder-complia…> - read and publish agreements <https://www.springer.com/gp/open-access/springer-open-choice/springer-compa…> - preprint sharing <https://www.springer.com/gp/open-access/preprint-sharing/16718886> - my publication process <https://www.springer.com/gp/authors-editors/journal-author/journal-author-h…> - production <https://www.springer.com/gp/authors-editors/journal-author/journal-author-h…> - publication <https://www.springer.com/gp/authors-editors/journal-author/journal-author-h…> - post-publication <https://www.springer.com/gp/authors-editors/journal-author/journal-author-h…> - ORCID <https://www.springernature.com/de/researchers/orcid?utm_source=springer&utm…> - Publons <https://www.springernature.com/gp/reviewers/publons> - article sharing <https://www.springernature.com/gp/researchers/sharedit> - citation alerts <https://www.springer.com/gp/authors-editors/journal-author/journal-author-h…> If you have additional questions, please do not hesitate to contact us. Best regards, Vassilis --- Dr Vassilis Cutsuridis Senior Lecturer School of Computer Science & Lincoln Sleep Research Center University of Lincoln Lincoln UK Tel: +44 (0) 1522 83 5701 Email: vcutsuridis(a)lincoln.ac.uk Web: http://staff.lincoln.ac.uk/vcutsuridis Personal website: http://www.vassiliscutsuridis.org/

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Free Online Seminar: How to build your own Connectome?
by Markus Butz-Ostendorf Oct. 16, 2020

Oct. 16, 2020

Dear List, My apologies for cross-postings first of all! I would like to draw your attention to the first free online webinar on connectomics in clinical application with our novel neuroimaging software NICARA, particularly dedicated to human connectomics. Abstract at the end of this message. The seminar takes place online on Tue, 20 Oct 2020 at 3pm (CET). Participation is free of charge but registration is kindly requested via this link https://www.biomax.com/webinar With NICARA every neuroscientists can explore the beauty of connectomes and focus on connectome-related research questions without being a neuroimaging or neuroinformatics expert him- or herself. Register one of the limited NICARA demo accounts today via https://ssl.biomax.de/nicara/ Looking forward to meeting you online at the seminar! kind regards, Markus == Free Online Seminar Series: How to build your own Connectome? With our neuroimaging solution NICARA we help clinicians working in the field of mental disorders to classify their patients faster and even better than ever before. Pharmacologists can significantly speed up the evaluation of the clinical efficacy of new drugs and scientists can access data and publications quickly and easily, thus greatly accelerating the success of research, while saving costs. All of these experts face more or less the same problem: Extracting structural and functional brain connectivity form raw images is time consuming and requires extensive expert knowledge. With NICARA you have thousands of publicly available connectomes at your fingertips and the possibility to analyze your own data by creating individual connectomes on the fly. Explore the world of connectomics with NICARA and learn how you can easily build your own Connectome. Register today for free for one of our upcoming Online Seminars and Live Demos. for Clinicians: 20/10/2020, 3:00 pm for Scientists 10/11/2020, 3:00 pm for Pharmacologists 1/12/2020, 3:00 pm To register, please go to https://www.biomax.com/webinar and request your access data via the webinar page. We are looking forward to meeting you. -- Dr. rer. nat. Markus Butz-Ostendorf Innovation Manager Brain Science Senior Product Manager Biomax Informatics AG Robert-Koch-Str. 2, 82152 Planegg, Germany Registergericht: Amtsgericht München, HRB 134442 Vorstand: Dr. Klaus Heumann Vorsitzender des Aufsichtsrates: Prof. Dr. Hans-Werner Mewes Tel: +49 89 895574-862 Fax: +49 89 895574-825 Email:markus.butz-ostendorf@biomax.com Website:http://www.biomax.com PGP:https://ssl.biomax.de/pgp/

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PhD and PostDoc positions on physical models of biological computation
by elisabetta chicca Oct. 16, 2020

Oct. 16, 2020

The Bio-Inspired Circuits and Systems (BICS) group at the University of Groningen, Netherlands headed by Prof. Elisabetta Chicca is inviting applications for PhD and PostDoc positions on physical models of biological computation. The positions will be embedded in a highly interdisciplinary, international research group lead by Prof. Elisabetta Chicca, who recently started a new group in the Faculty of Science and Engineering (FSE) at the University of Groningen. The BICS group aims to identify the principles of neural computation and implement them in fully parallel and low-power neuromorphic systems that offer the opportunity to overcome the limitations of traditional digital architectures. The successful candidate should have a background in physics, computer sciences, electrical engineering, neurosciences or some related field. Some modelling, programming or analog CMOS design experience is advantageous. Applications will be considered until the positions are filled. The application should include a cover letter stating the candidate’s research interests and how these fit to the research conducted in the BICS group; a CV outlining prior education, research experience, skills and publications; reprints (if available); academic transcripts; and names of two referees. Electronic submission is preferred (to be addressed to Prof. Elisabetta Chicca, e.chicca <e.chicca(a)rug.nl>ATrug.nl <e.chicca(a)rug.nl>). ------------------------------------------------------------ Prof. Dr. Elisabetta Chicca Full Professor Chair of Bio-Inspired Circuits and Systems (BICS) Zernike Institute for Advanced Materials CogniGron - Groningen Cognitive Systems and Materials Center University of Groningen Nijenborgh 4, 9747 AG Groningen The Netherlands Phone: +31 50 363 8731 Office: 5113.0039 Secretary: Jeannette de Boer Phone: +31 50 363 4843

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Postdoctoral position in computational and statistical neuroscience
by John Pearson Oct. 16, 2020

Oct. 16, 2020

Posting below. Interested candidates are also encouraged to reach out directly. The laboratories of Dr. Richard Mooney (https://www.neuro.duke.edu/mooney-lab) and Dr. John Pearson (http://pearsonlab.github.io<https://urldefense.com/v3/__http://pearsonlab.github.io/__;!!OToaGQ!5lp4UHC…>) at Duke University are seeking two (2) postdoctoral scholars in conjunction with an NIH BRAIN Initiative-funded project investigating the contributions of basal ganglia to vocal motor exploration and reinforcement learning. Candidates will combine state of the art viral, electrophysiological, imaging, and computational methods and work as part of a multi-institution team that also includes Dr. Carlos Lois, in the Division of Biology and Biological Engineering at CalTech, and Dr. Tim Gardner, in the Phil and Penny Knight Campus for Accelerating Scientific Impact at the University of Oregon. The first postdoc, appointed in the Department of Neurobiology, will use behavioral, optogenetic, electrophysiological and optical imaging methods to explore how cortico-basal ganglia circuits contribute to vocal exploration and learning. Previous experience with imaging and electrophysiological methods is desirable, and experience using viral gene transfer methods to monitor and manipulate neural activity will be especially helpful. Candidates with strong quantitative skills and an interest in developing or improving computational skills are especially desired. This postdoc will work closely with a related postdoc hire in the Department of Biostatistics & Bioinformatics, as well as team members across all institutions. The second postdoc, appointed in the Department of Biostatistics & Bioinformatics, will perform computational modeling of reinforcement learning in the birdsong system, including development of new statistical machine learning methods for the analysis of song, electrophysiology, and calcium imaging data. The postdoc will work closely with experimentalists to design studies, analyze data, and refine hypotheses. Candidates should hold a PhD in a quantitative discipline such as computational neuroscience, physics, statistics, or computer science. Previous experience in neurobiology is a plus but not required. This postdoc will work closely with a related postdoc hire in the Department of Neurobiology, as well as team members across the other institutions. John ------------------------------- John Pearson, Ph.D. Assistant Professor Biostatistics and Bioinformatics Center for Cognitive Neuroscience Electrical and Computer Engineering Neurobiology; Psychology and Neuroscience Duke University B255 LSRC Box 91003 Durham, NC 27708 919.613.8338 http://pearsonlab.github.io/

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Postdoc position on Biological Deep Learning
by Walter Senn Oct. 15, 2020

Oct. 15, 2020

Dear all One postdoc position devoted to learning in deep cortical networks is available in the Computational Neuroscience labs at the University of Bern, Switzerland. Our research is focussed on biologically realistic models of spatio-temporal processing in recurrent cortical networks and their relation to reinforcement learning, Bayesian computing, and neuromorphic implementations. The position is focussed on formalizing the dendritic processing of cortical pyramidal neurons, in particular on combining top-down and bottom-up information streams within pyramidal neurons, and in integrating these neurons in deep networks. The position is part of a collaboration with Profs Fritjof Helmchen and Giacomo Indiveri (UniZH / ETHZ) supported by the Swiss National Science Foundation and is available from January 1st, 2021, for 2 years (extendable). We offer a stimulating environment with three research groups in theoretical and computational neuroscience, along with experimental neuroscience at the same Department of Physiology (physio.unibe.ch/gruppen.aspx <file:///Users/walter/Documents/Walter_Physio/admin/ownPositionAnnouncments/HBP_PosAnnouncments2020/physio.unibe.ch/gruppen.aspx>), as well as close collaborations with other labs in neuroscience, artificial intelligence and neuromorphic engineering. Ideal candidates should have a strong background in computational neuroscience, machine learning, applied mathematics and/or physics. Please send your CV, publication list, letter of motivation and contact information for at least two references to Walter Senn (walter.senn(a)unibe.ch <mailto:walter.senn@unibe.ch>) and Mihai Petrovici (mihai.petrovici(a)unibe.ch <mailto:mihai.petrovici@unibe.ch>), with cc to Virginie Sabado (virginie.sabado(a)unibe.ch <mailto:virginie.sabado@unibe.ch>). The first evaluation round will begin on November 8, 2020. The positions will remain open until filled. With best regards, Mihai Petrovici and Walter Senn

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postdoc on computational modelling of perceptual inference and psychophysics (Hyafil lab, CRM, Barcelona)
by Alexandre Hyafil Oct. 15, 2020

Oct. 15, 2020

A postdoc position is available under the supervision of Alexandre Hyafil in the group of Computational Neuroscience at the *Center for Research in Mathematics (CRM),* Barcelona, Spain ( http://www.crm.cat/en/Research/ResearchGroups/Neuroscience/Pages/default.as…) The project will combine modelling and psychophysics (possibly neuroimaging) to study the mechanisms of propagation of belief in human perception. The candidate will benefit from the stimulating environment of Barcelona area in Theoretical and Systems Neuroscience and will have the opportunity of enjoying a lively city (should the pandemics permit). Our lab forms part of a larger interacting network of neuroscience labs in Barcelona ( http://www.barccsyn.org) Candidates should have a PhD in computational cognitive neuroscience or a related field. Prior experience with psychophysics, neuroimaging, machine learning and/or computational modelling will be valued. Financial support is provided by the Spanish Ministry of Science. Initial appointment: two years. *APPLICATION:* Send a curriculum and motivation letter with a list of two contacts for recommendation letter to alexandre.hyafil(a)gmail.com. Informal enquiries are welcome. *DEADLINE:* until the position is filled *STARTING DATE:* anytime before summer 2021

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PhD/Postdoc position in Tübingen, Deep nets + human neurophysiology data
by Jakob Macke Oct. 15, 2020

Oct. 15, 2020

Dear colleagues, We have a position for a Ph.D. Student or Postdoctoral Researcher (m/f/d, E13 TV-L) in `Deep learning for studying population codes in the human brain’, starting as soon as possible. The initial fixed-term contract will be for 3 years with possible extension. Details at https://uni-tuebingen.de/en/196976. How do neural circuits in the human brain recognize objects, persons and actions from complex visual stimuli? To address these questions, we will develop deep convolutional neural networks for modelling how neurons in high-level human brain areas respond to complex visual information. We will make use of a unique dataset of neurophysiological recordings of single-unit activity and field potentials recorded from the medial temporal lobe of epilepsy patients. Our tools will open up avenues for a range of new investigations in cognitive and clinical neuroscience, and may inspire new artificial vision systems. The position is part of the BMBF-funded project DeepHumanVision in collaboration with the `Dynamic Vision and Learning’ Group at TU Munich (Prof. Dr. Laura Leal-Taixé) and the Cognitive and Clinical Neurophysiology Group at University Hospital Bonn (Prof. Dr. Dr. Mormann). Our group develop computational methods that help scientists interpret empirical data, with a focus on basic and clinical neuroscience research. We want to understand how neuronal networks in the brain process sensory information and control intelligent behaviour, and use this knowledge to develop methods for the diagnosis and therapy of neuronal dysfunction. We aim to work in an interdisciplinary, collaborative and supportive work environment which emphasizes diversity and inclusion. Tübingen has an internationally renowned research community in artificial intelligence, machine learning and computational neuroscience, including the Cyber Valley Initiative, the Tübingen AI Center, the Excellence Cluster Machine Learning, and the new MSc Program Machine Learning. We are situated in the AI Research Building, in close proximity to the Max Planck Institutes for Intelligent Systems and Biological Cybernetics, and participate in the two International Max Planck Research Schools (IMPRS) `Intelligent Systems’ and `Mechanisms of Mental Function and Dysfunction’. The position is open to candidates who have a PhD or Master’s in in a quantitative discipline (e.g. computer science, maths, statistics, physics, electrical engineering, computational neuroscience), a genuine interest in interdisciplinary work at the interface of machine learning and neuroscience, and strong programming skills (ideally Python/PyTorch). Prior experience in deep learning, and/or in analysing neurophysiological data with statistical methods is advantageous. The University seeks to raise the number of women in research and teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference. The employment will be carried out by the central administration of the University of Tübingen. PhD applicants are also expected to apply to the IMPRS `Intelligent Systems’ https://imprs.is.mpg.de, Deadline also November 2. Please submit your application materials to mls-sekretariat(a)inf.uni-tuebingen.de, with subject `Application: Postdoc/PhD DeepHumanVision‘. Please include a CV, a brief statement of research interests, contact details of two referees and a work sample - anything that is genuinely your own work, e.g. a thesis, computer code, a research manuscript, an essay, or a publication. For postdoc applicants, we expect relevant prior publications. Application deadline: November 02, 2020. Best, Jakob Macke Prof. Dr. Jakob Macke Chair of Machine Learning in Science Excellence Cluster `Machine Learning: New Perspectives for Science’ Department of Computer Science University of Tübingen Adjunct Senior Research Scientist, Department of Empirical Inference Max Planck Institute for Intelligent Systems Tübingen Jakob.Macke(a)uni-tuebingen.de Office: Franziska Weiler, mls-sekretariat(a)inf.uni-tuebingen.de www.mackelab.org/tuebingen

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Positions in Probabilistic Data Science / Machine Learning Lab, Oldenburg University, Germany
by Jörg Lücke Oct. 14, 2020

Oct. 14, 2020

Dear list, The Machine Learning Lab at the University of Oldenburg, Germany, is seeking to fill the position of a Researcher in Probabilistic Data Science. We look for somebody who has already obtained a PhD degree or is close to obtaining one. The only definitive source of information is here: https://uol.de/stellen/?stelle=67593 The application deadline is Oct 20 but we very likely also accept applications until the end of next week. We are seeking somebody with knowledge on probabilistic generative modeling. Best wishes, Jörg Lücke -- Jörg Lücke (PhD) Professor and Head of the Machine Learning Lab Department of Medical Physics and Acoustics School of Medicine and Health Sciences University of Oldenburg 26111 Oldenburg Germany www.uol.de/ml

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COSYNE 2021: Abstract submission is now open
by Tomas Hromadka Oct. 14, 2020

Oct. 14, 2020

==================================================== Computational and Systems Neuroscience 2021 (Cosyne) MAIN MEETING ONLINE 24 - 26 February 2021 www.cosyne.org ==================================================== IMPORTANT DATES Abstract submission is now open Abstract submission deadline: 12 November 2020 ---------------------------------------------------- MEETING ANNOUNCEMENT ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. Cosyne 2021 will take place online, February 24 - 26, 2021. Please note that the dates have changed slightly from the initial announcement. The goal of this year’s meeting is to promote early stage investigators. Therefore, there are no invited talks from established researchers. The format will include featured contributed talks chosen from submitted abstracts, and interactive poster-like presentations (short recorded presentation + live interactions). More details to follow. All abstract submissions will be reviewed as in previous years, but reviewing will be fully double blind. The deadline for Abstract submission will be November 12, 2020. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, and computation with spiking networks. When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. ---------------------------------------------------- COSYNE 2021 TUTORIAL ---------------------------------------------------- Cosyne 2021 main meeting will be preceded by an online Cosyne Tutorial Session led by Kanaka Rajan (Icahn School of Medicine at Mount Sinai) on 23 February 2021. More details will be posted on www.cosyne.org. ORGANIZING COMMITTEE General & Program Chairs: Anne-Marie Oswald (U Pittsburgh) and Srdjan Ostojic (Ecole Normale Superieure Paris) Diversity Chairs: Eva Dyer (Georgia Tech, Emory) and Eric Shea-Brown (U Washington) Publicity Chair: Adam Calhoun (Princeton) Tutorial Chair: Il Memming Park (Stony Brook) Development Chair: Michael Long (NYU) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) PROGRAM COMMITTEE Athena Akrami (UCL) Demba Ba (Harvard) Omri Barak (Technion) Brice Bathellier (Paris) Yoram Burak (Hebrew University) Christine Constantinople (NYU) Saskia De Vries (Allen Institute) Victor de Lafuente (UNAM Mexico) Jan Drugowitsch (Harvard) Tatiana Engel (CSHL) Annegret Falkner (Princeton) Kevin Franks (Duke) Tim Hanks (UC Davis) Ann Hermundstad (Janelia) Andrew Leifer (Princeton) Sukbin Lim (Shanghai) Scott Linderman (Stanford) Mackenzie Mathis (EPFL Lausanne) Ida Momennejad (Microsoft) Cris Niell (U Oregon) Il Memming Park (Stony Brook) Adrien Peyrache (McGill Montreal) Kanaka Rajan (Icahn School of Medicine at Mount Sinai) Robert Rosenbaum (Notre Dame) Christina Savin (NYU) Marshal Shuler (Johns Hopkins) Daniela Vallentin (Max Planck Munich) CONTACT meeting [at] cosyne.org COSYNE MAILING LISTS Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> Mailing lists for details.

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Online Mentoring Job Offer
by Maryam Oct. 13, 2020

Oct. 13, 2020

WE WANT YOU ! ScienceBeam, which is a designer and manufacturer of neuroscience applications and organizer of neuroscience educational courses, is looking for professional, experienced and authentic mentors from all around the world for online courses. Required fields: ➢ Neuroscience ➢ Neuro-Biofeedback ➢ EEG/ERP/QEEG ➢ Cognitive Science ➢ Programming (MATLAB, Bio-Signal processing, etc.) If you are as passionate about mentoring as you are about the above-mentioned fields, and can give a few hours per week in return for an honorarium, we would love to hear from you. Apply now and send your resumes to: workshop(a)sciencebeam.com WhatsApp No: +8613380781282

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