- Comp-neuro - lists.cnsorg.org

CNS*2016

by Sharon Crook

Organization for Computational Neurosciences (OCNS) CNS*2016 25th Annual Computational Neuroscience Meeting Jeju Island, South Korea July 2-7, 2016 The main meeting (July 3-5) will be preceded by a day of tutorials (July 2) and followed by two days of workshops (July 6-7). Invited Keynote Speakers: Nicolas Brunel, University of Chicago, USA Mitsuo Kawato, Advanced Telecommunications Research Institute, Japan Tatyana Sharpee, Salk Institute, USA Registration opened on January 13, 2016. Abstract submissions are now being accepted and will close on February 28. Workshop proposals are now being accepted. Note that one of the authors must register as sponsoring author for the main meeting before abstract submission is possible. In case the abstract is not accepted for presentation, the registration fee will be refunded. For up-to-date conference information, please visit http://www.cnsorg.org/cns-2016-jeju ----------------------------------------------------------------------------------- OCNS is the international member-based society for computational neuroscientists. Become a member to be eligible for travel awards and more. Visit our website for more information: http://www.cnsorg.org

Feb. 2, 2016

Open postdoctoral position in computational neuroscience+machine learning+statistics

by Turaga, Srinivas C

The Turaga Lab is looking for an exceptional postdoctoral researcher, for research at the intersection of machine learning and neuroscience. https://www.janelia.org/lab/turaga-lab —— About the lab —— With recent technological advances in 3d electron microscopy, optogenetics and large-scale chronic in vivo neural imaging, it is now possible to measure and perturb the activity of large populations of neurons, and to map their connectivity. These new data can be used understand how the structure of a neural circuit gives rise to its function. Our lab develops machine learning algorithms to map neural connectivity, and statistical models to characterize neural activity and to relate activity to connectivity. We have pioneered the use of deep-learning based machine learning algorithms to map neural connectivity from 3d electron microscopic images of brain tissue, and we are now working to improve these methods. This involves solving interesting new problems in structured prediction, active learning and unsupervised learning at an unprecedented scale (imagine working with labeled training datasets with 10^9 examples in a 10^6 dimensional feature space and wanting to achieve accuracies of 99.999%!). We are developing novel statistical methods for the analysis of large-scale calcium imaging datasets, and medium-scale connectome datasets, in order to help understand the latent structure of neural activity and neural connectivity. Our ultimate goal is build models combining large-scale activity measurements with structural connectomes in order to relate neural activity to neural connectivity with statistical and mechanistic models. —— About the institute —— HHMI's Janelia Research Campus is a unique, world-class research community near Washington, D.C. dedicated to understanding the function of neural circuits and developing synergistic imaging technology. Our highly collaborative structure is designed to support interdisciplinary work in small lab groups. We seek candidates who are comfortable with risk and are able to think independently to develop novel approaches. —— Applying —— Applicants should have a strong quantitative background with degrees or expertise in machine learning, computational neuroscience, applied mathematics, physics or related discipline. Excellent collaborative programming skills in Python, C/C++, Java or similar languages are essential. To apply, please send me a CV and names and addresses of 2-3 references by email. I will also be attending Cosyne 2016 in Salt Lake City from Feb 25-28 and will be happy to meet you there. Srini Turaga, Group Leader turagas(a)janelia.hhmi.org https://www.janelia.org/lab/turaga-lab Howard Hughes Medical Institute / Janelia Research Campus 19700 Helix Drive, Ashburn VA 20147 Office: +1 (571) 209 4131 Fax: +1 (571) 209 4939

Feb. 2, 2016

PhD Position: Modelling Gait in People with Parkinsons Disease, University of Exeter

by Tsaneva-Atanasova, Krasimira

Based within the EPSRC Centre for Predictive Modelling in Healthcare, a £2M initiative bringing together mathematicians, statisticians and clinicians, you will work on a project aiming to develop a data-driven mathematical modeling framework in order to study gait impairments in patients with Parkinson’s under the supervision of Prof Krasimira Tsaneva-Atanasova. To Apply: Candidates with strong quantitative training (e.g. a BSc or MSc in Physics, Mathematics, Computational Neuroscience, Computer Science, or Engineering) and evidence of scientific achievement are invited to apply. Knowledge of biomechanics and/or neuroscience is a plus. Please apply using the following link: http://www.exeter.ac.uk/studying/funding/award/?id=2057 Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare College of Engineering, Mathematics and Physical Sciences University of Exeter Exeter, Devon, EX4 4QF, UK tel: +44 (0) 1392 723615 email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> web: http://emps.exeter.ac.uk/mathematics/staff/kt298 ALTEREGO - Enhancing Social Interaction with an AlterEgo artificial agent http://www.euromov.eu/alterego/homepage

Feb. 2, 2016

***INDIN 2016 special session: Cognitive computing for Cyber Physical Systems ***

by Evgeny Osipov

Dear colleagues, Sorry for a possible cross-posting Please consider to submit your publication to special session “Biologically-Inspired Cognitive Architectures in Dependable Cyber-Physical Systems” on IEEE INDIN 2016 >> EXTENDED (FINAL) DEADLINE FEBRUARY 29, 2016 << >> LINK FOR SUBMISSION: http://vps.ieee-ies.org/submit-cgi-bin/authorlogin.pl?event=INDIN16 << >> Choose “SS Biologically Inspired Cognitive Architectures in Dependable Cyber-Physical Systems” as Technical Track when submitting your contribution. << IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS INDIN’16 18-21 JULY 2016, FUTUROSCOPE-POITIERS, FRANCE Special Session on “Biologically-Inspired Cognitive Architectures in Dependable Cyber-Physical Systems” Organized by IEEE Industrial Electronic Society. Technical Committee on Industrial Informatics. Sub-Committee on Bio-inspired industrial informatics Principal Organizer: Prof. Evgeny Osipov, Luleå University of Technology ———————————————————— INDIN 2016 (http://ieee-indin2016.sciencesconf.org/) is an IEEE International Conference on Industrial Informatics will be held on 18-23 July 2016, Futuroscope-Poitiers, France. The conference is sponsored by IEEE Industrial Electronics Society and Pprime Institute, Futuroscope-Poitiers, France. The proceedings are indexed by the Web of Science. Note that good quality papers may be considered for publication in IEEE Transactions on Industrial Informatics subject to further rounds of review. ———————————————————— Call for Papers Traditional computing architectures are designed to produce reliable systems with specifiable behaviours and properties. Their major strengths come from easiness of inspection, maintenance, interoperability, and reuse. However, all modern computing systems operate based on strict assumptions about their environments, thus are too inflexible to react to changing demands. In critical environments such as industrial automation, smart grids and dependable cyber-physical systems in general, this inflexibility results in serious in many cases life-critical errors. Alternative computing architectures, which greatly borrow their functionality from the versatility and efficiency of systems developed by nature, are known as biologically-inspired cognitive computing architectures (BICA). Traditionally these architectures find their applications in areas like natural language processing, image and speech processing. Very little attention so far was paid at exploring their applicability in the context of dependable industrial systems. This special session solicits contributions exploring diverse applications of BICA architectures for enriching intelligent functionality of industrial systems. Topics of interest include, but are not limited to: • Associative memory based reasoning • Combined machine learning / BICA solutions • Neural networks in cognitive computing architectures • Cognitive architectures for continuous signal processing • Cognitive fault detection and system identification • Cognitive and hybrid automatic control • Cognitive wireless communications • Symbiosis of cognitive and Von-Neumann computing architectures • Novel application areas and use-cases for BICA architectures in CPS and IoT. • BICA empowered software engineering • Spiking Neural Networks interfacing BICA architectures. Industrial usecases. -- Prof. Evgeny Osipov Dependable Communication and Computation Systems Department of Computer Science Electrical and Space Engineering Luleå University of Technology Tel. +46 920 49 15 78 Web. https://sites.google.com/site/evgenyosipov/

Feb. 2, 2016

Ph.D. and PostDoctoral positions on High-Performance Brain Simulations

by C. Strydis

Dear all, Please find below new job postings in the field of High-Performance Brain Simulations https://www.hipeac.net/jobs/9011/one-phd-position-and-one-postdoctoral-posi… Please direct all queries and applications to: c.strydis(a)erasmusmc.nl Lab job listings at: www.erasmusbrainproject.com/index.php/workopen/positions Kind regards, Christos Strydis -- ============================== Christos Strydis, Ph.D. Assistant Professor Neuroscience Department Erasmus Medical Center Wytemaweg 80 (12th floor) Office Ee1210a 3015 CN Rotterdam Tel: +31 - 10 - 70 - 43294 Fax: +31 - 10 - 70 - 44734 E-mail: C.Strydis(a)erasmusmc.nl Web: www.erasmusbrainproject.com/index.php/strydis ==============================

Feb. 2, 2016

Postdoctoral position in computational neuroscience in New York

by Ruben Coen Cagli

Postdoctoral position in the Coen-Cagli Laboratory Albert Einstein College of Medicine, New York, NY Start date August 2016 or later We are looking for a highly creative and motivated postdoctoral fellow to work in the field of computational and systems neuroscience in the laboratory of Ruben Coen-Cagli - Department of Systems and Computational Biology and Department of Neuroscience at Albert Einstein College of Medicine (AECOM) in New York City (https://sites.google.com/site/rubencoencagli/<https://sites.google.com/site/rubencoencagli/>). Our lab studies how biological sensory systems interpret the surrounding environment. Topics include probabilistic representations of natural images; models of selectivity and variability in large cortical populations; the behavioral consequences of neuronal variability; and uncertainty in visual and auditory perception. We combine theories of probabilistic neural coding, tools from computer vision and machine learning, eye-tracking experiments, and neurophysiology through collaborations. The candidate is expected to perform research related to these topics. The lab features state of the art computing and eye-tracking facilities. Close interaction and collaboration with other members of the department is anticipated. Applicants must have a Ph.D. in a relevant discipline, with an academic record of scientific excellence and independent research. Prior experience should include areas such as computational neuroscience, machine learning, computer vision, or statistics. Applicants should have a keen interest in interdisciplinary approaches to biological and neural systems. AECOM offers a vibrant interdisciplinary environment, with a growing systems and computational contingent. It is located in a quiet neighborhood of New York, only a short subway ride from Manhattan. Information about working at the AECOM, including benefits and housing for postdocs, can be found at https://www.einstein.yu.edu/research/belfer-institute/ The position starts in or after August 2016, and is funded for several years, with an initial one year appointment and expectation of extension given satisfactory performance. Salary is competitive and will be commensurate with experience. Candidates should send a single pdf file, consisting of a 1-page motivation letter, CV, and publication list to ruben.coencagli(a)gmail.com. Furthermore, candidates should organize two letters of reference, to be sent to the same e-mail address. The position is open until filled. Albert Einstein College of Medicine, Inc. is an equal opportunity employer committed to hiring minorities, women, individuals with disabilities and protected veterans. ----------------- Ruben Coen-Cagli will be available at Cosyne to meet with candidates.

Feb. 1, 2016

Postdoctoral position in Computational Neuroscience at NYU-Shanghai

by Sukbin Lim

Multiple postdoctoral positions are available in Sukbin Lim's lab at NYU-Shanghai as part of NYU’s global network and the NYU-ECNU Institute of Brain and Cognitive Science (https://shanghai.nyu.edu/research/brain) The overarching goal of our lab is to understand network interactions and dynamics in neuronal systems. In particular, our work is focused on investigating network mechanisms and synaptic plasticity for higher cognitive functions such as learning and memory. More information on the research can be found at http://shanghai.nyu.edu/research/brain/faculty/Sukbin-Lim. Environment: Institute of Brain and Cognitive Science at NYU-Shanghai is a multidisciplinary and collaborative research environment. Candidates will be encouraged to collaborate with experimental and computational groups at NYU and NYU-Shanghai, and will have the opportunities to spend time at NYU in New York in case of a collaboration between Shanghai and New York. The initial appointment is for 1 year, renewable up to 3 years subject to progress and globally competitive compensations will be provided. To Apply: Qualified applicants are expected to hold a PhD by the start date of the position in computational and theoretical neuroscience, or related discipline with a strong quantitative training in Mathematics, Physics, Computer Sciences and Engineering. Strong programming skills (e.g., Python, MATLAB or C/C++) and experience in modeling networks/complex systems will be highly valued. Knowledge of Neuroscience would be a plus. Applications will be reviewed until the position is filled. To be considered, please send a curriculum vitae, short research statement and the names and contact information of two references to *sukbin.lim(a)**nyu.edu <xinying.cai(a)nyu.edu>*.

Feb. 1, 2016

CfP: SASO 2016 - IEEE International Conference on Self-Adaptive and Self-Organizing Systems, September 12-16, Augsburg, Germany

by newsletter

************************************************************************* CALL FOR PAPERS Tenth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2016) Augsburg, Germany; 12-16 September 2016 http://uni-augsburg.de/saso2016 @SASO2016Conf ************************************************************************* Part of FAS* - Foundation and Applications of Self* Computing Conferences Co-located with: The International Conference on Cloud and Autonomic Computing (ICCAC 2016) http://iccac2016.se.rit.edu ------------------- Aims and Scope ------------------- The aim of the Self-Adaptive and Self-Organizing systems conference series (SASO) is to provide a forum for the foundations of a principled approach to engineering systems, networks, and services based on self-adaptation and self-organization. The complexity of current and emerging networks, software, and services, especially when dealing with dynamics in the environment and problem domain, has led the software engineering, distributed systems, and management communities to look for inspiration in diverse fields (e.g., complex systems, control theory, artificial intelligence, sociology, and biology) to find new ways of designing and managing such computing systems. In this endeavor, self-organization and self-adaptation have emerged as two promising interrelated approaches. They form the basis for many other self-* properties, such as self-configuration, self-healing, or self-optimization. Systems exhibiting such properties are often referred to as self-* systems. The tenth edition of the SASO conference embraces the inter-disciplinary nature and the scientific, empirical, and application dimensions of self-* systems and welcomes novel results on both self-adaptive and self-organizing systems research. The topics of interest include, but are not limited to: - Systems theory: theoretical frameworks and models; biologically- and socially-inspired paradigms; inter-operation of self-* mechanisms; - Systems techniques: techniques to specify and analyze self-* systems, like statistical physics, machine learning, multi-agent systems, or other novel techniques; - Systems engineering: reusable mechanisms, design patterns, architectures, methodologies; software and middleware development frameworks and methods, platforms and toolkits; hardware; self-* materials; governance of self-* systems, emergent behavior in self-* systems; - System properties: robustness, resilience, and stability; emergence; computational awareness and self-awareness; reflection; anti-fragility; - Cyber-physical and socio-technical systems: human factors and visualization; self-* social computers; crowdsourcing and collective awareness; human-in-the-loop; - Data-driven approaches: data mining; machine learning; data science and other statistical techniques to analyze, understand, and manage behavior of complex systems; - Education: experience reports; curricula; innovative course concepts; methodological aspects of self-* systems education; - Ethics and Humanities in self-* systems; - Applications and experiences with self-* systems in any of the following domains: + Smart-*: application of self-* principles to smart-grids, smart-cities, smart-environments, smart-vehicles + Industrial automation: embedded self-* systems, adaptive industrial plants, smart industries (Industry 4.0) + Transportation: autonomous vehicles, coordination between vehicles, pedestrians, and infrastructure, and traffic optimization + Unmanned systems: aerial vehicles, undersea vehicles, other robotic platforms + Internet of Things: challenges, applications, and benefits; self-* for network management, self-* applied to Cybersecurity We are looking for contributions that present novel theoretical or experimental results, novel design patterns, mechanisms, system architectures, frameworks or tools, or practical approaches and experiences in building or deploying real-world systems and applications. Contributions contrasting different approaches for engineering a given family of systems, or demonstrating the applicability of a certain approach for different systems, are equally encouraged. Likewise, papers describing substantial innovation or insights in the use and communication of self-* systems in the classroom are welcome. Where relevant and appropriate, accepted papers will also be encouraged to participate in the Demo or Poster Sessions. -------------------- Important Dates -------------------- Abstract submission: May 2, 2016 Paper submission: May 9, 2016 Rebuttal phase: June 16-20, 2016 Notification: June 23, 2016 Camera ready copy due: July 5, 2016 Conference: September 12-16, 2016 ---------------------------- Submission Instructions ---------------------------- Submissions can be up to 10 pages, formatted according to the standard IEEE Computer Society Press proceedings style guide, and submitted electronically in PDF format. Please register as authors and submit your papers using the SASO 2016 conference management system https://easychair.org/conferences/?conf=saso2016. The proceedings will be published by IEEE Computer Society Press, and made available as a part of the IEEE Digital Library. Note that a separate Call for Poster and Demo Submissions will also be issued. As per the standard IEEE policies, all submissions should be original, i.e., they should not have been previously published in any conference proceedings, book, or journal and should not currently be under review for another archival conference. We also highlight IEEE’s policies regarding plagiarism and self-plagiarism (http://www.ieee.org/publications_standards/publications/rights/ID_Plagiaris…) --------------------- Review Criteria --------------------- Papers should present novel ideas in the cross-disciplinary research context described in this call, motivated by problems from current practice or applied research. Both theoretical and empirical contributions should be highlighted, substantiated by formal analysis, simulation, experimental evaluations, comparative studies, and so on. Appropriate references must be made to related work. Because SASO is a cross-disciplinary conference, we encourage papers to be intelligible and relevant to researchers who are not members of the same specialized sub-field. Authors are also encouraged to submit papers describing applications. Application papers should provide an indication of the real world relevance of the problem that is solved, including a description of the deployment domain, and some form of evaluation of performance, usability, or comparison to alternative approaches. Experience papers are also welcome, especially if they highlight insights into any aspect of design, implementation or management of self-* systems that would be of benefit to practitioners and the SASO community. All submissions will be rigorously peer reviewed and evaluated on the basis of the quality of their technical contribution, originality, soundness, significance, presentation, understanding of the state of the art, and overall quality. ------------------------------- Conference General Chair ------------------------------- Wolfgang Reif University of Augsburg, DE -------------------- Program Chairs -------------------- Giacomo Cabri, University of Modena and Reggio Emilia, IT Gauthier Picard, École Nationale Supérieure des Mines de Saint-Étienne, FR Niranjan Suri, Florida Institute of Human and Machine Cognition, FL, USA

Jan. 31, 2016

Postdoc position in large-scale neural modeling -- Eliasmith lab

by Peter Blouw

In brief, the Eliasmith lab at the Centre for Theoretical Neuroscience has a position available for a 2-year postdoc. The focus is on large-scale spiking neural models that exhibit interesting behaviors and run on supercomputing infrastructure. "Interesting behaviour" is broadly defined, including vision, motor control, decision making, any variety of learning, audition, language processing, and so on. Full details below: *SOSCIP/IBM Canada Post-Doctoral Fellow (PDF) Research Scientist* Launched in 2012, SOSCIP was founded by seven Ontario universities and IBM Canada Limited as a collaborative research consortium, with a mandate to bring together academic researchers and small- and medium-sized companies to drive innovation using state-of-the-art advanced computing and big data analytics technologies, commercial outcomes for social and economic development in Ontario. New investments from IBM Canada and other stakeholders have enabled SOSCIP to expand its computing platforms and resources to increase capacity and add new members. With the addition of our three new academic partners, membership in the consortium has more than doubled over the last two years to 16 organizations. The IBM Canada Research & Development Centre is expanding, and we are seeking a post-doctoral fellow who has a PhD in Theoretical or Computational Neuroscience or a related field, with strong programming skills and experience in high-performance computing environments. This role will support a research project led by Dr. Chris Eliasmith in the Centre for Theoretical Neuroscience at the University of Waterloo. Dr. Eliasmith's lab constructs state-of-the-art, large-scale, neuron-level models of a wide variety of behaviours, recently publishing what remains the world's largest functional brain model, Spaun, in Science. These models are simulated in the software Nengo, which is able to run models on a wide variety of hardware platforms, or 'backends', including neuromorphic hardware. Recently, a backend for BlueGene/Q has been developed, allowing Nengo models, including Spaun, to run on the supercomputers housed at SOSCIP. The successful candidate will focus on scaling up models, including Spaun, to take full advantage of these hardware resources. Scaling will include developing theory and implementation of new behaviours, as well as increasing the biological fidelity of Nengo models. A strong publication record, with demonstrated applications of neural-level models to behaviour (e.g. vision, motor control, memory, decision making, etc.), neuron-level compartmental modeling, various applications of learning (deep learning, reinforcement learning, STDP, etc.), and large-scale modeling are greatly desired. Familiarity with Python, MPI, and Javascript would be beneficial. Education and Experience - PhD in Theoretical or Computational Neuroscience, or a related field - strong programming skills and experience in high-performance computing environments - experience working as part of a research team Work Location: Waterloo, Ontario Term of Contract: 2-years maximum IBM is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Jan. 31, 2016

Okinawa/OIST Computational Neuroscience Course 2016: one week left to apply

by Erik De Schutter

OKINAWA/OIST COMPUTATIONAL NEUROSCIENCE COURSE 2016 Methods, Neurons, Networks and Behaviors June 13 - June 30, 2016 Okinawa Institute of Science and Technology Graduate University, Japan https://groups.oist.jp/ocnc 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 13th through June 30th, 2016 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 4 - February 5, 2016. Applicants will receive confirmation of acceptance in March. Like in preceding years, OCNC will be a comprehensive three-week course covering single neurons, networks, and behaviors with ample time for student projects. The first week will focus exclusively on methods with hands-on tutorials during the afternoons, while the second and third weeks will have 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. There is no tuition fee. The sponsor will provide lodging and meals during the course and may support travel for those without funding. 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: • Erik De Schutter (OIST) • Sophie Deneve (École Normale Supérieure, France) • Kenji Doya (OIST) • Chris Eliasmith (University of Waterloo, Canada) • Tomoki Fukai (RIKEN BSI, Japan) • Michael Häusser (University College London, UK) • Yukiyasu Kamitani (ATR & Kyoto University, Japan) • Etienne Koechlin (École Normale Supérieure, France) • Bernd Kuhn (OIST) • Stefan Mihalas (Allen Institute for Brain Science, USA) • Partha Mitra (Cold Spring Harbor, USA) • Astrid Prinz (Emory University, USA) • John Rinzel (New York University, USA) • Yoko Yazaki-Sugiyama (OIST)

Jan. 29, 2016