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Leaders and followers: Quantifying consistency in spatio-temporal propagation pattern
by Thomas Kreuz Aug. 15, 2017

Aug. 15, 2017

Dear all, may I kindly draw your attention to our paper on the new multivariate directional measure *SPIKE-Order*. In this paper we propose a new approach to quantify consistency of spatio-temporal propagation patterns in sequences of discrete events (e.g. spike trains). This includes a sorting from leader to follower. As usual we show some applications to neurophysiological data. *Leaders and followers: Quantifying consistency in spatio-temporal propagation pattern <http://iopscience.iop.org/article/10.1088/1367-2630/aa68c3/meta>* Thomas Kreuz, Eero Satuvuori, Martin Pofahl and Mario Mulansky New J. Phys., *19*, 043028 (2017). Abstract: Repetitive spatio-temporal propagation patterns are encountered in fields as wide-ranging as climatology, social communication and network science. In neuroscience, perfectly consistent repetitions of the same global propagation pattern are called a *synfire pattern*. For any recording of sequences of discrete events (in neuroscience terminology: sets of spike trains) the questions arise how closely it resembles such a synfire pattern and which are the spike trains that lead/follow. Here we address these questions and introduce an algorithm built on two new indicators, termed *SPIKE-order* and *spike train order*, that define the *synfire indicator* value, which allows to sort multiple spike trains from leader to follower and to quantify the consistency of the temporal leader-follower relationships for both the original and the optimized sorting. We demonstrate our new approach using artificially generated datasets before we apply it to analyze the consistency of propagation patterns in two real datasets from neuroscience (giant depolarized potentials in mice slices) and climatology (El Niño sea surface temperature recordings). The new algorithm is distinguished by conceptual and practical simplicity, low computational cost, as well as flexibility and universality. Implementations are provided online in three free code packages called SPIKY <http://www.fi.isc.cnr.it/users/thomas.kreuz/Source-Code/SPIKY.html> (Matlab GUI), PySpike <http://mariomulansky.github.io/PySpike/>(Python library) and, most recently, cSPIKE <http://www.fi.isc.cnr.it/users/thomas.kreuz/Source-Code/cSPIKE.html>(Matlab command line with MEX-files). Best regards, Thomas Kreuz PS: Three further recent articles: *Measures of spike train synchrony for data with multiple time scales <http://www.sciencedirect.com/science/article/pii/S0165027017301619>* Eero Satuvuori, Mario Mulansky, Nebojsa Bozanic, Irene Malvestio, Fleur Zeldenrust, Kerstin Lenk, Thomas Kreuz JNeurosci Methods *287*, 25 (2017). Background Measures of spike train synchrony are widely used in both experimental and computational neuroscience. Time-scale independent and parameter-free measures, such as the ISI-distance, the SPIKE-distance and SPIKE-synchronization, are preferable to time scale parametric measures, since by adapting to the local firing rate they take into account all the time scales of a given dataset. New method In data containing multiple time scales (e.g. regular spiking and bursts) one is typically less interested in the smallest time scales and a more adaptive approach is needed. Here we propose the A-ISI-distance, the A-SPIKE-distance and A-SPIKE-synchronization, which generalize the original measures by considering the local relative to the global time scales. For the A-SPIKE-distance we also introduce a rate-independent extension called the RIA-SPIKE-distance, which focuses specifically on spike timing. Results The adaptive generalizations A-ISI-distance and A-SPIKE-distance allow to disregard spike time differences that are not relevant on a more global scale. A-SPIKE-synchronization does not any longer demand an unreasonably high accuracy for spike doublets and coinciding bursts. Finally, the RIA-SPIKE-distance proves to be independent of rate ratios between spike trains. Comparison with existing methods We find that compared to the original versions the A-ISI-distance and the A-SPIKE-distance yield improvements for spike trains containing different time scales without exhibiting any unwanted side effects in other examples. A-SPIKE-synchronization matches spikes more efficiently than SPIKE-synchronization. Conclusions With these proposals we have completed the picture, since we now provide adaptive generalized measures that are sensitive to firing rate only (A-ISI-distance), to timing only (ARI-SPIKE-distance), and to both at the same time (A-SPIKE-distance). *Robustness and versatility of a nonlinear interdependence method for directional coupling detection from spike trains <https://journals.aps.org/pre/abstract/10.1103/PhysRevE.96.022203>* Irene Malvestio, Thomas Kreuz, Ralph G Andrzejak Physical Review E *96*, 022203 (2017). The detection of directional couplings between dynamics based on measured spike trains is a crucial problem in the understanding of many different systems. In particular, in neuroscience it is important to assess the connectivity between neurons. One of the approaches that can estimate directional coupling from the analysis of point processes is the nonlinear interdependence measure L. Although its efficacy has already been demonstrated, it still needs to be tested under more challenging and realistic conditions prior to an application to real data. Thus, in this paper we use the Hindmarsh-Rose model system to test the method in the presence of noise and for different spiking regimes. We also examine the influence of different parameters and spike train distances. Our results show that the measure L is versatile and robust to various types of noise, and thus suitable for application to experimental data. *SPIKE-order <http://www.scholarpedia.org/article/SPIKE-order>* Thomas Kreuz, Eero Satuvuori, Mario Mulansky Scholarpedia, *12*(7):42441 (2017). -- Institute for complex systems, CNR Via Madonna del Piano 10 50119 Sesto Fiorentino (Italy) Tel: +39-349-0748506 Email: thomas.kreuz(a)cnr.it Webpage: http://www.fi.isc.cnr.it/users/thomas.kreuz/

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Research Associate, Neuroimaging analyst, Western University
by Jorn Diedrichsen Aug. 15, 2017

Aug. 15, 2017

Western University has received a $66M investment from the Canada First Research Excellence Fund (CFREF). This investment will bring together researchers from across the University under a unifying initiative called BrainsCAN. The mission of BrainsCAN is to reduce the burden of brain disorders that affect sensory, cognitive, and motor functions. The initiative aims at extending and mobilizing knowledge of the mappings between neural circuits and mental functions to deliver evidence-based interventions. The Research Associate, Neuroimaging Analyst will apply their expertise and knowledge to support ongoing research projects directed by the principal investigators of the BrainsCAN initiative. The incumbent will become part of BrainsCAN’s Computational Core, which aims to develop new computational techniques for the analysis of behavioral, brain imaging, and neuronal data. The incumbent will play a lead role in training staff, students and postdoctoral fellows in the application of data analysis and modelling techniques. The incumbent will have developed an independent method-based research portfolio, and will support and operationalize new and innovative computational techniques. Working with individual laboratories, the incumbent will help to develop research and project plans, advise on data analysis techniques and statistical inference related to neuroimaging and electrophysiological research, and assist in the technical and statistical aspects of manuscripts and research reports. Deadline for applications: September 27th Further particulars: https://www.academicacareers.com/node/7227 Please contact me if you have further questions, Jörn Diedrichsen Western Research Chair Brain Mind Institute Department of Computer Science Department of Statistics Email: jdiedric(a)uwo.ca<mailto:jdiedric@uwo.ca> Tel: 1-519-661-2111 x86994

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Research associate position in matlab programming
by Tania Rinaldi Barkat Aug. 14, 2017

Aug. 14, 2017

Our lab, hosted by the Department of Biomedicine of Basel University, Switzerland, is currently seeking a research associate for a 6-month project. The role would be to write an analysis program in matlab for neuronal data from electrophysiological recordings, as well as analyze the data. JOB DESCRIPTION The first part of the project consists of writing an extension of a professional, user-friendly matlab program for the analysis of electrophysiological data based on an existing program we already have in the lab. The successful candidate will interact with experimentalists in our lab, understand their needs and produce a modular and user-friendly matlab program for extracellular neuronal recordings. The second part of the project consists of using this program to analyze data aimed at deepening our understanding of the brain. Start date is as soon as possible. The period of employment is 6 months, with possibility of extension. YOU ARE OUR NEW RESEARCH ASSOCIATE IF YOU: - Have extensive programming experience in matlab - Have previously worked with neuroscience data, ideally electrophysiological recordings - Have the dual ability of analyzing researchers’ need and translating it into code - Are a creative problem-solver - Are a self-starter and an independent researcher ABOUT THE LAB www.brainsoundlab.com The aim of our lab is to understand the role of specific neural circuits in making sense of sounds. We combine optogenetics, in vivo electrophysiology, voltage-sensitive dye imaging and behavioral assays to explore the functions of neuronal circuits in the mouse auditory cortex. To apply, please send your CV and a cover letter briefly summarizing your research interests to Tania Barkat (tania.barkat(a)unibas.ch) --------------------------- Tania Rinaldi Barkat Assistant Professor in Neurophysiology Basel University Department of Biomedicine, room 7001 Klingelbergstrasse 50-70 4056 Basel Switzerland +41 61 207 1638 www.brainsoundlab.com

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International Brain Laboratory Staff Positions Ads
by Zachary Mainen Aug. 11, 2017

Aug. 11, 2017

Dear all, Please see below 5 available positions for staff with the International Brain Lab. Dissemination through your contacts would be much appreciated. Best, Zach Mainen --- The International Brain Laboratory (https://www.internationalbrainlab.com/) is seeking 5 collaborators who will play key roles in a new large-scale international collaboration in brain research. The IBL combines the efforts of approximately 50 scientists in 20 laboratories toward understanding the brain-wide basis of a complex behavior. The project will involve recording the activity of millions of neurons in the working brain and building mathematical models of the resulting data. The data sets this project will produce are vast and complex, including physiological recordings, behavioural measurements, and video, all of which must be standardized into common formats, integrated into a single database, and subjected to quality control. These core positions will support the both experimental and theoretical work through the entire lifecycle of data, including acquisition, analysis, modeling and dissemination. Project Manager (PM) - The primary responsibilities of the PM will include ensuring delivery of key milestones, managing overall project budget and finances, facilitating project governance and internal communication, and liaising with funders, external agencies and partners. Candidates should have demonstrated success in project management of a comparable scale and a strong background in scientific research. Technical Manager (TM) - The TM will be responsible for ensuring reproducibility of experiments across labs by (1) helping to establish and maintain a common set of experimental apparatus for behavior and neural recordings and (2) establishing procedures for standardizing, monitoring and troubleshooting experimental conditions, including animal subjects, surgical procedures, materials, etc. The position will involve extensive travel between ten experimental laboratories at six institutions across the U.S. and Europe. The ideal candidate would have a PhD in neuroscience and very strong technical and experimental skills. Strong organizational and interpersonal skills are required. Prior experience in laboratory or project management is desirable. Data Coordinator (DC) - The DC will work closely with our contributing labs and scientific programming staff to ensure the integrity and organization of data collected by experimental labs. The ideal candidate would have a PhD in neuroscience, and extensive experience with large neurophysiological and behavioral datasets. Attention to detail and ability to work collaboratively are both essential. Strong computing ability is also important, including knowledge of relational databases, Python and MATLAB. Scientific MATLAB Programmer (SMP) - The SP will contribute to the design of applications and pipelines for organization, storage and analysis of this data. The job will involve building software and data infrastructure for this collaborative research project, and supporting it. The ideal candidate will have extensive experience with MATLAB and previous work with big data in scientific research. Knowledge of Python and relational databases and experience interfacing with experimental control hardware is desirable. Senior Scientific Programmer (SSP) - The SSP will lead the design of applications and pipelines for organization, storage and analysis of this data. The job will involve building software and data infrastructure, as well as a role in ensuring data integrity, working closely with data providers to ensure it meets project standards. The ideal candidate will have extensive experience with relational databases and Python. Experience with MATLAB, previous work with big data in scientific research, and experience interfacing with experimental control hardware would also be desirable. Remuneration will be competitive and commensurate with experience. There is considerable flexibility in base location within the U.S. and Europe. To apply, please send cover letter and CV to info(a)internationalbrainlab.com with subject: PositionAcronym LastName. Review of applications will begin immediately and continue until the position is filled, with an ideal start date of Sept.-Oct., 2017. --- Zachary F. Mainen, Ph.D. Champalimaud Neuroscience Programme Champalimaud Centre for the Unknown Av. Brasília s/n 1400-038 Lisbon Portugal +351 210 480 100 zmainen(a)neuro.fchampalimaud.org <zmainen(a)fchampalimaud.org> www.neuro.fchampalimaud.org/group/mainen @zmainen

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Postdoc Position in Retina Research / Computational Neuroscience
by Gollisch, Tim Aug. 11, 2017

Aug. 11, 2017

A postdoc position is available in the lab of Tim Gollisch at the University Medical Center Göttingen, Germany. The group studies information processing and neural coding in the neural network of the vertebrate retina, using a combination of electrophysiological and computational approaches. Experimental methods include extracellular multielectrode-array recordings and intracellular recordings from neurons in the isolated retina (mouse and salamander), using both wild-type retinas and optogenetic retina models of vision restoration therapy. A strong focus of the group is to combine these experiments with novel tools for data analysis and mathematical modeling. Our research group if part of the strong and lively neuroscience research community of Göttingen, including the university, several Max Planck Institutes, the German Primate Center, and the European Neuroscience Institute. We are also part of the Bernstein Center for Computational Neuroscience Göttingen and of the Collaborative Research Center "Cellular Mechanisms of Sensory Processing" (http://sfb889.uni-goettingen.de/) For more information about the research group, please visit the group's website: http://www.retina.uni-goettingen.de/. We are looking for a highly motivated scientist with a good background in electrophysiology or computational/theoretical neuroscience. Experience in both of these areas is a bonus, but not required. Experience in computer programming or in scripting of data analysis routines is also a plus. The position is for 2 years initially with the possibility for renewal. Please send your application to Tim Gollisch (tim.gollisch(a)med.uni-goettingen.de<mailto:tim.gollisch@med.uni-goettingen.de>), including a CV, a statement of what interests you about the group's work, and contact details for two references. The University Medical Center Göttingen is an equal opportunities employer, and women are especially encouraged to apply. Applicants with disabilities and equal qualifications will be given preferential treatment. -- Prof. Dr. Tim Gollisch University Medical Center Goettingen, Dept. of Ophthalmology Waldweg 33, 37073 Goettingen Tel. +49 (0)551 39-13542 tim.gollisch(a)med.uni-goettingen.de<mailto:tim.gollisch@med.uni-goettingen.de> www.retina.uni-goettingen.de<http://www.retina.uni-goettingen.de>

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[INNS-BDDL 2018] Call for Papers
by Teng Teck Hou Aug. 11, 2017

Aug. 11, 2017

[Apologies for cross-postings] ########################################################### CALL FOR PAPERS The 3rd INNS Conference on Big Data and Deep Learning 2018 April 17-19, 2018, Sanur - Bali, Indonesia Homepage: http://www.innsbigdata2018.org #######################Description:###################### The International Neural Network Society (INNS) is the premiere organization for individuals interested in a theoretical and computational understanding of the brain and applying that knowledge to develop new and more effective forms of machine intelligence. INNS was formed in 1987 by the leading scientists in the neural network field. Researchers and colleagues who work in the area of big data and machine learning, we are happy to announce "The 3 rd INNS Conference on Big Data and Deep Learning 2018 (INNS BDDL 2018) will be held on April 18 19, 2018 in Sanur Bali, Indonesia. The aim of this conference is to create a valuable and important forum for scientists and engineers throughout the world to present the latest research findings and idea at the forefront of Big Data and Deep Learning. Accepted papers will be published by Elsevier, Scopus indexed. Several papers will be selected for possible publication in top journals. The conference will feature a comprehensive technical program with technical tracks on: Track 1: Big Data Track 2: Big Data Algorithms Track 3: Deep Learning Track 4: Application Areas Important Dates ################################################################### * Tutorial and workshop proposals (Submission) 15 September 2017 * Tutorial and workshop proposals (Decision) 30 September 2017 * Paper submission 2 November 2017 * Decision notification 31 December 2017 * Conference 17 - 19 April 2018 ################################################################### Previous INNS Conference: INNS 2016 in Thessaloniki, Greece INNS 2015 in San Francisco, USA #################### Organizing committees ############### General chairs Seiichi Ozawa, Kobe University, Japan Ah-Hwee Tan, Nanyang Technological University, Singapore Program Chairs Plamen P. Angelov, Lancaster University, UK Asim Roy, Arizona State University, USA Mahardhika Pratama, Nanyang Technological University, Singapore Local Committee Chairs Dieky Adzkiya, Institut Teknologi Sepuluh Nopember, Indonesia Advisory Board Yew-Soon Ong, Nanyang Technological University, Singapore Robert Kozma, University of Memphis, USA Sankar K. Pal, Indian Statistical Institute, India Haibo He, University of Rhode Island, USA Witold Pedrycz, University of Alberta, Alberta, Canada Leszek Rutkowski, Czestochowa University of Technology, Poland Nikola Kasabov, Auckland University of Technology, New Zealand Fernando Gomide, University of Campinas, Brazil Marley Vellasco, Pontifícia Universidade Católica do Rio de Janeiro, Brazil Yoonsuck Choe, Texas A&M University Minho Lee, Kyungpook National University, South Korea Bao-Liang Lu, Shanghai Jiao Tong University, China Irwin King, the Chinese University of Hong Kong, Hong kong Mohammad Nuh, Institut Teknologi Sepuluh Nopember, Indonesia Joni Hermana, Institut Teknologi Sepuluh Nopember, Indonesia Heru Setyawan, Institut Teknologi Sepuluh Nopember, Indonesia Tutorials/Workshop Chairs Igor Skrjanc, University of Ljubljana, Slovenia Sundaram Suresh, Nanyang Technological University, Singapore Poster Sessions Chairs Eko Setiadji, Institut Teknologi Sepuluh Nopember, Indonesia Agus Salim, La Trobe University, Australia Special Sessions Chairs Justin Wang, La Trobe University, Australia Yongping Pan, National University of Singapore, Singapore Panel Chairs Sreenatha Anavatti, University of New South Wales, Australia Mukesh Prasad, University of Technology, Sydney, Australia Achmad Affandi, Institut Teknologi Sepuluh Nopember, Indonesia Awards Chairs Tapabrata Ray, University of New South Wales, Australia Dejan Dovzan, University of Ljubljana, Slovenia Richard J. Oentaryo, McLaren Applied Technologies, Singapore Publication Chairs Edwin Lughofer, Johannes Kepler University, Austria Jose Antonio Iglesias, Carlos III University of Madrid, Spain Moamar Sayed?Mouchaweh, Institute Mines Telecom Lille Douai, France Publicity Chair Simone Scardapane, Sapienza University, Italy Teng Teck Hou, Singapore Management University, Singapore Hendro Nurhadi, Institut Teknologi Sepuluh Nopember, Indonesia International Liaison Chairs Yun Sing Koh, University of Auckland, New Zealand Deepak Puthal, University of Technology Sydney, Australia Wirawan, Institut Teknologi Sepuluh Nopember, Indonesia Webmaster Mohamad Abdul Hady, Institut Teknologi Sepuluh Nopember, Indonesia Andri Ashfahani, Institut Teknologi Sepuluh Nopember, Indonesia Choiru Zain, La Trobe University, Australia ###### Topics and Areas include, but not limited to the following###### >>BIG DATA Autonomous, online, incremental learning in big data High dimensional data, feature selection, feature transformation for big data Scalable algorithms for big data Big data analytics Data stream analytics Parallel & distributed computing for big data analytics (cloud, map-reduce, etc.) Online learning Online multimedia/stream/text analytics Link and graph mining Big data and cloud computing, large scale stream processing on the cloud Big data and collective intelligence/collaborative learning Big data and hybrid systems Big data and self-aware systems Big data and infrastructure Big data visualization >>Big Data Algorithm Neuromorphic hardware for scalable machine learning Evolving systems for big data analytics Evolutionary systems and big data Fuzzy systems and big data Cognitive modelling and big data Probabilistic approach for big data Concept drift detection for big data Granular computing for big data Transfer learning for big data >>Deep Learning Deep belief network Convolutional neural network Long short term memory Deep network architecture Deep autoencoder Deep stacked network Deep learning for natural language processing Deep learning for machine vision Evolving deep network Transfer learning in deep learning Online deep learning >>Application Areas Banking and Securities Communications, Media and Entertainment Healthcare Providers Education Manufacturing & Natural Resources Government Insurances Retail & Wholesale Trade Transportation Energy & Utilities, Etc. ##########################Sponsoring Organizations########################## * INNS - International Neural Network Society * MTC - Mechatronic Technology Center, Institut Tecknologi Sepuluh Nopember ############################################################################

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Bernstein 2017 Workshop: "Multiscale modeling and simulation"
by Salvador Dura Aug. 10, 2017

Aug. 10, 2017

Dear All, We would like to bring your attention to the "Multiscale modeling and simulation" workshop at the Bernstein Conference 2017, Sept 12-13, Göttingen, Germany. Website: http://www.nncn.de/en/bernstein-conference/2017/satellite-workshops/multisc… Short abstract: Understanding brain function requires characterizing the interactions occurring across many temporal and spatial scales. Mechanistic multiscale modeling aims to organize and explore these interactions across these scales. Multiscale models can provide insights into how changes at the molecular and cellular levels affect dynamics at local networks and brain areas. At the highest levels, they allow us to connect neural activity to theories of behavior, memory and cognition. The recent introduction of large neuroscience projects in US and EU Brain Research through Advancing Innovative Neurotechnologies (BRAIN) and Human Brain Project (HBP) respectively provide an opportunity to rapidly gather new and more accurate data to incorporate into the multiscale models. This workshop will present some of the latest multiscale modeling tools and approaches in neuroscience, as well as representative examples of datadriven multiscale neural simulations. The workshop aims to encourage both computational and experimental neuroscientists to make use of multiscale modeling in their research. Organizers: Salvador Dura-Bernal and Bill Lytton (SUNY Downstate) Speakers: Tue, Sept 12: - Bill Lytton (SUNY Downstate) - Jean Pierre Changeux (Pasteur Institute) - Volker Steuber (University of Hertfordshire) - Robert McDougal (Yale University) - Salvador Dura-Bernal (SUNY Downstate) - Cliff C Kerr (University of Sydney) Wed, Sept 13: - Szabolcs Kali (Hungarian Academy of Science/HBP) - Marianne Bezaire (Boston University) - Daniel Durstewitz (ZI Mannheim) - Kael Dali (Allen Institute for Brain Science) We look forward to seeing you there! Best Salva -- Salvador Durá-Bernal, Ph.D. Research Assistant Professor State University of New York Downstate Medical Center

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postdoc position
by Jean Daunizeau Aug. 4, 2017

Aug. 4, 2017

Dear all, Please find below the description of an open postdoc position. Do not hesitate to contact me should you require additional information. Best, Jean. **** Postdoctoral position in computational cognitive neuroscience **** This position is available at the Brain and Spine Institute (Paris, France) <http://icm-institute.org/en/>, in the Motivation, Brain & Behaviour team <https://sites.google.com/site/motivationbrainbehavior/>, under the direction of Dr. Jean Daunizeau. The position will follow standard French salaries at INSERM. Expected starting date: Fall 2017. *Computational cognitive neuroscience* uses mathematical modelling as a tool to understanding how mental processes (e.g., perception, memory, attention, emotion, etc...) are controlled by brain circuits. Its breadth typically ranges from biological models of neural network activity to cognitive models of brain information processing, to machine learning approaches to neuroscience data. In line with this approach, the Motivation, Brain & Behaviour group addresses the issue of identifying the* neural bases of motivation in health and disease* with a strong multi-disciplinary focus. The successful candidate will team with students with very diverse academic backgrounds (from neurology, psychiatry, biology and psychology, to philosophy, to economics and mathematics). S/he will be expected to contribute to all aspects of the research, including computational modelling, as well as data collection and analysis. A non-exhaustive list of possible projects is provided here: https://sites.google.com/site/jeandaunizeauswebsite/students. Required skills: - *[Mandatory]* Ph.D. either in Cognitive Neuroscience or in Engineering (or related fields) - *[Mandatory]* Autonomy in programming in MATLAB, Python or C - *[Desired]* Experience in computational models of neural and/or cognitive processes - Fluency and solid writing skills in English are expected. French is not a requirement. Please apply to jean.daunizeau(a)gmail.com with a recent CV, a brief (1 page) summary of your previous research and a letter of motivation. -- Jean Daunizeau Motivation, Brain and Behaviour group (ICM) web: http://sites.google.com/site/jeandaunizeauswebsite/

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AoN Brainhack Warsaw 2017 - call for project proposals
by Natalia Bielczyk Aug. 4, 2017

Aug. 4, 2017

AoN Brainhack Warsaw 2017 November 18-19, 2017 University of Warsaw, Warsaw, Poland *— The call for proposals extended to 1st September 2017 — * On the weekend of 18-19th November 2017, the first edition of *AoN Brainhack* *Warsaw* will take place. During this two-day event dedicated to students and PhD students, we will work in teams on neuroscience-related projects. The aim of the event is to meet new, enthusiastic researchers, make new friendships in academia, learn, share the knowledge on data mining and brain research, but also promote open science in the spirit of the whole Brainhack community (Craddock et al., 2016). The venue and the exemplary projects are presented on our website: *https://brainhackwarsaw.github.io/ <https://brainhackwarsaw.github.io/>* Please note this Brainhack is a satellite event for the interdisciplinary Aspects of Neuroscience conference which will take place on 24-26th November 2017 in Warsaw. Participation in the conference is not mandatory but we encourage to also consider this. Important deadlines: Deadline for project proposals: September 1st, 2017 Announcement of projects: September 15th, 2017 Participant registration starts: September 1st, 2017 Deadline for participant registration: November 1st, 2017 At the moment, the *call for project proposals* is open. The proposals can include various forms of a group activity, e.g., data analysis, app development, a two-day discussion club, developing a new software etc. The organizers will provide a few openly available datasets to the project authors, but developing projects using private datasets is also welcome. *Please send the project proposals and all the related questions to the mailing address: **brainhackwarsaw(a)gmail.com <brainhackwarsaw(a)gmail.com>* Also, please team up with us! Join our channel #brainhack-warsaw-2017 on Brainhack Slack project (https://brainhack-slack-invite.herokuapp.com) for the updates, and share your own ideas with us! We are looking forward to working with you at the AoN Brainhack Warsaw! *The AoN Brainhack Warsaw 2017 team:* Natalia Bielczyk, MSc, Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands (natalia.bielczyk(a)gmail.com) Krzysztof Bielski, MSc, Faculty of Psychology, University of Warsaw, Warsaw, Poland Michał Bola, PhD, Laboratory of Brain Imaging, Nencki Institute of Experimental Biology, Warsaw, Poland Daniel Borek, MSc, Faculty of Physics, University of Warsaw, Warsaw, Poland, (dtborek@g <norbert.kopco(a)upjs.sk>mail.com) Beata Goźlińska, BSc, Faculty of Physics, University of Warsaw, Warsaw, Poland

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Post-doc positions in analyses of electron microscopic images from the brain (Kyoto U, Japan)
by Hidetoshi Urakubo Aug. 4, 2017

Aug. 4, 2017

Dear members of Comp-neuro mailing list, Integrated Systems Biology Lab at Kyoto University invites applications for research position for analyses of three-dimensional microscopic images and/or functional magnetic images (fMRI, for example) from the animal/human brain, with a strong motivation into systems/computational neuroscience. We look forward to your applications and recommendations. The full advertisement is available below. On behalf of Prof. Shin Ishii Hidetoshi Urakubo ============================================== Shin Ishii Laboratory, Department of Systems Science, Graduate School of Informatics, Kyoto University Yoshida-Honmachi 36-1, Sakyo-ku, Kyoto 606-8501 Japan Phone: +81-75-753-4908 Fax: +81-75-753-4907 Email: urakubo-h(a)sys.i.kyoto-u.ac.jp ============================================== [[[ Post-doc positions in analyses of electron microscopic images from the brain ]]] We are seeking a highly motivated post-doc researcher, with a background in 3d/bio image processing and/or computational neuroscience. We are conducting research projects, “Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS; up to 2019/3/31; http://brainminds.jp/en/ ; Phil. Trans. R. Soc. B 370: 20140310),” and “Brain Information Dynamics underlying Multi-area Interconnectivity and Parallel Processing (Grant-in-Aid for Scientific Research on Innovative Areas, MEXT, Japan; up to 2022/3/31).” Those projects aim to map the structure and function of neuronal circuits to understand the vast complexity of the human/marmoset/rodent brains. The candidate will work on the projects on 3D reconstitution of marmoset brain atlas from 3D microscopic images (from EM and/or Optical) under collaboration with experiment teams. For this position, a PhD or a MD degree, a proven track record of peer-reviewed publications, and solid communication skills in English and/or Japanese are essential. All projects are done with our tenure track and post-doc researchers of various backgrounds including systems biology, bioinformatics, computational biology, mathematical engineering, and machine learning. Our laboratory also has a strong collaboration with other laboratories in Advanced Telecommunications Research Institute International (ATR) and RIKEN Brain Science Institute. [Job title and Job description] Title is a Full-time Researcher / Full-time Research Engineer The position is open after October 1st 2016 (negotiable) Work location is Yoshidahonmachi 36-1, Sakyo-ku, Kyoto-city, Japan. 606-8501 The contract is annually renewable up to the end of those projects based on the evaluation. Salary will be commensurate with qualifications and experience. Social insurance will be applied. Days off include weekends, public holidays, Year-end and New Year holidays, Foundation Day, and summer vacation. These and other provisions are in accordance with Kyoto U regulations (Kyoto University’s regulations). [Application and required documents] Please send the following five materials to the address below, either in printed or electronic form: 1. Complete CV 2. List of publications 3. Reprints of 1 to 3 major publications 4. Document (one or two pages in A4 or letter size) describing: - Summary of your previous research - Interests and proposal for research 5. Two letters of recommendation (including one from the current supervisor, if available) [Selection process] Selection will be made based on application screening and interviews. [Requirements] Applicants must: - have a Ph.D. (or be near completion). - have strong motivations and ambitions to participate in the research above. [Number of openings] One or two [Deadline for application] Nov 1st (will remain open if positions are not filled) [Send application to] Shin Ishii Integrated Systems Biology Laboratory, Graduate School of Informatics, Kyoto University Yoshida-honmachi, Sakyo, Kyoto 606-8501, Japan Email: Shin Ishii <ishii-secr [at] sys.i.kyoto-u.ac.jp> http://ishiilab.jp/kyoto/en/

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