January 2016 - Comp-neuro - lists.cnsorg.org

15 PhD positions for PACE, an EU funded Innovative Training Network for understanding Perception and Action in Complex Environments
by Laurent Perrinet May 19, 2016

May 19, 2016

Dear colleagues, PACE (Perception and Action in Complex Environments) is an Innovative Training Network funded by the Marie Sklodowska-Curie program of the European Union starting on April 1st, 2015. The network involves 10 academic and private full partners, from 6 European and associated countries (France, Spain, Italy, Netherlands, UK, Israel), plus 5 associated partners (private companies and public organizations). The network gathers a broad range of expertise from experimental psychology, cognitive neurosciences, brain imaging, technology and clinical sciences as well as transferable skills. The PACE network promotes interdisciplinary research and training in the field of human movement sciences with a strong emphasis on perception-action coupling in complex environments. We focus on changes of this coupling across lifespan and in pathological diseases affecting the nervous system. The goal is to train PhD students through collaborative research projects, international courses and workshops. -> 15 PhD positions, starting next fall, are offered across the different network sites. You can find a short description of the proposed PhD projects at the following link: http://www.int.univ-amu.fr/IMG/pdf/PACE_Table_positions.pdf Applications are welcome immediately and until the end of May (but some specific timing constraints may be enforced in some of the partners' sites: please get more information from local contacts). You will find further general information (sections 1 to 3), eligibility and application conditions (section 4) here: http://www.int.univ-amu.fr/-ITN-Marie-Curie-network-PACE Thanks for distributing this announcement to potential candidates, Laurent -- Laurent Perrinet - INT (UMR 7289)/CNRS http://invibe.net/LaurentPerrinet

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NEURAL COMPUTATION - April, 2014
by Terry Sejnowski April 24, 2016

April 24, 2016

Neural Computation - Contents -- Volume 26, Number 4 - April 1, 2014 Available online for download now: http://www.mitpressjournals.org/toc/neco/26/4 ----- Article Parametric Inference in the Large Data Limit Using Maximally Informative Models Justin Block Kinney, Gurinder Singh Atwal Letters Input Statistics and Hebbian Crosstalk Effects Anca R. Radulescu Learning Nonlinear Regularities in Natural Images by Modeling the Outer Product of Image Intensities Peng Qi, Xiaolin Hu Dissociable Forms of Repetition Priming: A Computational Model Kirill Makukhin, Scott Bolland Refined Rademacher Chaos Complexity Bounds With Applications to the Multi-Kernel Learning Problem Yunwen Lei, Lixin Ding Large Margin Low Rank Tensor Analysis Guoqiang Zhong, Mohamed Cheriet Large-scale Linear RankSVM Ching-Pei Lee, Chih-Jen Lin ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp SUBSCRIPTIONS - 2014 - VOLUME 26 - 12 ISSUES USA Others Electronic Only Student/Retired $70 $193 $65 Individual $124 $187 $115 Institution $1,035 $1,098 $926 Canada: Add 5% GST MIT Press Journals, 238 Main Street, Suite 500, Cambridge, MA 02142-9902 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-orders(a)mit.edu ------------

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ICMNS 2016: Deadline Extended to Feb. 7, 2016
by Zachary Kilpatrick March 27, 2016

March 27, 2016

*Abstract deadline extended to February 7, 2016* https://icmns2016.inria.fr/call-for-contributions/ <https://icmns2016.inria.fr/call-for-contributions/> There will also be a prize for best papers. International Conference on Mathematical Neuroscience (ICMNS 2016) at the Congress Center in Juan-les-Pins on the French Riviera May 29 to June 1, 2016 Tutorials: May 29 Main Conference: May 30 - June 1 https://icmns2016.inria.fr/ <https://icmns2016.inria.fr/> CONFIRMED SPEAKERS Wulfram Gerstner (École polytechnique fédérale de Lausanne) John Rinzel (New York University) Antoine Triller (École Normale Supérieure de Paris) Rachel Kuske (U British Columbia) Jonathan Rubin (U Pittsburgh) Hinke Osinga (U Aukland) Carina Curto (Penn State University) Ruben Moreno-Bote (Foundation Sant Joan de Deu) Hiroya Nakao (Tokyo Institute of Technology) Eric Shea-Brown (U Washington) Si Wu (Beijing Normal University) Alex Roxin (Centre de Recerca Matematica) PROGRAM COMMITTEE Toni Guillamon (Universitat Politècnica de Catalunya) Roland Potthast (U Reading) Gregory Faye (Université Paul Sabatier ) Wilhelm Stannat (TU Berlin) Jonathan Touboul (College de France) Gilles Wainrib (Ecole Normale Supérieure) Suzanne Ditlevsen (University of Copenhagen) Boris Gutkin (Ecole Normale Supérieure) Martin Wechselberger (U Sydney) Jonathan Rubin (U Pittsburgh) Martin Krupa (INRIA Sophia Antipoilis) Carlo Laing (Massey University) Andre Longtin (U Ottawa) Daniele Avitabile (U Nottingham) Jose Carrillo (Imperial College) Pascal Chossat (Université Nice Sophia Antipolis) Carson Chow (National Institutes of Health) Steve Zucker (Yale University) Eric Shea-Brown (U Washington) Rachel Kuske (U British Columbia) Laura Sacerdote (Universita di Torino) Reinhard Hopfner (Johannes-Gutenberg Universitat) Olivier Faugeras (INRIA - Sophia Antipolis) Paul Bressloff (U Utah) Steve Coombes (U Nottingham) CONFERENCE CHAIRS Romain Veltz (INRIA - Sophia Anitpolis) Zachary Kilpatrick (U Houston) Evelyn Buckwar (Johannes Kepler Universitat Linz)

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v5.7 of NeuroMorpho.Org released on 30 May, 2014
by NeuroMorpho Administrator March 10, 2016

March 10, 2016

Version 5.7 of NeuroMorpho.Org was released on 30 May, 2014. The release included 29 new data sets (1341 reconstructions), including from three new animal species (dragonfly, moth, and sheep). The database now contains 11,335 reconstructions from 144 contributing labs. More than 3.2 million reconstructions were downloaded in over 130,000 unique visits from 146 countries. Please visit the What's new<http://neuromorpho.org/neuroMorpho/WIN.jsp> page for details on data included in this release, including new species strains, brain regions, cell types, and experimental conditions. The Acknowledgements <http://neuromorpho.org/neuroMorpho/acknowl.jsp> include details on contributing labs, and the About<http://neuromorpho.org/neuroMorpho/about.jsp> page provides an updated overview of the repository content. A new user-friendly functionality, OntoSearch<http://neuromorpho.org/neuroMorpho/OntoSearch.jsp>, was introduced in this release, enabling more powerful searches of species and strains with automated synonym translation, taxonomical relations, and keyword auto-completion. The literature coverage database was also updated to include publications through March 2014. We are continuously grateful to all the data owners who freely share their data with the community. We always appreciate any and all feedback and comments. Sincerely, The NeuroMorpho.Org team -- Ruchi Parekh, Ph.D. NeuroMorpho.Org Project Lead Postdoctoral Research Fellow Center for Neural Informatics, Structures, and Plasticity Krasnow Institute for Advanced Study MS2A1, George Mason University Fairfax, VA 22030 (USA) Ph - +1-703-993-4382<tel:%2B1-703-993-4382> www.neuromorpho.org<http://www.neuromorpho.org/> nmadmin(a)gmu.edu<mailto:nmadmin@gmu.edu>?

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CfP: SASO 2016 - IEEE International Conference on Self-Adaptive and Self-Organizing Systems, September 12-16, Augsburg, Germany
by newsletter Jan. 31, 2016

Jan. 31, 2016

************************************************************************* 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

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Postdoc position in large-scale neural modeling -- Eliasmith lab
by Peter Blouw Jan. 31, 2016

Jan. 31, 2016

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.

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Okinawa/OIST Computational Neuroscience Course 2016: one week left to apply
by Erik De Schutter Jan. 29, 2016

Jan. 29, 2016

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)

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Conference announcement: "The neuroscience of decision-making"
by Paul Cisek Jan. 28, 2016

Jan. 28, 2016

38th International Symposium of the GRSNC The neuroscience of decision-making May 2-3, 2016 Université de Montréal WEBSITE: <http://www.grsnc.umontreal.ca/38s/> http://www.grsnc.umontreal.ca/38s/ PROGRAM: <http://www.grsnc.umontreal.ca/38s/prog_e.html> http://www.grsnc.umontreal.ca/38s/prog_e.html REGISTRATION: <http://appl.grsnc.umontreal.ca/en/symposium/38s/registration.cfm> http://appl.grsnc.umontreal.ca/en/symposium/38s/registration.cfm POSTER: <http://www.grsnc.umontreal.ca/38s/38s_poster.pdf> http://www.grsnc.umontreal.ca/38s/38s_poster.pdf We are pleased to announce the 38th symposium of the Groupe de Recherche sur le Système Nerveux Central (GRSNC) which is entitled "The neurosciences of decision-making". This symposium will be held on May 2-3, 2016 at the Université de Montréal, Pavillon 3200 Jean-Brillant, room B-2245 and the organizers are Drs Paul Cisek (UdeM), Alain Dagher (McGill), Lesley Fellows (McGill), John Kalaska (UdeM) et Peter Shizgal (Concordia). Research on the neural bases of decision-making has experienced a rapid growth in the last 20 years. It addresses a great diversity of questions, ranging from how animals weigh the costs and benefits of different actions to what goes wrong when humans exhibit maladaptive behavior, such as in addiction. In this symposium, we will discuss cutting-edge research on this topic, reviewing the progress that has been made and addressing the central open questions facing this rapidly developing field. In planning the sessions, we have paid particular attention to issues that stretch from the most basic neuroscience all the way to clinical applications. We will highlight converging evidence from the full range of neuroscientific methods applied in this field, considered within a diversity of conceptual frameworks. There will be four sessions of presentations by invited speakers from around the world as well as two contributed poster sessions. The presentations are regrouped in for sessions: * Brain representations of value: Common or multiple (Chairperson: Peter Shizgal) * Encoding and learning values: Neural and computational mechanisms (Chairperson: Alain Dagher) * Decision in the wild (Chairperson: John Kalaska) * Diseases and deviances (Chairperson: Lesley Fellows) Lecturers: Joshua D. Berke, Thomas Boraud, Paul Cisek, Alain Dagher, Peter Dayan, Nathaniel Daw, Lesley Fellows, J. Randall Flanagan, Michael J. Frank, Karl Friston, Hugh Garavan, Paul W. Glimcher, Joseph Kable, Elizabeth A. Murray, Michael L. Platt, David Redish, Michael N. Shadlen, Peter Shizgal, Daphna Shohamy and Jonathan D. Wallis. Submissions are invited for poster presentations. The deadline for submission is March 31, 2016 We would appreciate if you could forward this message to colleagues and students. Manon Dumas for the organizing committee Groupe de recherche sur le système nerveux central (GRSNC) Université de Montréal Département de neurosciences Pavillon Paul-G.-Desmarais, bureau 4115 Courriel: <mailto:m.dumas@umontreal.ca> m.dumas(a)umontreal.ca Téléphone: (514) 343-6366 Télécopieur: (514) 343-6113

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Research Internship position at Numenta
by Subutai Ahmad Jan. 28, 2016

Jan. 28, 2016

RESEARCH INTERNSHIP POSITION IN COMPUTATIONAL NEUROSCIENCE AND MACHINE LEARNING NUMENTA, Inc. About Numenta: Numenta was founded in 2005 and is a leader in the emerging field of machine intelligence. Its biologically inspired technology is based on a detailed and evolving theory of the neocortex first described in co-founder Jeff Hawkins’ book, On Intelligence. The current technology can be applied to anomaly detection in servers and applications, human behavior, and geo-spatial tracking data. Numenta is focused on understanding the computational principles behind the cortex in detail, and implementing practical systems that operate on those principles. NuPIC, Numenta's open source code base, is one of the top three most active machine learning projects on Github. For more details, please see www.numenta.com Job description: The Research Group at Numenta is looking for outstanding MS or PhD students or other research scientists for a paid internship during the Spring, Summer or Fall 2016. We are looking for candidates with expertise in Machine Learning, Computational Neuroscience and/or Natural Language Processing. Preference given to candidates with experience in one or more of the following areas: sequence learning, natural language processing, neuron modeling, and computational models of cortex. Numenta's interns will get exposure to all aspects of Hierarchical Temporal Memory (HTM) learning algorithms, participate in leading edge research in computational neuroscience, and get full clearance to publish their work and research source code. The internship commitment is for 3 to 4 months full time (longer appointments up to one year may be possible). We are located in Silicon Valley (Redwood City, CA). What you can expect to learn and how you might contribute: - The challenges of designing and implementing detailed models of cortical function that can be applied to real-world problems - Gain experience solving hard problems in domains such as natural language processing, streaming analytics, sensorimotor inference, and/or reinforcement learning - Participate in designing functional models of Layers 2/3, 4, 5, and 6, thalamocortical circuits, feedback circuits, and sensorimotor processing - Learn how to contribute to a top open source project, and improve your software engineering skills - Obtain a detailed understanding of Hierarchical Temporal Memory Desired qualifications: - Currently enrolled in a PhD program, or a recent PhD graduate, or equivalent research experience - Strong research background in machine learning or machine intelligence - Strong research background in computational neuroscience - Excellent algorithmic problem solving skills, and the ability to implement solutions in Python, C/C++, Java, etc. - Established track record of publications in leading peer reviewed conferences and journals - Excellent programming skills - Working knowledge of HTM algorithms a plus - Excellent written and verbal communication skills, and the ability to work in a team oriented environment - A belief that the best way to build intelligent machines is to understand the cortex How to apply: Qualified applicants should send the following to interns(a)numenta.com: - Cover letter describing their specific interest in Numenta. Please include any relevant experience with HTM algorithms or NuPIC. - Resume or CV, including list of relevant courses and published papers. Numenta is an equal opportunity employer supporting workforce diversity. IMPORTANT NOTE: Numenta is unable to consider internship applications from international researchers unless they are US Citizens, hold a Green Card, or are currently enrolled in a US University and eligible for OPT.

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Postdocs integrated into the Human brain Project – specifically data-driven modeling at the subcellular or network levels, or tool development/support
by Jeanette Hällgren Kotaleski Jan. 28, 2016

Jan. 28, 2016

Dear Colleagues, dear all, KTH Royal Institute of Technology, Stockholm, is currently recruiting postdocs to be working within the Human Brain Project. 1) Postdoc/application expert – specifically development of brain modeling tools: Specifically for the current position software applications providing user-friendly interface to cellular-level modelling tools will be developed, supported and used. These will include an optimization framework (for fitting electrical models of neurons to their observed electrical behaviour) and also a morphology pipeline (the tool used to analyse and validate neuron morphologies). More info and how to apply at: https://intra.kth.se/en/anstallning/karriar/karriar-och-kompetensutveckling… 2) Postdoc in computational systems (neuro)biology – specifically synaptic plasticity and neuromodulation: Specifically for the above position data-driven modeling of receptor induced cascades such as GPCR dependent cascades involved in neuromodulation and synaptic signaling will be done. More info and how to apply at: https://intra.kth.se/en/anstallning/karriar/karriar-och-kompetensutveckling… 3) Postdoc in brain simulations - specifically motor control and selection of behaviour: Specifically for the position, modeling of motor control and learning with basal ganglia as important components will be done. The modeling tools are mainly Nest and Neuron. More info and how to apply at: https://intra.kth.se/en/anstallning/karriar/karriar-och-kompetensutveckling… All the best, Jeanette Hellgren Kotaleski Prof, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm

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