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ANDA 2018 - G-Node Advanced Neural Data Analysis Course, March 5 - 22, 2018, Jülich, Germany
by Frings, Maren Sept. 5, 2017

Sept. 5, 2017

ANDA 2018 - G-Node Advanced Neural Data Analysis Course March 5 - 22, 2018 Haus Overbach, Juelich-Barmen, Germany Techniques to record neuronal data from populations of neurons are rapidly improving. Simultaneous recordings from hundreds of channels are possible while animals perform complex behavioral tasks. The analysis of such massive and complex data becomes increasingly challenging. This advanced course aims at providing deeper training in state-of-the-art analysis approaches in systems neuroscience. The course is addressed to excellent master and PhD students and young researchers who are interested in learning advanced techniques in data analytics and in getting hands-on experience in the analysis of electrophysiological data. Internationally renowned researchers will give lectures on statistical data analysis and data mining methods with accompanying exercises. Students will define and perform their own analyses on provided data to solve a challenge. Participants are required to have a strong interest in data analysis, a background in a mathematical or related field, knowledge of algebra, matrix operations, and statistics, and need to have solid programming experience (preferably in Python). Date and Venue March 5 - 22, 2018 Haus Overbach, Juelich-Barmen, Germany Faculty · Moshe Abeles, Bar-Ilan Univ, Israel · Michael Denker, Juelich Research Center and RWTH Aachen Univ, Germany · Alain Destexhe, CNRS, Gif sur Yvette, France · Sonja Grün, Juelich Research Center and RWTH Aachen Univ, Germany · Björn Kampa, RWTH Aachen, Germany · Christian Machens, Champalimaud Centre for the Unknown, Portugal · Martin Nawrot, University of Cologne, Germany · Yifat Prut, Hebrew Univ Jerusalem, Israel · Alexa Riehle, CNRS, Marseille, France · Jonathan Victor, Weill Cornell Medical College, USA · Thomas Wachtler, G-Node, LMU Munich, Germany Topics covered Single neuron properties and statistics · Stochastic processes · Surrogate methods · Detection of spatio-temporal patterns · Unitary Events · Statistical analysis of massively parallel spike data · Higher-order correlation analyses · Spike-LFP relationship · Population coding · State space analysis · Machine learning · Data mining · Data management, reproducibility, data sharing · Elephant toolbox Requirements Applicants should be familiar with linear algebra, probability, differential and integral calculus and experienced using Python or Matlab. Preparatory reading material will be provided. Students should bring their own laptops and should be able to install software on their system. Students that do not have a suitable laptop should indicate this immediately after acceptance to the course. We will be able to provide a small number of laptops for the time of the course. Course Fee A course fee of 800 Euros will be charged to accepted students. The course fee contributes to covering accommodation and meals, including coffee breaks. A few stipends will be available to support students with documented need of funding. Housing Accommodation in 2-bed rooms for students will be provided at the course site. How to apply The application should include · a letter of motivation (max 1 page) · curriculum vitae (please indicate the relevant courses you have taken) · description of programming experience · a letter of recommendation. Please send all documents as a single PDF file to <advanced-course(a)g-node.org<mailto:advanced-course@g-node.org>>. Deadlines Applications must be received by October 15, 2017. Early application is encouraged because number of participants is limited. For further information see https://portal.g-node.org/advanced-course-2018/ Organizers · Sonja Grün, Juelich Research Center and RWTH Aachen Univ, Germany · Martin Nawrot, University of Cologne, Germany · Thomas Wachtler, G-Node, Ludwig-Maximilians-Universität München, Germany Dr. Maren Frings Scientific Coordinator Institute of Neuroscience and Medicine (INM-6) Computational and Systems Neuroscience & Institute for Advanced Simulation (IAS-6) Theoretical Neuroscience Forschungszentrum Jülich GmbH and JARA 52425 Jülich, Germany Building 15.22 Room 4004 Phone +49 2461 61-9468 Fax +49 2461 61-9460 m.frings(a)fz-juelich.de<mailto:m.frings@fz-juelich.de> ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ 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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Bernstein 2017 Workshop, "The Neural Code: Universal Grammar or Area-Specific Mechanisms?"
by Hazem Toutounji Sept. 4, 2017

Sept. 4, 2017

Dear Colleagues, We would like to draw your attention to the upcoming workshop *The Neural Code: Universal Grammar or Area-Specific Mechanisms?* at the *Bernstein Conference 2017*, which will take place preceding the conference on *September 12-13* in *Göttingen, Germany*. *Abstract:* The brain responds to sensory stimuli with complex, yet structured, patterns of action potentials, which in turn gives rise to perception, action, remembrance and other facets of the organism's mental life. Finding order in the complexity of neural activity, and the quest for the neural code, occupied much of both experimental and theoretical neuroscience in the last decades. Several general theories of how the brain might encode and transfer information have been suggested, partly backed by experimental evidence. Attractor dynamics, binding by synchrony, brain oscillations acting at multiple temporal scales and Bayesian coding are some of the more prominent proposals into this direction. The debate whether these strategies are different facets of a fundamental neural grammar, or are local codes within functionally distinct brain regions, is far from settled. The aim of the workshop is to bring together experts in the field of neural coding, in order to discuss basic mechanisms of information encoding and the deeper question of whether there is a unifying grammar of neural representations. Schedule: Tue, Sept 12, 2017 13:00 Damian Battaglia, Aix-Marseille University, Marseille, France *Do oscillations modulate information processing? From routing states to computing modes* 13:45 Mattia Rigotti, Physical Sciences Department, IBM T. J. Watson Research Center, Yorktown Heights, NY *Functional role of the dimensionality of neural responses* 14:30 General discussion 15:00 Coffee Break 15:30 Máté Lengyel, University of Cambridge, UK *A sampling-based neural code of uncertainty in V1 (and I bet elsewhere, too)* 16:15 Nicolas Brunel, University of Chicago, Chicago, USA *Statistics of connectivity in networks optimizing information storage: fixed point attractors vs sequences* 17:00 Misha Tsodyks, Weizmann Institute of Science, Israel *Population spikes codes for processing and working memory* 17:45 General discussion Wed, Sept 13, 2017 9:00 Stefano Panzeri, Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genova, Italy *The relationship between cross-cell coupling and the timescales of population coding across cortex* 9:45 Thilo Womelsdorf, Vanderbilt University, Nashville, Tennessee, USA *Neural coding and inter-areal integration of goal-relevant information using spike bursts* 10:30 *Coffee break* 11:00 Pascal Fries, Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany *Rhythms for Cognition: Communication through Coherence* 11:45 Genaral discussion Kind regards, Eleonora Russo and Hazem Toutounji -- Dr. rer. nat. Hazem Toutounji Postdoctoral Researcher in Theoretical Neuroscience Central Institute of Mental Health Medical Faculty Mannheim of Heidelberg University Square J5, 68159 Mannheim, Germany office: +49-621-1703-2366

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PhD Opportunities in the Department of Cognitive Sciences at the University of California, Irvine
by Jeff Krichmar Sept. 4, 2017

Sept. 4, 2017

Dear colleagues, The Department of Cognitive Sciences at the University of California, Irvine is seeking graduate students for admission in Fall 2018. We invite exceptional and highly motivated candidates to apply for full-time PhD research in computational neuroscience, machine learning, computational vision, neural networks, and neurorobotics. Students will have the opportunity to work in the Cognitive Anteater Robotics laboratory (PI: Jeff Krichmar), the Neuromorphic Machine Intelligence laboratory (PI: Emre Neftci), and the newly established Visual Perception laboratory (PI: Zyg Pizlo) at UC Irvine. For more information about ongoing research see: · http://www3.psych.purdue.edu/~zpizlo/ · http://nmi-lab.org/ · http://www.socsci.uci.edu/~jkrichma/CARL/ Projects include: · Cognitive robotics for decision-making, planning, perception, and memory. · Efficient coding in the brain. · Models of neuromodulation. · Neurobiologically inspired vision models. · Models of human problem solving. · Neuromorphic engineering and machine learning · Spike-based computation Applicants should have strong mathematical and computer programming skills, as well as good communication skills. Successful applicants will receive funding toward their Ph.D. for at least 5 years. Founded in 1965, UCI is the youngest member of the prestigious Association of American Universities. The campus has produced three Nobel laureates and is known for its academic achievement, premier research, innovation and anteater mascot. UCI has more than 30,000 students and offers 192 degree programs. It’s located in one of the world’s safest and most economically vibrant communities and is Orange County’s second-largest employer, contributing $5 billion annually to the local economy. For more information about the Cognitive Sciences graduate program, please see: http://www.cogsci.uci.edu/graduate/index.php Jeff Krichmar Professor Department of Cognitive Sciences University of California, Irvine Email: jkrichma(a)uci.edu Website: http://www.socsci.uci.edu/~jkrichma Emre Neftci, PhD (ETH Zurich) Assistant Professor Neuromorphic Machine Intelligence Lab (http://nmi-lab.org/) Department of Cognitive Sciences, University of California, Irvine Email: eneftci(a)uci.edu Zygmunt Pizlo Professor Falmagne Endowed Chair in Mathematical Psychology Department of Cognitive Sciences University of California, Irvine Email: zpizlo(a)uci.edu

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[Extended Deadline-CFP] - HAI 2017 Workshop: Representation Learning for Human and Robot Cognition
by Amir Aly Sept. 4, 2017

Sept. 4, 2017

CALL FOR PAPERS **Apologies for cross posting ** The full day workshop: "*Representation Learning for Human and Robot Cognition*" In conjunction with the *5th International Conference on Human-Agent Interaction* *- Bielefeld - Germany - October * *17th, 2017* *Webpage: **http://cognitive-mirroring.org/en/events/hai2017_workshop/* <http://cognitive-mirroring.org/en/events/hai2017_workshop/> *I. Aim and Scope *Creating intelligent and interactive robots has been subject to extensive research studies. They are rapidly moving to the center of human environment so that they collaborate with human users in different applications, which requires high-level cognitive functions so as to allow them to understand and learn from human behavior. To this end, an important challenge that attracts much attention in cognitive science and artificial intelligence, is the “Symbol Emergence” problem, which investigates the bottom-up development of symbols through social interaction. This research line employs representation learning based models for understanding language and action in a developmentally plausible manner so as to make robots able to behave appropriately on their own. This could open the door to robots to understand syntactic formalisms and semantic references of human speech, and to associate language knowledge to perceptual knowledge so as to successfully collaborate with human users in space. Another interesting approach to study representation learning is “Cognitive Mirroring”, which refers to artificial systems that could make cognitive processes observable, such as the models that could learn concepts of objects, actions, and/or emotions from humans through interaction. A key idea of this approach is that robots learn individual characteristics of human cognition rather than acquiring a general representation of cognition. In this way, the characteristics of human cognition become observable and can be measured as modifications in model parameters, which is difficult to verify through neuroscience studies only. In this workshop, we invite researchers in artificial intelligence, cognitive science, cognitive robotics, and neuroscience to share their knowledge and research findings on representation learning, and to engage in cutting-edge discussions with other experienced researchers so as to help promoting this research line in the Human-Agent Interaction (HAI) community. *II. Keynote Speakers * 1. *Beata Joanna Grzyb *– Radboud University – The Netherlands 2. *Thomas Hermann*– Bielefeld University – Germany 3. *Tetsuya Ogata *– Waseda University – Japan 4. *Erhan Oztop *– Ozyegin Universiy – Turkey 5. * Stefan Wermter *– University of Hamburg – Germany *III. Submission * 1. For paper submission, use the following EasyChair web link: *Paper Submission <https://easychair.org/conferences/?conf=rlhrc2017>*. 2. Use the ACM SIGCHI format: *ACM SIGCHI Templates <http://www.sigchi.org/publications/chipubform>*. 3. Submitted papers should be limited to 2-4 pages maximum. The primary list of topics covers the following points (but not limited to): - Computational model for high-level cognitive capabilities - Predictive learning from sensorimotor information - Multimodal interaction and concept formulation - Human-robot communication and collaboration based on machine learning - Learning supported by external trainers by demonstration and imitation - Bayesian modeling - Learning with hierarchical and deep architectures - Interactive reinforcement learning * IV. Important Dates * 1. Paper submission: *15-September-2017* 2. Notification of acceptance: *25-September-2017* 3. Camera-ready version: *5-**October-2017* 4. Workshop: *17-October-2017* *V. Organizers * 1. *Takato Horii *– Osaka University – Japan 2. *Amir Aly *– Ritsumeikan University – Japan 3. *Yukie Nagai *– National Institute of Information and Communications Technology – Japan 4. * Takayuki Nagai *– The University of Electro-Communications – Japan -- *Amir Aly, Ph.D.* Senior Researcher Emergent Systems Laboratory College of Information Science and Engineering Ritsumeikan University 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577 Japan

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Bernstein 2017 workshop: "Information transmission and communication in brain circuits"
by alireza valizadeh Sept. 4, 2017

Sept. 4, 2017

Dear All, We would like to draw your attention to the half day workshop *"Information transmission and communication in brain circuits"* at Bernstein Conference 2017, Sep 13, Göttingen, Germany. *Abstract:* The question of how the brain integrates the mutiplicity of local processes dispersed through its entire anatomy is a fundamental question in neuroscience. Any single cognitive function may involve several specialized areas whose association is mediated by the functional integration among them. Such integration is mediated by information exchange between brain areas through the routes which can change in fast timescales over which the structure is fixed, providing a flexible effective connectivity despite the rigidity of the infrastructure over fast timescales. The flexibility of the information routing and dynamic effective connectivity are a consequence of the multistability of the collective dynamics of the brain networks. In other words, a single structural connectivity can support plenty of degenerate dynamical states for each of which a special pattern of information transfer between the nodes is observed. Neuronal collective oscillations are hypothesized to provide such a basis for the dynamics communication between brain regions. Several lines of experimental evidences and theoretical arguments indicate that the phase relations between the oscillations of different brain regions can alter effective connectivity by modulating the gain of mutual influence between them. In this workshop the notion of information transfer in brain circuits and the role of brain rhythms in providing a dynamic effective communication network will be reviewed and the latest theoretical and experimental achievements will be presented. *Speakers:* - Wolf Singer (Max Planck Institute), - Mark Timme (Max Planck Institute) - Demian Battaglia (Aix-Marseille University) - Christoph Kirst (The Rockefeller University) - Santiago Canals (Instituto de Neurociencias de Alicante) - Raul Vicente (University of Tartu) - Leonardo Gollo (QIMR Berghofer Medical Research Institute) - Alireza Valizadeh (Institute for Advanced Studies in Basic Sciences) *Website:* http://www.nncn.de/en/bernstein-conference/2017/satellite-workshops/informa… Best regards, Alireza Valizadeh, Claudio Mirasso ------------------------------------------------------------------------ Alireza Valizadeh Associate professor Neurophysics lab, Institute for Advanced Studies in Basic Sciences (IASBS) School of cognitive sciences, Institute for research in fundamental sciences (IPM) Iran Tel:(+98) 24 3315 2120 Fax:(+98) 24 3315 2104 valizade(a)iasbs.ac.ir Web: http://www.iasbs.ac.ir/~valizade/index.html ------------------------------------------------------------------------

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CfPs Journal of Integrative Neuroscience: Brain-Inspired Intelligence Technology
by Reinoud Maex Sept. 2, 2017

Sept. 2, 2017

Call for Papers Special issue of the Journal of Integrative Neuroscience on Brain-Inspired Intelligence Technology Guest Editors: R.J. Martis, H. Lin, E. Barakova and Y. Zeng BRAIN-INSPIRED INTELLIGENCE TECHNOLOGY Brain-inspired intelligence technology aims to showcase the principles and mechanisms of human intelligence through development of brain-inspired intelligent systems. It is an effort to extract, integrate and analyse these principles and mechanisms across scale from quantum neuroscience to cognitive science research in pioneering the next wave of sentient technologies. The special issue is unprecedented, showcasing brain-inspired technology beyond 2020. Deadline for submission:25 November 2017 How to Submit: Authors are requested to submit their manuscript via the submission system available at http://msTracker.com/submit1.php?jc=jin In the “Cover Letter” box please indicate you are submitting your paper to the special issue on Brain-Inspired Intelligence Technology Topics of relevance include: * Biophysical neural networks * Brain-inspired cognitive models * Wetware design * Neurophotonics * Elemental conscious constructs * Quantum entanglement in agents * Cognitive technology supporting brain-inspired intelligence * Brain connectome based on optical nanoscopy technology * Observer-independent intelligence * Pico-scale resolution patch-clamping * Brain-inspired super and general artificial intelligence * New deep neural networks for brain-inspired learning * Brain-inspired intelligent hardware infrastructures * Cognitive neurorobotics For more information contact: Yi Zeng, Ph.D Deputy Director Research Center for Brain-inspired Intelligence Institute of Automation Chinese Academy of Sciences Beijing, China, 100190 Email: yi.zeng(a)ia.ac.cn see also http://www.iospress.nl/wp-content/uploads/2017/03/CfP_Brain-Inspired_Intell…

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APA Technology, Mind, & Society Conference - Submissions due Oct 20
by Jeff Krichmar Sept. 2, 2017

Sept. 2, 2017

Dear Colleagues, This upcoming APA conference on Technology, Mind, & Society may be of interest to many of you. Visit: http://www.apascience.org/conference/index.html The American Psychological Association will hold an interdisciplinary conference on Technology, Mind, and Society in Washington, D.C., on April 5-7, 2018. Scientists, practitioners, policymakers, and students from around the world are invited to participate in the event. The conference will provide a venue for reporting and assessing current efforts to understand and shape the interactions of human beings and technology, for identifying priorities for future work, and for promoting exchange and collaboration among participants. The conference will feature four keynote speakers: Cynthia Breazeal (MIT), Justine Cassell (Carnegie Mellon), Eric Horvitz (Microsoft Research), and Sandy Pentland (MIT). APA invites you and your colleagues and students to submit papers, symposia, and posters for this conference, which will be organized around the following broad themes: • Basic research: How humans understand and use technology, impacts of technology on human experience and behavior, human-technology interactions as mutually adaptive systems, role of technology in advancing other areas of scientific research, and related topics. • Foundations of technology design: Development of technologies informed by psychological, behavioral, and social science research. • Applications: Development, use, and impact of specific technologies in domains such as aging, education, mental and physical health, recreation, and the workplace. • Broader implications: Ethical and policy questions concerning the opportunities and challenges arising from human-technology interactions. The deadline for submissions is October 20, 2017. Submissions can be made here: https://www.openconf.org/APAScience2018TMS/openconf.php The conference is open to researchers, professionals, and students in all relevant areas, including psychology and other behavioral and social sciences, neuroscience, computer science, engineering, design, health research, education research, city and regional planning, public policy, history of science and technology, and philosophy. The conference aims to address the full range of contemporary and emerging technologies. These include but are not limited to artificial intelligence, robotics, mobile devices, social media, virtual/augmented reality, gaming, geographic information systems, autonomous vehicles, and biomedical technologies (e.g., brain-machine interfaces, genetic engineering). APA is sponsoring the conference in cooperation with the Association for the Advancement of Artificial Intelligence (AAAI) and the Association for Computing Machinery — Special Interest Group for Computer-Human Interaction (ACM SIGCHI). We look forward to seeing you at the Technology, Mind, and Society Conference! For additional information, see the conference website. If you have any questions, please contact the APA Science Directorate (science(a)apa.org) Jeff Krichmar Department of Cognitive Sciences 2328 Social & Behavioral Sciences Gateway University of California, Irvine Irvine, CA 92697-5100 jkrichma(a)uci.edu http://www.socsci.uci.edu/~jkrichma

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Scientist I/II - Computational Neuroscience at Allen Institute for Brain Science
by Stefan Mihalas Sept. 1, 2017

Sept. 1, 2017

POSITION SUMMARY We are seeking to fill a position at the level of Scientist to work on coarse-grained models of cortical networks aiming to understand how the observed structure and activity gives relate to cortical computations necessary for visual processing (e.g. figure ground segregation, integration of context). We use mouse vision as a model system and this position will focus on using population statistics (http://alleninstitute.github.io/dipde/) and filter neuron model simulation tools. More specifically, the scientist will work on (i) fitting network models with simple neurons which network structures are consistent with the observed mesoscopic connectivity and in vivo cellular activity, (ii) simulate the activity of such networks at neuronal an population levels and (iii) analyzing the relation between observed network structure and that predicted from different models of cortical computations. ESSENTIAL DUTIES AND RESPONSIBILITIES * Participate in team efforts to find network parameters which are consistent with activity (http://observatory.brain-map.org/visualcoding/) and connectivity (http://connectivity.brain-map.org/) data. * Simulate cortical networks parameterized from experimental data using population and simplified neuron model simulation tools. * Analyze how computations in vision (e.g. figure/ground segregation, integration of context) result from networks similar to those simulated. * Interact with groups performing simulations at other levels of resolution and with experimental groups. * Maintain clear and accurate communication with supervisor and team members. * Publish/present findings in peer-reviewed journals/scientific conferences. BASIC QUALIFICATIONS SCIENTIST I * PhD degree in computational neuroscience, physics, mathematics, applied mathematics or related field. * Strong background in scientific computing is required. * Experience in computational neuroscience is preferred. SCIENTIST II * PhD degree in computational neuroscience, physics, mathematics, applied mathematics or related field. * 4+ years of postdoctoral experience in computational science * Preferred Computational neuroscience * Strong background in scientific computing is required. * Strong publication record. Preferred Qualifications: * Ability to meet aggressive timelines and deliverables in a collaborative environment. * Proven independent thinking and flexibility. * Strong written and verbal communication skills * Experience in pursuing research projects in collaborative fashion. Our mission at the Allen Institute for Brain Science is to accelerate the understanding of how the human brain works in health and disease. By implementing a team science approach on a large scale, we strive to generate useful public resources, drive technological innovations and discover fundamental brain properties through integration of experiments, modeling and theory. To apply please visit https://www.alleninstitute.org/what-we-do/brain-science/careers/job-search/. Applications will be considered on an ongoing basis. Apologies for coss-posting, Stefan Mihalas Assistant Investigator Allen Institute for Brain Science www.alleninstitute.org<http://www.alleninstitute.org/> Affiliate Assistant Professor Department of Applied Mathematics University of Washington

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5th Baltic-Nordic School on Neuroinformatics (BNNI 2017)
by Marja-Leena Linne Sept. 1, 2017

Sept. 1, 2017

5th Baltic-Nordic School on Neuroinformatics BNNI 2017 Theoretical modelling of brain functions in neurological and psychiatric disorders: Advancing future neuroscience and medicine through Neuroinformatics methods Place: Neuroscience Institute Lithuanian University of Health Sciences Eiveniu str.4, Kaunas Lithuania Time: 6-7 October 2017 More information and applications at: web.lsmuni.lt/bnni/en Important dates: 10 September 2017: Application deadline 12 September 2017: Acceptance notification 6-7 October 2017: School We invite advanced master students, doctoral students, and postdoctoral researchers to participate in the BNNI 2017 to be held at the Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania. The course is interdisciplinary and covers modeling at different levels of organization of the brain, focusing on neurological and psychiatric disorders. The course combines lectures, tutorials and computer exercises. This school is the fifth in the series of the Baltic-Nordic Courses on Neuroinformatics (BNNI 2013 in Kaunas, Lithuania; BNNI 2014 in Tampere, Finland; BNNI 2015 in Tartu, Estonia; BNNI in Warsaw 2016, Poland). The target audience of the course will be advanced master students, doctoral students and postdoctoral researchers in biomedical and technology sciences, from medicine, biology, psychology, to mathematics, informatics, information technology, physics, chemistry, who would like to get an introduction to neuroinformatics and computational neuroscience. Some experience with programming and quantitative reasoning as well as strong interest in computational and mathematical modeling of the brain will be desirable but not necessary to benefit from the school. Last year we had participants from 14 countries all over the world! Faculty includes: Marja-Leena Linne, Tampere University of Technology, Finland; The Human Brain Project Bruce Graham, University of Stirling, UK Daniel Wojcik, Nencki Institute of Experimental Biology, Warsaw, Poland Arnd Roth, University College London, UK Peter Jedlicka, NeuroScience Center, Goethe-University, Frankfurt, Germany Tuomo Mäki-Marttunen, Simula Research Laboratory, Oslo, Norway Inga Griskova-Bulanova, Institute of Bioscience, Vilnius University, Lithuania Rima Naginiene, Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania Andrius Radziunas, Department of Neurosurgery, Medical Academy, and Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania Ausra Saudargiene, Neuroscience Institute, Lithuanian University of Health Sciences, and Vytautas Magnus University, Kaunas, Lithuania and others. Venue: The lectures will be held at the Neuroscience Institute, Lithuanian University of Health Sciences, Eivenių str. 4, Kaunas, Lithuania Practical arrangements: There is a small tuition fee of 50 euros. The organizers will provide teaching materials, meals and coffee during the course. The participants are expected to cover their travel and health insurance expenses as well as lodging. The course is supported by the Research Council of Lithuania and Lithuanian University of Health Sciences. We are looking forward to welcoming you at the BNNI 2017 in Kaunas, Lithuania!

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Doctoral student position - Robot-assisted modeling of spatial navigation paradigms in biological organisms - DEADLINE EXTENDED
by samarasinghe＠ini.rub.de Sept. 1, 2017

Sept. 1, 2017

Please note that the deadline for applications to the position below has been extended to *15.09.2017*. *Research **Position **at the Institute for Neural Compu**ta**ti**o**n * A position as *d**octoral student **in integrative **n**euroscience and **c**ognitive **s**cience *is available immediately in the group of Prof. Sen Cheng in the Institute for Neural Computation at the Ruhr University Bochum, Germany. The research will focus on robot-assisted modeling of spatial navigation paradigms in biological organisms. Robotic simulations, as well as, physical robots will be used to develop and evaluate the desired models. The position will be funded at 50% of the standard salary scale TV-L E13. It is initially limited to 1 year with the possibility of extension, depending on the availability of funding. Candidates should have an excellent degree in neuroscience, physics, mathematics, engineering, or a related field. Competence in mathematical modeling, and excellent programming skills (Python, C/C++, or Matlab) are mandatory. Candidates are further required to have a strong background in at least one of the following fields: robotics, computational neuroscience, or cognitive modeling. Experience with interdisciplinary research in integrative neuroscience and cognitive science and with collaborative research would be a further asset. The working language at the institute is English. To apply, please send a statement of your research interests, academic transcripts, and a complete CV in one PDF file to samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de> by *15**.09****.2017*. Please also request from at least two academic referees that they send letters of reference directly to the same email address. Further information may be available at https://www.ini.rub.de/the_institute/jobs/. The Ruhr University Bochum provides a dynamic research environment in neuroscience and cognitive science. The Institute for Neural Computation unifies various core competencies extending from experimental and theoretical neuroscience to machine learning and robotics. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Universitätstr. 150 D-44780 Bochum Tel: +49 (0)234 32 27316 Email: samarasinghe(a)ini.rub.de Hours: Monday 9-12 & 14-16; Friday 9-12 & 14-16; Wednesday 12 - 16

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