- Comp-neuro - lists.cnsorg.org

Faculty jobs in brain stimulation at Stanford University
by Wei Wu March 26, 2018

March 26, 2018

To whom it may concern, I wanted to share a link to this job posting for those who are interested: http://med.stanford.edu/content/dam/sm/psychiatry/documents/ about_us/FacultyJobs/BrainStimulation.pdf

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11ᵗʰ Advanced Scientific Programming in Python in Camerino, Italy, 3—8 September, 2018
by Jakob Jordan March 25, 2018

March 25, 2018

11ᵗʰ Advanced Scientific Programming in Python ============================================== a Summer School by the G-Node and the University of Camerino https://python.g-node.org Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are devised to be interactive and to give the students enough time to acquire direct hands-on experience with the materials. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game. We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. We show how clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization are driving Python to become a standard tool for the programming scientist. This school is targeted at Master or PhD students and Post-docs from all areas of science. Competence in Python or in another language such as Java, C/C++, MATLAB, or Mathematica is absolutely required. Basic knowledge of Python and of a version control system such as git, subversion, mercurial, or bazaar is assumed. Participants without any prior experience with Python and/or git should work through the proposed introductory material before the course. We are striving hard to get a pool of students which is international and gender-balanced: see how far we got in previous years <https://python.g-node.org/wiki/archives#stats>! Date & Location =============== 3–8 September, 2018. Camerino, Italy. Application =========== You can apply online: https://python.g-node.org/wiki/applications Application deadline: 23:59 UTC, 31 May, 2018. There will be no deadline extension, so be sure to apply on time. Be sure to read the FAQ before applying: https://python.g-node.org/wiki/faq Participation is for free, i.e. no fee is charged! Participants however should take care of travel, living, and accommodation expenses by themselves. Program ======= • Version control with git and how to contribute to open source projects with GitHub • Best practices in data visualization • Organizing, documenting, and distributing scientific code • Testing scientific code • Profiling scientific code • Advanced NumPy • Advanced scientific Python: decorators, context managers, generators, and elements of object oriented programming • Writing parallel applications in Python • Speeding up scientific code with Cython and numba • Memory-bound computations and the memory hierarchy • Programming in teams Also see the detailed day-by-day schedule: https://python.g-node.org/wiki/schedule Faculty ======= • Ashwin Trikuta Srinath, Cyberinfrastructure Technology Integration, Clemson University, SC USA • Jenni Rinker, Department of Wind Energy, Technical University of Denmark, Roskilde Denmark • Juan Nunez-Iglesias, Melbourne Bioinformatics, University of Melbourne Australia • Nicolas P. Rougier, Inria Bordeaux Sud-Ouest, Institute of Neurodegenerative Disease, University of Bordeaux France • Pietro Berkes, NAGRA Kudelski, Lausanne Switzerland • Rike-Benjamin Schuppner, Institute for Theoretical Biology, Humboldt-Universität zu Berlin Germany • Tiziano Zito, freelance consultant, Berlin Germany • Zbigniew Jędrzejewski-Szmek, Red Hat Inc., Warsaw Poland Organizers ========== For the German Neuroinformatics Node of the INCF (G-Node) Germany: • Tiziano Zito, freelance consultant, Berlin Germany • Caterina Buizza, Personal Robotics Lab, Imperial College London UK • Zbigniew Jędrzejewski-Szmek, Red Hat Inc., Warsaw Poland • Jakob Jordan, Department of Physiology, University of Bern, Switzerland Switzerland For the University of Camerino Italy: • Flavio Corradini, Computer Science Division, School of Science and Technology, University of Camerino Italy • Barbara Re, Computer Science Division, School of Science and Technology, University of Camerino Italy Website: https://python.g-node.org Contact: python-info(a)g-node.org -- Jakob Jordan Institute of Neuroscience and Medicine (INM-6) Computational and Systems Neuroscience & Institute for Advanced Simulation (IAS-6) Theoretical Neuroscience Jülich Research Centre and JARA Jülich, Germany tel.: +49 2461 61-96450 http://www.csn.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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PhD Position in Computational Neuroscience
by Obermayer, Klaus, Prof. Dr. March 25, 2018

March 25, 2018

PhD Position in Computational Neuroscience & Machine Learning Neural Information Processing Group, Fakultät IV, Technische Universität Berlin and Bernstein Center for Computational Neuroscience, Berlin, Germany Salary grade E13 (TV-L Berliner Hochschulen) Duration: max. 5 years Starting date: October 1st, 2018 Working field: The successful candidate is expected to join collaborative research projects at the interface of computational neuroscience and machine learning. The position is also affiliated with the Bernstein Center for Computational Neuroscience Berlin (https://www.bccn-berlin.de/) and the candidate is welcome to participate in its scientific and training activities. Teaching responsibilities include the supervision of two tutorials per week during the semester associated with the courses taught by the Neural Information Processing Group. For more information about our current research projects see: http://www.ni.tu-berlin.de/. Requirements: Successfully completed university degree (Master, Diplom or equivalent) in Computational Neuroscience, Computer Science or another MINT subject; very good knowledge of machine learning and Computational Neuroscience; experience in teaching (supervision of tutorials) is desirable; very good German and English skills. How to apply: Please send your written application with the reference number (IV-158/18) and the usual documents to Technische Universität Berlin - Der Präsident - Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Neuronale Informationsverarbeitung, Prof. Dr. Obermayer, Sekr. MAR 5-6, Marchstr. 23, 10587 Berlin or - preferably - by e-mail to klaus.obermayer(a)tu-berlin.de. Closing date: April 20th, 2018 To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Please send copies only. Original documents will not be returned.

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Methods in Neuroscience at Dartmouth (MIND) 2018 Computational Summer School
by Matthijs van der Meer March 23, 2018

March 23, 2018

Methods in Neuroscience at Dartmouth (MIND) 2018 Computational Summer School https://summer-mind.github.io/ July 30th - August 7th, 2018 Application Deadline: April 29th, 2018 We are delighted to welcome applications for the second annual Methods in Neuroscience at Dartmouth (MIND) Computational Summer School. The theme of this year’s summer school is Narratives and Natural Contexts. There has been renewed interest in extending the study of neural and psychological phenomena in highly controlled laboratory settings to more naturalistic paradigms that more closely reflect the rich spatiotemporal structure of the real world. Bridging this divide requires developing new experiments and analytic methods. The goal of our summer school is to provide a forum for gaining hands-on experience with some of the latest computational tools that can help gain insight into understanding how our brains process naturalistic stimuli and contexts. We will offer a mix of expertise at a broad range of spatiotemporal scales and domains (e.g. behavioral, cognitive, social; circuit, whole-brain, and social networks; etc.). In addition, we will maintain our special focus on training students to use and contribute to open-source tools, data sharing, and other “best practices” for open science. For more information, and/or to apply, please visit our website, https://summer-mind.github.io/. Please note that this year’s application deadline is April 29, 2018. You may also find information about last year’s summer school (theme: multiscale network dynamics) along with all course materials here, https://summer-mind.github.io/2017.html. We anticipate a diverse and talented mix of graduate students, postdoctoral researchers, and junior faculty will participate in the summer school, and we hope to see you this summer in Hanover! Kind regards, Luke Chang, Jeremy Manning, and Matt van der Meer Directors Jim Haxby, Thalia Wheatley, and Dan Rockmore Advisory Committee This event is sponsored by the Center for Social Brain Sciences, Center for Cognitive Neuroscience, Dartmouth Research Computing, and Neukom Institute for Computational Sciences at Dartmouth.

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Job openings at Jülich Supercomputing Centre
by Jochen Martin Eppler March 23, 2018

March 23, 2018

Dear all, at the Jülich Supercomputing Centre at Forschungszentrum Jülich, Germany, we currently have two open positions in the context of the Human Brain Project: * Scientific programmer in computational neuroscience<http://www.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2018-061-EN…> * Senior scientific developer in computational neuroscience<http://www.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2018-062-EN…> For details about the institute and the positions, please follow the links. Best regards, Jochen! -- Dr. Jochen Martin Eppler Phone: +49(2461)61-96653 ---------------------------------- Simulation Laboratory Neuroscience Jülich Supercomputing Centre Institute for Advanced Simulation ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ 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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Brain Dynamics Toolbox for Matlab
by Stewart Heitmann March 23, 2018

March 23, 2018

Dear all, The Brain Dynamics Toolbox (http://www.bdtoolbox.org <http://www.bdtoolbox.org/>) is open-source software for simulating dynamical systems in neuroscience. It is for researchers and students who wish to explore mathematical models of brain function using Matlab. It includes a graphical tool for simulating dynamical systems in real-time as well as command-line tools for scripting large-scale simulations. Custom systems of differential equations can typically be defined in less than 100 lines of standard matlab code. The graphical interface is designed to be used as both a research tool and a teaching tool. Its hub-and-spoke architecture allows new combinations of numerical solvers and interactive plots (time plots, phase plots, bifurcation diagrams, space-time plots, etc) to be applied to any model with no additional programming effort. Version 2018a of the Brain Dynamics Toolbox has just been released and is available from http://www.bdtoolbox.org <http://www.bdtoolbox.org/> The Handbook for the Brain Dynamics Toolbox is available from https://www.amazon.com/dp/198057250X <https://www.amazon.com/dp/198057250X> The toolbox will be featured at the at the Australian Connectomics School (ACS-2018) in Melbourne, 30 May to 1 June 2018. Best Regards Stewart Heitmann & Michael Breakspear QIMR Berghofer Medical Research Institute Systems Neuroscience Group

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Now hiring: The Krembil Centre for Neuroinformatics, CAMH - Toronto, Canada
by Sean Hill March 22, 2018

March 22, 2018

The Krembil Centre for Neuroinformatics (www.krembilneuroinformatics.ca<http://www.krembilneuroinformatics.ca>) based at CAMH (www.camh.ca<http://www.camh.ca>), and fully affiliated with the University of Toronto, Canada, is hiring world-leading specialists to transform our understanding of mental health by organizing, integrating, analyzing, visualizing and modelling data across all levels of the brain —from genes to circuits to behaviour. This multimodal data is gathered across the clinical environment including genetic, epigenetic, MRI, DTI, fMRI, hd-EEG, actigraphy and electronic medical record data. Teams will employ state-of-the-art techniques including topological data analysis, machine learning and multiscale computational modeling to accelerate identification and treatment of mental health disorders. Research is performed in an open, team science environment, with an emphasis on reproducible data-driven research and a patient-centric approach. A focus on global collaboration is key to transforming our understanding of mental health and its treatment. The centre will operate as an incubator for medical technologies to identify, manage and treat mental illness, while shaping policy at national and global levels. The centre is expanding with the following openings (see http://krembilneuroinformatics.ca/apply for full details and to apply): *Independent Scientist for Computational Genomics The Independent Scientist for Computational Genomics will build and lead a team of talented bioinformatics researchers, computational biologists, and computer scientists who employ and develop state-of-the-art genetic, epigenetic and transcriptomic analyses and predictive models to provide new insights into mental health and brain disorders in a data driven way, making outcome predictors and identifying optimal intervention opportunities. *Independent Scientist for Brain Circuit Modelling The Independent Scientist for Brain Circuit Modelling will build and lead a team responsible for the development, simulation and analysis of dynamic and perturbable computational models of biophysically detailed brain circuitry (for both preclinical and human brains), integrating genetic, epigenetic and transcriptomic data, and ion channel, cellular and synaptic biophysics. The team will work in close collaboration with other groups involved in detailed biophysical modeling, e.g. the Blue Brain Project and Allen Institute for Brain Science. The team will also be responsible for curating and maintaining data, literature and models to enable data-driven modeling of brain circuitry in health and disease, in addition to the concurrent construction of atlases, development of analysis approaches and identification of biomarkers to define mental health and brain disorders in a data driven way, such as aberrant dynamical processes. *Independent Scientist for Whole Brain Modelling The Independent Scientist for Whole Brain Modelling will build and lead a team responsible for the development of dynamic and perturbable causal models of the human brain, in health and in the context of mental illness, incorporating multi-modal neuroimaging and expression data including, but not limited to, structural, functional, diffusion and spectrometry MRI, PET/CT and EEG. The team will also be responsible for the concurrent construction of atlases, development of analysis approaches and identification of biomarkers to define mental health and brain disorders in a data driven manner. *Independent Scientist for Whole Person Modelling The Independent Scientist for Whole Person Modeling will build and lead a team responsible for the development and application of predictive modeling approaches for individual citizen, patient and population trajectories and outcomes. This includes tools, pipelines and approaches for the exploration, visualization and analysis of complex high-dimensional data, with the aim of the data-driven definition of mental health and brain disorders, and the establishment of outcome predictors and identification of optimal intervention opportunities. *Independent Scientist for Brain and Health Knowledge Management The Independent Scientist for Brain and Health Knowledge Management will build and lead a team responsible for organizing and disseminating data, models and literature related to the definition and treatment of mental health disorders to support both researchers and clinicians. This team will maintain and curate ontologies of brain disorders and link to data, analyses, visualizations, literature and models supporting their definition. This clinical support platform will support reasoning and inference across definitions and datasets to bridge psychiatric and neurological disorders. *Knowledge Engineering Lead The Krembil Centre for Neuroinformatics is launching a knowledge engineering initiative to structure and map vast quantities of clinical and research data into a unified schema and develop a knowledge graph. This initiative will lay the technical foundation to support supervised and unsupervised content discovery, enable data mining, and facilitate interactive modes of engagement with our data corpus. A new Knowledge Engineering team is being established to spearhead the implementation of this initiative. This is a unique opportunity to partner with world-class researchers in the creation of unprecedented knowledge discovery tools. *Brain Imaging Data Engineer The Brain Imaging Data Engineer role will be accountable for managing and enhancing the solution for collecting, storing, curating and integrating brain imaging data sets across the organization, including, but not limited to the following modalities: MRI, PET and EEG. You will work closely with the senior architects on the technology team as well as collaborating with scientific leads. You will be accountable to evolve the technology solution to keep up with industry changes to ensure the solution remains optimal. *Molecular Data Engineer The Molecular Data Engineer role will be accountable for managing and enhancing the solution for collecting, storing, curating and integrating molecular data sets across the organization. You will work closely with the senior architects on the technology team as well as collaborating with scientific leads. You will be accountable to evolve the technology solution to keep up with industry changes to ensure the solution remains optimal. *Senior Project Manager – BrainHealth Databank The Senior Project Manager will work with multiple stakeholders both internal and external to CAMH and be responsible for the hands-on leadership and oversight for the development and execution of work plans, accountabilities, and timelines associated with the BrainHealth Databank initiative. The BrainHealth Databank platform will be specifically designed to support multidimensional phenotyping studies that combine digital phenotyping and laboratory-based data across existing and future clinical studies at CAMH. All data will be organized within the knowledge graph of the BrainHealth Databank. The platform will support configuration of studies that integrate common data elements and CRFs, wearable and mobile devices, voice samples, electronic medical record (EMR) extracts, outcome assessments and health care system usage. CONFIDENTIALITY NOTICE: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. AVIS DE CONFIDENTIALITÉ : Ce message électronique, ainsi que tout fichier qui y est joint, est reserve à l'usage exclusif du destinataire visé et peut contenir des renseignements confidentiels et privilégiés. Toute lecture, utilisation, divulgation ou distribution non autorisée est interdite. Si vous n'êtes pas le destinataire visé, veuillez en aviser l'expéditeur par retour de courriel et détruire toutes les copies du message original.

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CFP, Special session - Hybrid Life: Approaches to integrate biological, artificial and cognitive systems, ALife 2018
by Manuel Baltieri March 21, 2018

March 21, 2018

[Apologies for cross-posting] ********** Call for Papers ********** Special session - Hybrid Life: Approaches to integrate biological, artificial and cognitive systems https://sites.google.com/view/hybrid-life/ <https://sites.google.com/view/hybrid-life/> 2018 Artificial Life conference (ALife) Tokyo, JAPAN, 23-27 July 2018 - http://2018.alife.org/ <http://2018.alife.org/> --------------------------------------------------------------------------------------------- DESCRIPTION: The main focus of ALife research is the study of natural systems with the goal of understanding what life is. More concretely, ALife defines ways to investigate processes that contribute to the formation and proliferation of living organisms. In this session we focus on three common approaches to tackle this investigation, proposing ways to integrate, extend and possibly improve them. More specifically we refer to: 1) the formalisation of the necessary properties for the definition of life, 2) the implementation of artificial agents, and 3) the study of the relation between life and cognition. For this special session we propose to start from these well-established Alife methodologies, and extend them through: a unified formal language for the description and modelling of living, as well as artificial and cognitive systems, e.g. control theory, Bayesian inference, dynamical systems theory, etc., the exploration of biological creatures enhanced by artificial systems (or artificial systems augmented with organic parts) in order to investigate the boundaries between living and nonliving organisms, and the evaluation of coupled biological-artificial systems that could shed light on the importance of interactions among systems for the study of living and cognitive organisms. This special sessions aims to invite contributions from the fields of psychology, computational neuroscience, HCI, theoretical biology, artificial intelligence, robotics and cognitive science to discuss current research on the formalisation, combination and interaction of artificial/living/cognitive systems from theoretical, modelling and implementational perspectives. Potential topics include, but are not limited to: Formalisation of life and cognition (e.g. dynamical systems theory, stochastic optimal control, Bayesian inference, etc.) Cognitive robotics Autopoiesis Life-mind continuity thesis Systems biology Origins-of-life theories with relationships to artificial and cognitive systems Animal-robot interaction Bio-inspired robotics Bio-integrated robotics Human-machine interaction Augmented cognition Sensory substitution Interactive evolutionary computation Artificial perception Important Dates 19th March 2018 – Paper submission deadline 23rd April 2018 – Paper acceptance notification 21st May 2018 – Camera-ready version 23-27th July 2018 – Artificial Life conference (ALife), Tokyo, Japan Paper Submission Papers and abstracts submitted to this special sessions will be reviewed by a selected group of experts from the a-life community as well as from other areas key to our proposal, specifically chosen for this review process. If you are submitting to a special session you will be given the opportunity to select it during the submission process. Submissions to special sessions follow the same format, instructions and deadlines of regular ALife papers. Organizers Manuel Baltieri, University of Sussex, Brighton, UK. m.baltieri(a)sussex.ac.uk <mailto:m.baltieri@sussex.ac.uk> Keisuke Suzuki, University of Sussex, Brighton, UK. k.suzuki(a)sussex.ac.uk <mailto:filippo.m.bianchi@uit.no> Hiryuki IIzuka, Hokkaido University, Sapporo, Japan hiroyukiiizuka(a)gmail.com <mailto:hiroyukiiizuka@gmail.com> Contacts For questions, enquiries and more information please check our website https://sites.google.com/view/hybrid-life/ <https://sites.google.com/view/hybrid-life/> or get in touch with m.baltieri(a)sussex.ac.uk <mailto:m.baltieri@sussex.ac.uk>. All the best, -- Manuel Baltieri, EASy group Department of Informatics, University of Sussex, UK Twitter: @manuelbaltieri

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Abstract submission for Neuroinformatics 2018 in Montréal, Canada is open!
by congress March 21, 2018

March 21, 2018

Dear all, Abstract submission for Neuroinformatics 2018 in Montréal, Canada on August 9-10 is now open! The annual INCF Congress provides a meeting place for researchers in all fields related to neuroinformatics. Join us for keynotes from top neuroscientists, community sessions and poster- and demo sessions. Neuroinformatics 2018 will be a great opportunity to introduce new participants to the field of neuroinformatics and highlight new and innovative tools and approaches. Providing a forum for infrastructure providers and developers of tools, standards, and best practices to help define the capabilities of the global network, receive training on how to participate in the Open, FAIR and Citable global network and learn how to provide better services to their constituents. *Abstract submission deadline is April 30: **neuroinformatics2018.org/abstracts <http://neuroinformatics2018.org/abstracts>* Registration will open shortly. More information: *neuroinformatics2018.org <http://www.neuroinformatics2018.org>* Please spread this information to anyone you feel would be interested in attending. *The International Neuroinformatics Coordinating Facility (INCF) is an international non-profit organization devoted to advancing the field of neuroinformatics and global collaborative brain research. Learn more about INCF www.incf.org <http://www.incf.org/>* *We look forward to seeing you in Montréal!* Best Regards The INCF Secretariat <http://www.neuroinformatics2018.org> <http://www.neuroinformatics2018.org>

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DynaSim: A MATLAB/GNU Octave Toolbox for Neural Modeling and Simulation
by Jason Sherfey March 20, 2018

March 20, 2018

Dear Colleagues, We are happy to announce the release of DynaSim, an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It was designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments; it is the first, comprehensive neural modeling and simulation platform developed in MATLAB. It provides C compilation, optimized vector calculations, multi-core processing, and support for compute clusters to overcome the traditionally slow simulation speeds of MATLAB. It is also available for high performance computing via the Neuroscience Gateway web portal. A paper introducing DynaSim was recently published in Frontiers in Neuroinformatics: https://www.frontiersin.org/articles/10.3389/fninf.2018.00010/full. Documentation is available online at http://dynasimtoolbox.org. We hope this tool reduces barriers for investigating dynamics in neural models, facilitates collaborative modeling, and complements other tools being developed in the neuroinformatics community. Most of all, we hope you find this toolbox useful! Please direct questions to the lead developer, Jason Sherfey < sherfey(a)mit.edu> or the user mailing list: https://groups.google.com/forum/#!forum/dynasim-users. Best regards, Jason Dr. Jason Sherfey Postdoctoral Research Fellow Psychological & Brain Sciences, Boston University Massachusetts Institute of Technology The Picower Institute for Learning & Memory http://JasonSherfey.com

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