January 2019 - Comp-neuro - lists.cnsorg.org

Creating a list of important computational predictions
by Yiota Poirazi 04 Jan '21

04 Jan '21

Dear all, I believe you would agree that, the greatest recognition of our computational work comes with the experimental verification of our computational predictions. To highlight the most important outcomes of our theoretical work and facilitate a closer interaction with experimental labs so as to increase the chances of our predictions being experimentally tested, I would like to encourage you to nominate your favorite prediction at the following google form: https://docs.google.com/forms/d/e/1FAIpQLSeJZ2RrXJ0nZonIuyNzN0Cl gXDKDb7xTzoJOiqZTGxm9Kh7ow/viewform?c=0&w=1&usp=mail_form_link This effort started during the CNS 2017 meeting in Antwerp with the support of the OCNS Board. The resulting list will be posted on the CNS 2017 web site and disseminated in social media, as a reference for experimentalists. Thank you very much for supporting this important effort! Best wishes, Yiota Poirazi -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/> -- This message has been scanned for viruses and dangerous content by *E.F.A. Project* <http://www.efa-project.org>, and is believed to be clean. Click here to report this message as spam. <http://mailgate1.imbb.forth.gr/cgi-bin/learn-msg.cgi?id=4BCD7A00A1.A57D7&to…> -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/>

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[publication and call for dialog] IEEE CIS Newsletter on Cognitive and Developmental Systems
by Pierre-Yves Oudeyer 23 Jan '20

23 Jan '20

Dear colleagues, we are happy to announce the release of the latest issue of the IEEE CIS Newsletter on Cognitive and Developmental Systems (open access). This is a biannual newsletter addressing the sciences of developmental and cognitive processes in natural and artificial organisms, from humans to robots, at the crossroads of cognitive science, developmental psychology, artificial intelligence, machine learning and neuroscience. It is available at: https://goo.gl/NAwBfD Featuring dialog: === "Curiosity as Driver of Extreme Specialization in Humans" == Dialog initiated by Celeste Kidd with responses from: Elizabeth Bonawitz, Maya Zhe Wang, Brian Sweis, Benjamin Hayden, Susan Engel, Abigail Hsiung, Shabnam Hakimi, Alison Adcock, Moritz Daum, Arjun Shankar, Tobias Hauser, Goren Gordon and Perry Zurn == Topic: Curiosity-driven learning is probably one of the most fundamental mechanisms in human learning, and yet it is also probably one of the least understood. Broadly construed as spontaneous exploration and engagement with activities or material without any extrinsic goal (as opposed to searching for information useful for an extrinsic goal), many mysteries remain to be uncovered. What are the causal links between curiosity and learning? How does prior knowledge about a topic or an activity relates to curiosity about this topic? What is the role of curiosity in life-span development? Can human curiosity explain the apparently unique tendency of humans for extreme specialization? Reversely, how do different forms of curiosity (diversive or specific) evolve as children grow up and become adults? While early computational models of curiosity propose theoretical approaches to understand their cognitive mechanisms, how can we understand the affective/ emotional dimensions of curiosity? And how has the linguistic concept of “curiosity” evolved in occidental culture? Call for new dialog: === « Leveraging Adaptive Games to Learn How to Help Children Learn Effectively" == Dialog initiated by George Kachergis == Topic: How can one achieve efficiently “translational educational sciences” and get these principles used in real-world large-scale educational technologies? In this dialog, Georges Kachergis highlights challenges related to collaborations between cognitive scientists and game developers, how to deploy real world experiments, and how to enable scientific understanding when many variables cannot easily be controlled? Those of you interested in reacting to this dialog initiation are welcome to submit a response by December 15th, 2018. The length of each response must be between 600 and 800 words including references (contact pierre-yves.oudeyer(a)inria.fr) Let us remind you that all issues of the newsletter are all open-access and available at: https://goo.gl/ZjjZNz I wish you a stimulating reading! Best regards, Pierre-Yves Oudeyer, Editor of the IEEE CIS Newsletter on Cognitive and Developmental Systems Research director, Inria Head of Flowers project-team Inria and Ensta ParisTech, France http://www.pyoudeyer.com Twitter: https://twitter.com/pyoudeyer and Fabien Benureau, Editorial Assistant Cognitive NeuroRobotics Unit, Okinawa Institute of Science and Technology 1919-1 Tancha, Onna, Okinawa Japan Email: fabien.benureau [at] oist [dot] jp

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Postdoc positions on Consciousness Research at Monash Uni, Australia
by Naotsugu Tsuchiya 13 Jan '20

13 Jan '20

Position A: DP180100396 (in collaboration with Masafumi Oizumi, Hiroto Kawasaki, Giulio Tononi) No report paradigm in EEG/MEG/intracranial recordings and the analysis of integrated information across sensory and prefrontal cortex Position B: DP180104128 (in collaboration with Marta Garrido, Ueli Rutishauser, Ralph Adolphs) The analysis of MEG/intracranial recordings, using Granger causality and integrated information We are looking for highly talented postdocs (application from PhD students with a prospect of getting PhD in 1 year are welcomed) for the above two ARC-funded positions. Ideal candidates in both positions would have strong publications, strong programming skills in Matlab/Python, strong background in data analysis, preferably neuroimaging data or neural spikes. The projects include 1) design of various psychophysical paradigms (*pdf <https://academic.oup.com/nc/article/doi/10.1093/nc/niw023/2970153/Are-we-un…>)*, including no-report paradigms (*pdf <https://drive.google.com/file/d/0B9N0ysU85rs7bEF5d1VVX3J4T3c/view>*), which can be used for subsequent EEG/MEG/intracranial recording experiments and 2) analysis of EEG/MEG/intracranial data using the approximations of integrated information (link1 <http://www.eneuro.org/content/4/5/ENEURO.0085-17.2017>, *link <https://drive.google.com/open?id=0B9N0ysU85rs7NFVSQlIza215eVU> *, *link <http://www.pnas.org/content/early/2016/12/02/1603583113.abstract>*, *link <http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.10046…>)* ). Please send the inquiry with your CV to naotsugu.tsuchiya(a)monash.edu. Applicants with most fit background and skills will be contacted for subsequent interview over the internet. The positions will be available until they are filled. Regards Nao Tsuchiya -- -- *Nao (Naotsugu) Tsuchiya* Associate Professor *Monash Institute of Cognitive and Clinical Neurosciences* Attention and Memory Program School of Psychological Sciences Monash University 770 Blackburn Monash Brain Imaging facility, Clayton, VIC 3800 Australia T: +61 3 9905 4564 E: naotsugu.tsuchiya(a)monash.edu W: homepage: http://users.monash.edu.au/~naotsugt/Tsuchiya_Labs_Homepage http://med.monash.edu.au/psych/email-sig/miccn-email-sig.jpg <http://www.monash.edu/neuro-institute/> 2. Visiting Researcher at Department of Dynamic Brain Imaging, Advanced Telecommunications Research (ATR), Japan 3. Visiting Researcher at CiNet, Osaka University, Japan orcid.org/0000-0003-4216-8701

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Professorship in Artificial Intelligence
by Steuber, Volker 08 May '19

08 May '19

Professor of Artificial Intelligence University of Hertfordshire, UK School of Computer Science, College Lane Campus, Hatfield Salary £58,293 to £64,397 pa dependent on skills and experience FTE: Full time position working 37 hours per week (1.0FTE) Duration of Contract: Permanent position Closing date: 3 September 2018 Applications are invited for an exceptionally well qualified Professor of Artificial Intelligence of international standing who shares our commitment to research-informed teaching, embraces the research impact agenda, and values collegiality. Applicants will strengthen existing activity within the School and develop it further, enhancing the research strengths and external reputation of the School of Computer Science and contributing significantly to its performance in future research assessments and collaborations with public and commercial partners. The successful applicant will connect to and complement the research conducted by the Adaptive Systems Research Group within the Centre for Computer Science and Informatics Research. The School hosts the University of Hertfordshire Robot House, a facility ubiquitously equipped with low-cost sensors providing a realistic environment for experiments with robotics in a smart home; a fully-fledged RoboCup lab for development of humanoid robots participating in international competitions, and a large variety of different robotic platforms, including iCub and Baxter. We encourage applications from researchers across a wide spectrum of AI, and particularly encourage applications from researchers working on emerging topics in AI. Possible fields include, but are not limited to: • Machine learning: reinforcement learning, Deep Methods, statistical methods, large scale data modelling/intelligent processing and high-performance learning algorithms • Robotics: embodied and/or cognitive robotics, HRI, robot safety, emotional/social robots, smart homes and sensors, sensor fusion, assistive robotics • Complex Systems: collective intelligence, adaptive, autonomous and multi-agent/robot systems, collective and swarm intelligence, social and market modelling, adaptive, evolutionary and unconventional computation • Mathematical Modelling: statistical modelling, information-theoretic methods, compressive sensing, intelligent data visualization, multiscale models, optimization • Emerging Topics in AI: computer algebra and AI, topological methods (e.g. persistent homology), modern topics in games and AI • AI and applications: financial modelling, AI and biology/physics/cognitive sciences • Foundations: fundamental questions of intelligence and computation, emergence of life/intelligence, Artificial Life As well as providing research supervision at PhD and MSc level, the School of Computer Science offers modules in Artificial Intelligence, machine learning, neural and evolutionary computing, as well as Artificial Life on the BSc and MSc programmes. Applicants will be committed to a strong research and research-informed teaching agenda, and will actively contribute to increase research impact of the School, in the enthusiastic, welcoming and collegiate environment of the school. Applicants must hold a PhD (or equivalent) in a relevant subject, possess excellent communication skills in English, an internationally excellent research record and reputation, including publications of the highest quality suitable for submission to the REF (UK Research Excellence Framework). Applicants are expected to show evidence of experience and success in research/commercial income generation, engagement with the research impact agenda, engagement with key stakeholders in the relevant Artificial Intelligence community and management and leadership ability. The professor will have opportunity to contribute actively to interdisciplinary research projects at the school and university level. Applications must be made online https://www.herts.ac.uk/contact-us/jobs-and-vacancies/academic-vacancies?, reference 016194?. Informal enquiries may be addressed to Dr Volker Steuber (Associate Dean Research, v.steuber(a)herts.ac.uk) or Professor William Clocksin (Dean of School, w.clocksin(a)herts.ac.uk) Please note that applications sent directly by email will not be accepted.

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Postdoc position in computational neuroscience at the Gatsby Unit
by Peter Latham 05 Apr '19

05 Apr '19

The Gatsby Computational Neuroscience Unit, a world-class centre for theoretical neuroscience and machine learning, invites applications for one or more postdoctoral training fellowships in theoretical neuroscience. We are looking especially for someone with an interest and/or background in synaptic plasticity and learning. Candidates should have a very strong analytical background in physics, mathematics, statistics, or machine learning, with an emphasis on the use of Bayesian methods in neuroscience, a detailed knowledge and understanding of the literature, and a publication record in highly ranked conferences and journals. Candidates must also have a PhD in a relevant subject area by the agreed start date of the position. Training fellowships are funded by the Wellcome Trust, and are part of a continuing program of training postdoctoral researchers. The position is available for an initial period of two years, and may be renewed to a maximum of three years. To apply, go to http://www.gatsby.ucl.ac.uk/vacancies/index.html and click on Research Fellow (Training Fellowship in Theoretical Neuroscience or Machine Learning) Please be sure to attach to your online application a copy of your CV, statement of research interests, and full contact details (including e-mail addresses) of three academic referees. CVs should include education history, details of current or most recent position, and details of previous employment or fellowships. For further details of our research, go to http://www.gatsby.ucl.ac.uk/research.html Questions should be directed to Peter Latham, pel(a)gatsby.ucl.ac.uk

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[journals] CfP : Special Issue on Continual Unsupervised Sensorimotor Learning
by Nguyen, Sao Mai 14 Mar '19

14 Mar '19

Dear Colleagues, IEEE Transactions on Cognitive and Developmental Systems is currently running a Special Issue entitled " Continual Unsupervised Sensorimotor Learning". Dr. José Antonio Iglesias Martínez, Assoc. Prof. We would like to invite you to prepare a research article or a comprehensive review to be published in this special issue. AIM AND SCOPE Although machine learning algorithms continue to improve at a rapid pace enabling technologies and products such as autonomous driving cars and sophisticated image and speech recognition, it is often forgotten that these applications represent tailored solutions to specific tasks. Thus it is not clear if or how these autonomous systems can pave the road to general purpose machines envisioned by many. The pursuit for higher levels of autonomy and versatility in robotics is arguably lead by two main factors. Firstly, as we push robots out of the labs and productions lines, it becomes increasingly difficult to design for all possible scenarios that a particular robot might encounter. Secondly, the cost of designing, manufacturing, and maintaining such systems becomes prohibitive. As the algorithms for learning single tasks in restricted environments are improving, new challenges have gained relevance in order to get more autonomous artificial systems. These challenges include multi-task learning, multimodal sensorimotor learning and lifelong adaptation to injury, growth and ageing. Addressing these challenges promise higher levels of autonomy and versatility of future robots. This special issue on Continual Unsupervised Sensorimotor Learning is primarily concerned with the developmental processes involved in unsupervised sensorimotor learning in a life-long perspective, and in particular the emergence of representations of action and perception in humans and artificial agents in continual learning. These processes include action-perception cycle, active perception, continual sensory-motor learning, environmental-driven scaffolding, and intrinsic motivation. The special issue will highlight behavioural and neural data, and cognitive and developmental approaches to research in the areas of robotics, computer science, psychology, neuroscience, etc. Contributions might focus on mathematical and computational models to improve robot performance and/or attempt to unveil the underlying mechanisms that lead to continual adaptation to changing environment or embodiment and continual learning in open-ended environments. Contributions from multiple disciplines including cognitive systems, cognitive robotics, developmental and epigenetic robotics, autonomous and evolutionary robotics, social structures, multi-agent and artificial life systems, computational neuroscience, and developmental psychology, on theoretical, computational, application-oriented, and experimental studies as well as reviews in these areas are welcome. THEMES This special issue aims to report state-of-the-art approaches and recent advances on Continual Unsupervised Sensorimotor Learning with a cross-disciplinary perspective. Topics relevant to this special issue include but are not limited to: Emergence of representations via continual interaction Continual sensory-motor learning Action-perception cycle Active perception Environmental-driven scaffolding Intrinsic motivation Neural substrates, neural circuits and neural plasticity Human and animal behaviour experiments and models Reinforcement learning and deep reinforcement learning for life-long learning Multisensory robot learning Multimodal sensorimotor learning Affordance learning Prediction learning SUBMISSION Manuscripts should be prepared according to the “Information for Authors” of the journal found at http://cis.ieee.org/component/content/article/7/131-ieee-transactions-on-au…. Submissions must be done through the IEEE TCDS Manuscript center: https://mc.manuscriptcentral.com/tcds-ieee. Please select the category “SI: Continual Unsupervised Sensorimotor Learning”. IMPORTANT DATES 6th January 2019 – Paper submission deadline 15th March 2019 – Notification for authors 31st May 2019 – Deadline revised papers submission 30th June 2019 – Final notification for authors 31st July 2019 – Deadline for camera-ready versions September 2019 – Expected publication date More information on Continual Unsupervised Sensorimotor Learning http://projects.au.dk/socialrobotics/news-events/show/artikel/special-issue… GUEST EDITORS Nicolás Navarro-Gerrero Aarhus University, Aarhus, Denmark nng(a)eng.au.dk Sao Mai Nguyen IMT Atlantique, Francenguyensmai(a)gmail.com Erhan Öztop Özyeğin University, Turkeyerhan.oztop(a)ozyegin.edu.tr Junpei Zhong National Institute of Advanced Industrial Science and Technology (AIST), Japanjoni.zhong(a)aist.go.jp ---- Nguyen Sao Mai nguyensmai(a)gmail.com Researcher in Cognitive Developmental Robotics http://nguyensmai.free.fr

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Postdoctoral positions in computational neuroscience and artificial intelligence
by Maxim Bazhenov 01 Mar '19

01 Mar '19

Applications are invited for post-doctoral research positions in the laboratory of Dr. Maxim Bazhenov at the University of California, San Diego to study memory and learning and to develop neuroscience inspired computer algorithms capable of continual learning and adapting to the novel situations and contexts.This project involves close collaboration with the experimental laboratory of Dr. Bruce McNaughton (UC Irvine). The ultimate goal of the work is to advance the knowledge of how human and animal brains learn from experience and apply these principles to the artificial systems to enable continuous learning without catastrophic forgetting. The successful candidate will collaborate with a team of researchers to design neural network models of dynamic interactions between the hippocampus and neocortex during learning and memory consolidation in sleep and awake based on experimental data. These models will be used to derive learning principles that can be combined with advances in artificial intelligence and machine learning. An ideal candidate should have experience in computational/theoretical neuroscience and a basic knowledge of machine learning, or, alternatively, experience in machine learning algorithms and some basic knowledge of neuroscience. Experience with hierarchical learning, reinforcement learning, and/or goal-directed decision-making would be particularly helpful. The University of California offers excellent benefits. Salary is based on research experience. Applicants should send a brief statement of research interests, a CV and the names of three references to Maxim Bazhenov at mbazhenov(a)ucsd.edu -- Maxim Bazhenov, Ph.D. Professor, Department of Medicine, Neurosciences Graduate Program, UCSD, School of Medicine http://www.bazhlab.ucsd.edu/

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Mouse MRI postdoctoral opening in BL Kieffer lab - Douglas/McGill University
by Colleen Carter 31 Jan '19

31 Jan '19

POSTDOCTORAL POSITION available for NEUROIMAGING Laboratory of Pr. Brigitte L Kieffer Douglas Research Centre, McGill University, Montréal Canada We are seeking a Post-doctoral fellow with a strong background in neuroscience and computer programming who is interested in studying brain network activities and communication non-invasively using functional Magnetic Resonance Imaging (fMRI) in mice. Our group is a multidisciplinay team, and studies the role of G protein coupled receptors, including opioid and orphan receptors, in brain function and disease with an emphasis on reward/aversion processing, addiction and mood disorders. The laboratory develops customized genetic mouse mutants with targeted gene mutations to model of psychiatric disorders, and for drug discovery programs. Mice are characterized using sophisticated behavioral methods, optogenetics and neuroimaging approaches translatable to human research. The postdoctoral researcher will use fMRI in living mutant animals to characterize receptor function and drug effects on brain connectivity. Implications are in both basic and biomedical research. The postdoctoral fellow will design resting-state and pharmacological MRI-based experiments, implement existing and further develop state-of-the art post-processing methods, and the research will take place at the Douglas Research Center affiliated to McGill University. The Center has a state-of-the art brain-imaging center including a 7T animal scanner with cryoprobe, and a vibrant community of neuroimaging specialists and researchers for both animal and human research. The successful candidate must have: Ph.D. in Neuroscience /Computer Science Experience in fMRI methods development Excellent programming skills in one or more of the following: Matlab, Python, C/C++, R. Excellent writing and communication skills A record of scientific publication consistent with his/her stage of career development Project leadership skills Preferred Qualifications: Experience or interest in pre-clinical neuroscience research in the field of mental health Ability to work in a team Start date: 1 March 2019 Applicants are invited to submit their cover letter, CV and reference letters via email to: colleen.carter(a)douglas.mcgill.ca<mailto:emmanuel.darcq@douglas.mcgill.ca> Please indicate "Postdoc applicant for Kieffer team" in the subject line. We thank all applicants. Only selected candidates will be contacted. Colleen Carter Agente administrative - Divisions neurosciences et psychosociale, Coordonnatrice FACC, USER et Biosafety | Centre de recherche de l`Hôpital Douglas | 6875 boulevard LaSalle, Perry E-2102, Verdun, QC, H4H 1R3 | 514.761.6131 poste 3929 | Fax 514.762.3034 | colleen.carter(a)douglas.mcgill.ca<mailto:colleen.carter@douglas.mcgill.ca> | (http://douglas.research.mcgill.ca<http://douglas.research.mcgill.ca/>)

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Open positions at SimLab Neuroscience, Juelich, Germany
by Abigail Morrison 31 Jan '19

31 Jan '19

Dear colleagues, we are aiming to recruit scientific software developers and research scientists at the Simulation Lab Neuroscience at the Juelich Research Centre, Germany. Our focus is on exploiting high performance computing to solve fundamental problems in neuroscience. If you have an interest in leading and participating in projects to develop innovative neuroinformatics applications on Europe's finest supercomputers, we would like to hear from you. Specifically, we are looking for candidates to fill the following roles: Scientific software developer for HPC workflow middleware design and implementation at supercomputing scales http://www.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2019-023-EN… Research scientist specialising in brain modelling on HPC (from building new DSLs and their parsers to Bayesian inversion at supercomputing scales) http://www.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2019-024-EN… Research scientist for an interdisciplinary neuromorphic project combining computer science, neuroscience, computational science and mathematics http://www.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2019-025-EN… For a full description and details of how to apply, please see the online job announcements. All the best, Abigail Morrison -- Prof. Dr. Abigail Morrison IAS-6 / INM-6 / SimLab Neuroscience Jülich Research Center & Institute of Cognitive Neuroscience Ruhr-University Bochum http://www.fz-juelich.de/inm/inm-6 http://www.fz-juelich.de/ias/jsc/slns http://www.ikn.psy.ruhr-uni-bochum.de Office: +49 2461 61-9805 Fax # : +49 2461 61-9460 ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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Postdoctoral position available in Brinkman group at Stony Brook University
by Braden Brinkman 30 Jan '19

30 Jan '19

A postdoctoral position is available in Braden Brinkman's group in the Department of Neurobiology and Behavior at Stony Brook University, located on Long Island in New York State. The Brinkman group studies mathematical models of sensory coding and collective network dynamics, with a focus on how environmental and physiological constraints shape coding and computation in the brain. For more information on our work and the department, please visit the PI's website <https://www.sites.google.com/site/bradenbrinkman/> and the Stony Brook Neurobiology and Behavior homepage <https://renaissance.stonybrookmedicine.edu/neurobiology>. Candidates must have a strong background in quantitative methods; background in statistical physics is a plus. Position is available immediately, but we are also accepting applications from applicants expecting to graduate by June 1, 2019. Please submit applications through Stony Brook's jobs portal here (job # 1803718): https://stonybrooku.taleo.net/careersection/post_docs/jobdetail.ftl?job=180… Complete applications must include 1. C.V., including publication & preprint list. 2. A 1 to 2 page summary of past research accomplishments, highlighting the aspects of at least one project that the candidate found most interesting and/or enjoyable 3. A 1 page statement describing the candidates future directions of interest in the field of theoretical/computational neuroscience or mathematical biology. 4. 2 reference letters from senior scientists familiar with the candidate's work. Items 1-3 may be attached through the online application portal or sent directly to braden.brinkman(a)stonybrook.edu; letter writers should send letters directly to this email address. Deadline for applications is Feb 24, 2019. Please feel free to get in touch to express interest or ask any questions you may have about the position!

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