May 2018 - Comp-neuro - lists.cnsorg.org

Creating a list of important computational predictions
by Yiota Poirazi Jan. 4, 2021

Jan. 4, 2021

Dear all, I believe you would agree that, the greatest recognition of our computational work comes with the experimental verification of our computational predictions. To highlight the most important outcomes of our theoretical work and facilitate a closer interaction with experimental labs so as to increase the chances of our predictions being experimentally tested, I would like to encourage you to nominate your favorite prediction at the following google form: https://docs.google.com/forms/d/e/1FAIpQLSeJZ2RrXJ0nZonIuyNzN0Cl gXDKDb7xTzoJOiqZTGxm9Kh7ow/viewform?c=0&w=1&usp=mail_form_link This effort started during the CNS 2017 meeting in Antwerp with the support of the OCNS Board. The resulting list will be posted on the CNS 2017 web site and disseminated in social media, as a reference for experimentalists. Thank you very much for supporting this important effort! Best wishes, Yiota Poirazi -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/> -- This message has been scanned for viruses and dangerous content by *E.F.A. Project* <http://www.efa-project.org>, and is believed to be clean. Click here to report this message as spam. <http://mailgate1.imbb.forth.gr/cgi-bin/learn-msg.cgi?id=4BCD7A00A1.A57D7&to…> -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/>

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Postdoctoral positions in computational neuroscience and artificial intelligence
by Maxim Bazhenov March 1, 2019

March 1, 2019

Applications are invited for post-doctoral research positions in the laboratory of Dr. Maxim Bazhenov at the University of California, San Diego to study memory and learning and to develop neuroscience inspired computer algorithms capable of continual learning and adapting to the novel situations and contexts.This project involves close collaboration with the experimental laboratory of Dr. Bruce McNaughton (UC Irvine). The ultimate goal of the work is to advance the knowledge of how human and animal brains learn from experience and apply these principles to the artificial systems to enable continuous learning without catastrophic forgetting. The successful candidate will collaborate with a team of researchers to design neural network models of dynamic interactions between the hippocampus and neocortex during learning and memory consolidation in sleep and awake based on experimental data. These models will be used to derive learning principles that can be combined with advances in artificial intelligence and machine learning. An ideal candidate should have experience in computational/theoretical neuroscience and a basic knowledge of machine learning, or, alternatively, experience in machine learning algorithms and some basic knowledge of neuroscience. Experience with hierarchical learning, reinforcement learning, and/or goal-directed decision-making would be particularly helpful. The University of California offers excellent benefits. Salary is based on research experience. Applicants should send a brief statement of research interests, a CV and the names of three references to Maxim Bazhenov at mbazhenov(a)ucsd.edu -- Maxim Bazhenov, Ph.D. Professor, Department of Medicine, Neurosciences Graduate Program, UCSD, School of Medicine http://www.bazhlab.ucsd.edu/

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Columbia Workshop on Brain Circuits, Memory and Computation 2018
by Aurel A. Lazar Dec. 16, 2018

Dec. 16, 2018

Columbia Workshop on Brain Circuits, Memory and Computation 2018 <http://www.bionet.ee.columbia.edu/workshops/bcmc/2018> BCMC 2018 March 15-16, 2018 Center for Neural Engineering and Computation <http://cnec.columbia.edu/> Columbia University, New York, NY, USA Overview The goal of the workshop is to bring together researchers interested in developing executable models of neural computation/processing of the brain of model organisms. Of interest are models of computation that consist of elementary units of processing using brain circuits and memory elements. Elementary units of computation/processing include population encoding/decoding circuits with biophysically-grounded neuron models, non-linear dendritic processors for motion detection/direction selectivity, spike processing and pattern recognition neural circuits, movement control and decision-making circuits, etc. Memory units include models of spatio-temporal memory circuits, circuit models for memory access and storage, etc. A major aim of the workshop is to explore the integration of various sensory and control circuits in higher brain centers. A Fruit Fly Brain Hackathon <http://www.bionet.ee.columbia.edu/hackathons/ffbh/2018> is being conducted in conjunction with the workshop. Workshop participants are welcome to attend the hackathon. Registration Registration is free but all participants have to register <https://bcmc2018.eventbrite.com/>. Thank you! Organizer and Program Chair Aurel A. Lazar <http://www.ee.columbia.edu/~aurel>, Department of Electrical Engineering, Columbia University. Program Overview (Confirmed Speakers) Misha B. Ahrens <https://www.janelia.org/lab/ahrens-lab>, Janelia Research Campus, Ashburn, VA. Davi Bock <https://www.janelia.org/lab/bock-lab>, Janelia Research Campus, Ashburn, VA. Claude Desplan <https://wp.nyu.edu/desplanlab/>, Department of Biology, New York University. Mark A. Frye <http://www.fryelab.net/>, Department of Integrative Biology and Physiology, University of California, Los Angeles. C. Giovanni Galizia <http://neuro.uni-konstanz.de/03team/content/galizia.html>, Department of Biology, University of Konstanz. Maria N. Geffen <https://geffenlab.weebly.com/maria.html>, Department of Otorhinolaryngology and Department of Neuroscience, University of Pennsylvania. Hokto Kazama <http://kazama.brain.riken.jp/index.php>, Riken Brain Science Institute, Tokyo. Donggen Luo <http://mgv.pku.edu.cn/?co=posts&ac=faculty&catalog=enpiintro&pname=en_Dongg…>, McGovern Institute for Brain Research, Peking University, Beijing. Thomas Nowotny <http://www.sussex.ac.uk/profiles/206151>, Department of Informatics, University of Sussex. Pavan Ramdya <https://ramdya-lab.epfl.ch/home>, Brain Mind Institute, EPFL, Lausanne. Aravinthan D.T. Samuel <https://scholar.harvard.edu/aravisamuel/home>, Department of Physics and center for Brain Science, Harvard University. Simon G. Sprecher <http://www.sprecherlab.com/simon-sprecher/>, Department of Biology, University of Fribourg. Seth Tomchik <http://www.scripps.edu/tomchik/>, The Scripps Research Institute Florida. Joshua T. Vogelstein <http://jovo.me/>, Dept. of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University. Scott Waddell <https://www.dpag.ox.ac.uk/research/waddell-group>, Department of Physiology, Anatomy and Genetics, University of Oxford. Anthony M. Zador <http://zadorlab.cshl.edu/>, Cold Spring Harbor Laboratory. Aurel http://www.bionet.ee.columbia.edu

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CFP: FLAIRS 2017, Marco Island, FL,
by bisant＠umbc.edu Oct. 18, 2018

Oct. 18, 2018

CALL FOR PAPERS FLAIRS 2017, Florida Artificial Intelligence Research Symposium Special Tracks on Data mining and Special Track on Cyber Security Marco Island, Florida http://www.flairs-30.info/ Paper submission deadline: November 21, 2016. Notifications: January 23, 2017. Camera ready version due: February 27, 2017. FLAIRS is an interdisciplinary artificial intelligence conference which especially encourages novel ideas and which features a double-blind review process. Data Mining Track This special track will be devoted to data mining with the aim of presenting new and important contributions in this area. Papers and contributions are encouraged for any work related to Data Mining. Topics of interest may include (but are in no way limited to): 1. Applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy. 2. Modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches. 3. Feature extraction and selection. 4. Post-processing techniques such as visualization, summarization, or trending. 5. Preprocessing and data reduction. 6. Knowledge engineering or warehousing. Papers dealing with Cloud-based unstructured data or Cloud-based tool suites, such as Mahout or Apache Spark, are also encouraged. Cyber-Security Track Original high quality papers are sought for leading edge research and applications relating to the application of AI and Cyber Security. Topics of interest may include but are not limited to: · Machine Learning for Intrusion Detection Systems · NLP for text analysis in Cyber Security · Video and CCTV semantic analysis for terrorist or criminal action detection · AI & Biometrics, Internet of Things, and Cloud Computing security · AI & SCADA systems, Network Systems, and Embedded Systems security · Formal and theoretical approaches of intelligent security in WSNs · Legal and policy issues in intelligent security · Integrity, privacy, authentication and access control · Intelligent secure systems in multimedia databases · Social networks security · Intelligent incident response techniques in network and communication systems · Risk analysis and intelligent management · Virtual Private Networks intelligent security · Automated reasoning techniques of incidents and evidence analysis · Evidentiary aspects of digital forensics · Collaborative intelligent investigation · Intelligent systems in management, storage and reassembly · Steganography, watermarking, and forensic techniques in multimedia content processing · Lightweight security techniques · Intelligent Large-scale investigations and Big Data · Innovative non-repudiation techniques · Intelligent vulnerability analysis and assessment · Attacks tracking · Data hiding, tamper detection and recovery techniques · Security of e- healthcare systems and applications Note: We invite original papers (i.e. work not previously submitted, in submission, or to be submitted to another conference during the reviewing process). Submission Guidelines Interested authors should format their papers according to AAAI formatting guidelines. The papers should be original work (i.e., not submitted, in submission, or submitted to another conference while in review). Papers should not exceed 6 pages (or 4 pages for short paper, to be presented as a poster) and are due by November 21, 2016. For FLAIRS-30, the 2017 conference, the reviewing is a double blind process. Author names and affiliations should be Xd out on submitted papers to provide double-blind reviewing. Papers must be submitted as PDF through the EasyChair conference system, which can be accessed through the main conference web site (http://www.flairs-30.info/) Note: do not use a fake name for your EasyChair login - your EasyChair account information is hidden from reviewers. Authors should indicate which special track they are submitting to. The proceedings of FLAIRS will be published by the AAAI. Authors of accepted papers will be required to sign a form transferring copyright of their contribution to AAAI. FLAIRS requires that there be at least one full author registration per paper.

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Up to 8 PhD fellowships in Cognitive Neuroscience at SISSA, Trieste, Italy
by Alessandro Treves Aug. 16, 2018

Aug. 16, 2018

SISSA is an elite postgraduate research institution, focused on Maths, Physics and Neuroscience. It operates in English: many among its students and faculty are not Italian. Campus above Trieste, overlooking the Gulf. Research approaches in the CNS PhD https://phdcns.sissa.it/ span the range from cognitive psychology and imaging in humans to behavioural neuroscience and multiple single-unit recording in rats, mathematical and computational modeling; with research groups led by Domenica Bueti, Davide Crepaldi, Mathew Diamond, Chris Mathys, Raffaella Rumiati, Alessandro Treves and Davide Zoccolan. Allied approaches are pursued in other SISSA PhDs. All admitted students receive a 4-year fellowship and engage full-time in research based in Trieste, with limited coursework in the first few months, talks and seminars throughout the year and a TEX event in the summer, see https://indico.sissa.it/event/26/ First deadline for EU candidates: March 2, 2018, for nonEU: March 31, 2018 -- Alessandro Treves http://people.sissa.it/~ale/limbo.html SISSA - Cognitive Neuroscience, via Bonomea 265, 34136 Trieste, Italy +39-040-3787623 Ambassador (BlaBlaCar) +39-349-2504602

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Deadline extended to June 15th for abstracts for the 2nd International Youth Conference of Bionic Science and Engineering (IYCBE2018), 7th-9th November 2018, Odense, Denmark
by Jan-Matthias Braun May 31, 2018

May 31, 2018

The deadline for abstract submission has been extended to June 15th, 23:59:59 Coordinated Universal Time (UTC). The 2nd International Youth Conference of Bionic Engineering (IYCBE2018) will be held on 7th-9th November 2018 in Odense, Denmark. WEBPAGE: http://iycbe2018.sdu.dk/ ****Abstract Submission Instructions and Publication Details**** The abstract should fit into 500 words, the title into 500 characters. Up to one figure or table can also be added. *Direct links to updated templates and all details are available at the conference webpage.* Then, submit your abstract on our submission page until 15th June 2018. https://easychair.org/my/conference.cgi?welcome=1;a=13832989;conf=iycbe2018 All accepted abstracts with oral or poster presentation will be published in Frontiers in Neurorobotics as an e-book. Selected authors may additionally be invited to submit extended versions for a conference Special Issue of Frontiers in Neurorobotics and Journal of Bionic Engineering. ****Plenary Talks**** John Hallam, University of Southern Denmark, Denmark Title: From Lizards to LEGO, and back again? Zhendong Dai, Nanjing University of Aeronautics and Astronautics, China Title: Biomimetic on gecko locomotion: revealing the biology mechanism and developing robot for engineering. Han Zhiwu, Jilin University, China Title: Title: Fabrication and Performance of Bionic Strain Component ****Keynote speakers**** Thierry Darmanin, University of Nice-Sophia Antipolis, France Title: Tunable Conducting Polymer Nanotubes with Special Wetting Properties Zhiguang Guo, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, China Title: Bioinspired Separation Materials for Liquid Lubricants Alexander Spröwitz, Max Planck Institute for Intelligent Systems, Germany Title: Implementing and Testing Bioinspired Mechanisms on Robots to Understand Legged Locomotion Massimo Sartori, University of Twente, Netherlands Title: Neuro-Mechanical Modelling for Man-Machine Interaction Lars Heepe, Kiel University, Germany Title: Biological and Biomimetic Surfaces: Adhesion, Friction, and Applications Limei Tian, Jilin University, China Title: Non-bactericidal coating of bionic surfaces used for anti-biofouling ****Important Dates**** *Extended* Abstract Submission Deadline: 15th June 2018, 23:59:59 UTC – SUBMISSION IS OPEN Notification of Acceptance: 20th August 2018 Camera Ready Submission: 20th September 2018 Early Registration: 20th September 2018 Conference: 7th-9th November 2018 ****Scope of the Conference**** To meet the demand of the bionic scientists for academic communication, the 2nd International Youth Conference of Bionic Engineering (ICBSE2018) will be held on 7th-9th November 2018 in Odense, Denmark. This conference will be supported by the Youth Committee of International Society of Bionic Engineering (ISBE) and Frontiers in Neurorobotics and organized by University of Southern Denmark and Nanjing University of Aeronautics & Astronautics. The objective of this interdisciplinary conference is to provide an international forum for youth or outstanding scientists and engineers around the world who are interested in the field of bionic science and engineering. All aspects of bionic science and engineering and application areas are welcome, including, but not limited to, the following topics: Bio-inspired Robotics Bio-inspired Sensors and Actuators Bio-inspired Energy Storage Bio-inspired Flexible Electronics Bio-Inspired Solar Cells Biomimetic Engineering Embodied Artificial Intelligence and Neurorobotics Functional Morphology Musculoskeletal Systems, Biomechanics Biological Interface and Functionalization Biomimetic Materials, Biomimetic Structures Mechanics, Biomimetic Surfaces Biomimetic Design Methodologies Bionic Fluid, Biological Systems and Brain-Inspired Computing and Neuromorphic Systems. ****Awards**** The best abstract, as well as the best poster, will be awarded at the conference. ****Conference Format**** The conference will be single track with additional poster sessions. ORGANIZING COMMITTEE The Honorary Chair: Julian Vincent General Chair: Poramate Manoonpong Vice-General Chairs: Limei Tian, Zhiguang Guo Program Chair: Jørgen C. Larsen Local Arrangement Chair: Danish Shaikh Publication Chairs: Jan-Matthias Braun, Xiaofeng Xiong Registration Chair: Tórur Andreassen Media Operation Chair: Mathias Thor Technical Support: Peter Billeschou, Leon Bonde Larsen, David Docherty

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CfP: Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data at BI 2018, Arlington, Texas, USA.
by Mufti Mahmud May 31, 2018

May 31, 2018

*[Apologies for cross posting.]* *Call for Paper for Special Session on * *Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data* *11th Brain Informatics Conference (BI 2018), Arlington, Texas, USA, December 7-9, 2018* *Web: http://uta.engineering/conferences/bi-2018/ <http://uta.engineering/conferences/bi-2018/>* Organizers: *Mufti Mahmud1, M Shamim Kaiser2, Ning Zhong3, Nitish V Thakor4* *1* *Computing and Technology, Nottingham Trent University, NG11 8NS – Nottingham, UK* 2*Institute of Information Technology, Jahangirnagar University, Savar, 1342 – Dhaka, Bangladesh* 3*Dept. of Life Science and Informatics, Maebashi Institute of Technology, 371-0816 - Maebashi-City, Japan* *4**Singapore Institute for Neurotechnology, National University of Singapore, 117456 – Singapore; & * *Dept. of Biomedical Engineering, Johns Hopkins University, Baltimore, 21205 – MD, USA* *Introduction:* The brain receives and processes information simultaneously coming from diverse sources. The neurons, being the basic information processing units, interconnect to each other to form hierarchical and/or parallel pathways. Technologies related to neural systems engineering have been employed to study these pathways along with processing and modelling of neuronal data for disease diagnosis and brain decoding purposes. Combining both experimental and computational approaches in recent years, thanks to the advancements in neurotechniques, scientists can access large amount of neuronal data and apply computationally intelligent and nature-inspired machine learning techniques including deep learning and reinforcement learning on those data to suggest next generation experimental design aiming to decipher brain’s information processing capabilities and diagnose its diseases. *Scope:* Developing data-intensive and intelligent tools, as well as sophisticated neurotechniques, to process and analyse the neuronal big data is one of the biggest challenges posed to today’s multidisciplinary brain science community. To share recent progress in decoding neuronal information processing, both in healthy and diseased brain, this special session aims to provide a forum for scientists from diverse disciplines including – computer, electrical, biomedical, and neuro engineering – who are looking for more relevant information in interpreting brain functions and diagnosing diseases using expert and computationally intelligent systems. This special session expects to attract papers on recent research progress in the area of intelligent computational tools and techniques in acquiring and processing neuronal big data. The focus areas include, but not limited to, the following: Ø Neural systems engineering and technology to study neural pathways; Ø Processing and modelling of neuronal data for disease diagnosis and brain decoding; Ø Bio-inspired methods for network analysis and pattern recognition in neural data; Ø Novel machine learning techniques for neuronal big data analysis; Ø Application of deep and reinforcement learning to neuronal big data analysis; Ø Computationally intelligent techniques for neuroscience applications; Ø Neuroinformatics (including cloud computing and real-time systems); Ø Cognitive science applications (learning, workload, decision making, etc.) and data analytics; Ø Computational and imaging methods for human brain connectome; and Ø Information analysis in human brain machine interface (invasive, noninvasive). *Submission of papers:* Submit Springer Lecture Notes in Computer Science (LNCS) complaint – 10 page – pdf paper to the Special Session following the steps below: Ø Prepare the paper as per the Springer LNCS template from: http://www.springer.com/us/computer-science/lncs/conference-proceedings-gui… Ø Visit https://wi-lab.com/cyberchair/2018/bi18/scripts/ws_submit.php?subarea=S Ø Select the link: Special session on Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data Ø Select the link Submit a New Paper (TYPE I Submission) Ø Provide paper details (i.e., Author(s), Paper Title, Abstract, Keywords, PDF file to upload). *Important dates:* Ø Paper submission deadline: *30 July 2018* Ø Decision notification: *30 August 2018* Ø Special Session date: *7 December 2018* Ø Conference dates: *8-9 December 2018*. -- *Mufti Mahmud, PhD* | (Senior) Lecturer of Computing & Technology <https://www.ntu.ac.uk/sat/about/academic_teams/comp_tech.html> | School of Science & Technology <https://www.ntu.ac.uk/sat/> Office: ERD200 | Nottingham Trent University <https://www.ntu.ac.uk/> | Clifton Campus | NG11 8NS – Nottingham, UK Phone: +44 (0)115 84 83202 | Email: mufti.mahmud(a)ntu.ac.uk Meeting requests: https://doodle.com/mufti http://orcid.org/0000-0002-2037-8348 https://sites.google.com/site/muftimahmud/ https://scholar.google.com/citations?user=L8em2YoAAAAJ&hl=en Senior Member, IEEE <https://www.ieee.org/> & ACM <https://www.acm.org/> Associate Editor, IEEE Access <http://ieeeaccess.ieee.org/> Editorial Board Member, Cognitive Computation <https://www.springer.com/biomed/neuroscience/journal/12559> & Big Data Analytics <https://bdataanalytics.biomedcentral.com/>

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New book: Neural Information Theory
by James V Stone May 31, 2018

May 31, 2018

I'd like to announce the publication of this book: Principles of Neural Information Theory: Computational Neuroscience and Metabolic Efficiency by James V Stone. Reviews, synopsis, and table of contents can be found here: http://sebtelpress.com regards, James V Stone, University of Sheffield, UK.

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[High Performance Computing] Become a specialist!
by Master in HPC May 31, 2018

May 31, 2018

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PhD studentship in Biocomputation Research Group, Centre for Computer Science and Informatics Research, University of Hertfordshire
by Shabnam Kadir May 30, 2018

May 30, 2018

Applications are invited for a *PhD studentship* on *Computational frameworks for high-dimensional neural data* with *Dr. Shabnam Kadir *in the *Biocomputation Research Group* in the Centre for Computer Science and Informatics Research, University of Hertfordshire, U.K. *Project Description* New developments in experimental technology have led to petabytes of raw data being produced by experimental neuroscientists, which are increasingly publicly available, e.g. Allen Institute data http://www.brain-map.org/. In particular, we are in the realm where population recordings of tens of thousands of neurons are feasible thanks to, e.g. a new generation of large dense probes for electrophysiological recordings, imaging using 2-photon microscopy coupled with calcium fluorescent sensors. Large scale neuronal recordings require novel approaches for both processing and quantitative analysis. As well as using techniques from high-dimensional statistics, machine learning, information theory, we aim to explore new approaches from mathematical fields outside statistics, such as algebraic topology. The study of networks is a particularly important topic in neuroscience: neurons communicate with each other electrically via synapses, forming intricate networks. These networks can be studied using techniques from computational topology (e.g. persistent homology, clique topology). These could be used to extract information about subnetworks and assemblies, both from large scale recordings, and via connectomics derived from simulations (Blue Brain Project). We aim in this project to go beyond spike sorting and develop new tools and computational frameworks which would help interpret high dimensional data and interrogate how information is being processed by the brain, e.g. How are sensory stimuli (location in environment, visual and auditory stimuli) encoded? How can we characterise the neural activity associated with memory, attention, decision making and motor control? We shall be collaborating with labs at Imperial, Pennsylvania State University and UCL. More information can be found here: http://www.herts.ac.uk/_ _data/assets/pdf_file/0003/187455/Dec2017-computational-fram eworks-for-high-dimensional-neural-data.pdf *Requirements * We are looking for candidates with the following profile: - Strong first degree in a quantitative field such as mathematics, physics, computer science, engineering, computational neuroscience. - Strong programming skills (e.g. Python, MATLAB, C++). - Interest in neuroscience and biology would be helpful. A studentship from the PhD Programme in Computer Science provides approximately £14,750 per annum bursary plus the payment of student fees. Applicants from outside the UK or EU are eligible. Research in Computer Science at the University of Hertfordshire has been recognised as excellent in the latest Research Excellence Framework Assessment (2014), with 50% of the research submitted rated as internationally excellent or world-leading. The Centre for Computer Science and Informatics Research provides a very stimulating environment, offering a large number of specialised and interdisciplinary seminars as well as general training and researcher development opportunities. The University is situated in Hatfield, in the green belt just north of London. Please contact *Dr Shabnam Kadir* (s.kadir2(a)herts.ac.uk) for informal enquiries. Application forms are available under http://www.herts.ac.uk/a pply/schools-of-study/computer-science/our-research/the-phd- programme-in-computer-science and should be returned to Mrs Lorraine Nicholls and Mrs Emma Thorogood, Research Student Administrators, University of Hertfordshire, College Lane, Hatfield, Herts, AL10 9AB, Tel: 01707 286083, doctoralcollegeadmissions(a)herts.ac.uk. The short-listing process will begin on 25th June 2018. ------------------------------------------------------------ ---------------------------------------------------- Dr Shabnam Kadir Senior Lecturer School of Computer Science, University of Hertfordshire, Hatfield, Hertfordshire AL10 9AB, United Kingdom. Tel. +44 1707 284641 ------------------------------------------------------------ ----------------------------------------------------

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Faculty position in systems neuroscience, U of Montreal
by Paul Cisek May 30, 2018

May 30, 2018

Professor in Systems/Computational Neuroscience Faculty of medicine / Department of neurosciences Mandate description The Département de neurosciences at the Université de Montréal invites applications for a faculty position at the assistant or associate level, in Systems/Computational Neuroscience. We are seeking candidates who use experimental and/or computational approaches to study how large-scale distributed brain networks implement behavioural-level phenomena such as sensorimotor control and decision-making, with a particular emphasis on system-level learning mechanisms. Ideal candidates will either combine multi-electrode, multi-area neurophysiological studies in behaving animals (in particular non-human primates) with sophisticated computational modeling of brain function, or alternatively, will use predominantly computational approaches to study how biologically realistic large-scale and recurrent network models simulate behavioral-level phenomena. The Département de neurosciences offers state of the art laboratory space and animal facilities for rodent and non-human primates research. Montréal is a rich academic environment, with 4 major universities and a strong tradition of systems neuroscience. The candidates will have outstanding opportunities for collaborations with other systems neuroscientists at the Université de Montréal, McGill University, Concordia University and the Université du Québec à Montréal, as well as with leading experts in artificial intelligence, machine learning and deep-learning networks who are centered in the MILA/IVADO at the Université de Montréal. Responsibilities - The appointed candidate will be expected to maintain an active research program, supervise graduate students, have international collaborations, contribute to the academic life of the Department of Neurosciences, and teach undergraduate and graduate courses. - The candidate will collaborate closely with researchers working in three affiliated research centers at University of Montreal: CHU-Ste Justine (Pediatric Hospital), Centre Hospitalier Universitaire de Montréal, Hôpital du Sacré-Coeur de Montréal. - The teaching language is French; consequently, non-French-speaking candidates should become able to teach in French no longer than three years after their appointment. Requirements - The candidate needs to hold a PhD in neurosciences (or equivalent) and demonstrate significant experience at the post-doctoral level in the field of computational neurosciences. - The candidate needs to show exceptional track record in the field, including in sensorimotor control, decision making, neurophysiological studies in living animal, and computational approaches in order to study how neural network are modeling behavior. - The candidate needs to hold teaching experience at graduate and undergraduate levels, as well as experience in supervising post-doctoral fellowships, research assistants, and highly qualified research personal. - We will prioritize candidates with exceptional research productivity with a publication of articles in the best journals in the field, as well as a strong track record of research funding from national and international research agencies. - The ability and interest of the candidate to work in a multidisciplinary team (biochemists, biologists, engineers, bio informaticians, and clinicians) is mandatory. - Have sufficient knowledge of the French language (written and spoken) or be determined to learn it *. General information Posting No: MED 4-18 / 4 Posting period: June 15th, 2018 Salary: The University of Montreal offers a competitive salary and a complete range of employee benefits Start date: Autumn 2018. The announcement will remain open until the selection committee finds an acceptable candidacy. Application procedure Interested candidates should send their curriculum vitae, a letter explaining their motivation, research interest and competence in their area of expertise, and three letters of support, no later than June 15th 2018; at the following address (email correspondence is preferred): Dr Patrick Cossette, directeur Département de neurosciences Faculté de médecine Université de Montréal C.P. 6128, succursale Centre-ville Montréal (Québec) H3C 3J7 E-mail : nancy.crete(a)umontreal.ca <mailto:nancy.crete@umontreal.ca> *Linguistic Policy The Université de Montréal is a Québec University with an international reputation. French is the language of instruction. To renew its teaching faculty, the University is intensively recruiting the worlds best specialists. In accordance with the institutions language policy, the Université de Montréal provides support for newly-recruited faculty to attain proficiency in French. Confidentiality The Université de Montréal application process allows all regular professors in the Department to have access to all documents unless the applicant explicitly states in her or his cover letter that access to the application should be limited to the selection committee. This restriction on accessibility will be lifted if the applicant is invited for an interview. Equal Access Employment Program Université de Montréal promotes diversity in its workforce and encourages members of visible and ethnic minorities as well as women, Aboriginal people, persons with disabilities and people of all sexual orientations and gender identities to apply. Immigration Requirements We invite all qualified candidates to apply at Université de Montréal. However, in accordance with immigration requirements in Canada, please note that priority will be given to Canadian citizens and permanent residents. Paul Cisek, PhD Département de neurosciences Université de Montréal Physical: 2960 chemin de la tour, local 4117 Montréal, QC H3T 1J4 CANADA Mailing: CP 6128 Succursale centre-ville, Montréal, QC H3C 3J7 CANADA e-mail: <mailto:paul.cisek@gmail.com> paul.cisek(a)gmail.com Web: www.cisek.org/pavel <http://www.cisek.org/pavel>

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SenseLab survey
by Ted Carnevale May 29, 2018

May 29, 2018

The SenseLab project applies neuroinformatics methods to make it easier to discover, understand, and reuse neuroscience models, and to relate those models to experimental data. We invite you to help guide the future development of ModelDB http://modeldb.yale.edu and the other SenseLab databases by taking this short survey: https://yalesurvey.ca1.qualtrics.com/jfe/form/SV_2sZuf5bxk99nTnf (Yale recipients: the survey's original URL is https:// yalesurvey.ca1.qualtrics.com/jfe/form/SV_2sZuf5bxk99nTnf minus the space between // and yalesurvey) The SenseLab Team https://senselab.med.yale.edu/ModelDB/modeldb_credits.cshtml

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Multiple Openings for Research Scientists and Engineers to Reverse Engineer intelligence
by Lopez, Camila May 29, 2018

May 29, 2018

Hi, Can you please post this job ad? Multiple Openings for Research Scientists and Engineers to Reverse Engineer intelligence We are looking for exceptionally talented researchers that share our vision: to discover new computational principles of brain intelligence and apply these principles to create fundamentally new algorithms for machine intelligence. We are particularly interested in candidates with expertise in machine learning, computational neuroscience or with strong quantitative background in Mathematics, Statistics, Physics or Computer Science. Our NINAI (Neuro-Inspired Networks for Artificial Intelligence) research team is interdisciplinary and international, with expertise ranging from large-scale neurophysiology and brain circuit analysis to deep learning. POSITIONS: We have opportunities in several project components and multiple locations, and all participants will interact extensively across multiple scientific disciplines and multiple sites. Highest-priority topics include: * Developing new architectures for deep networks * Neuro-inspired networks for real-world tasks * Functional modeling of neuronal microcircuits * Probabilistic inference by population codes * Statistical analysis of large-scale neural data from behaving animals THE TEAM: The project is led by Andreas Tolias (PI) and Xaq Pitkow (co-PI), from Baylor College of Medicine, and includes researchers from Columbia, Cornell, Rice University, University of Toronto, University of Tübingen, the Allen Institute, and Princeton: Matthias Bethge, Liam Paninski, Ankit Patel, Clay Reid, Sebastian Seung, Raquel Urtasun, Chris Xu, Richard Zemel. For detailed information about the team and its members, please see our website, ninai.org<http://ninai.org/>. QUALIFICATIONS: Candidates must have a record of productivity, excellent quantitative skills, good communication skills, and creativity. Experience in Machine Learning and in particular Deep Learning is desired. APPLYING: The positions provide a competitive annual salary and benefits, and outstanding scientific opportunities. Applicants should email a CV, letter of research interests, and contact information for three references to info(a)ninai.org<mailto:info@ninai.org>, camilal(a)bcm.edu<mailto:camilal@bcm.edu> and astolias(a)bcm.edu<mailto:astolias@bcm.edu>. We look forward to hearing from you!

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IEEE Special issue deadline extended!
by Steve Mehrkanoon May 29, 2018

May 29, 2018

Paper Submission Deadline Extended! CALL FOR PAPERS Special issue: Neural Systems Engineering and Mathematical Modelling of Brain dynamics using ECoG/EEG/MEG oscillations and Machine learning methods Journal IEEE Transactions on Neural Systems and Rehabilitation Engineering New Submission Deadline: 01/07/2018 Submission portal: https://mc.manuscriptcentral.com/tnsre-embs Contributions will receive prompt and thorough peer review and will be published online ahead of print after acceptance. In humans, interactions between neuronal circuits, systems and signals among micro-, meso- and macro-scales of brain dynamics underpin the functional organisation of the brain that supports our daily life activity. How efficiently neuronal circuits such as cortico-cortical, cortico-thalamic and thalamo-cortical networks interact among these multiple spatial scales remains to be fully elucidated. Mathematical, computational and experimental neuroscientists apply a variety of methods, techniques and algorithms, both in animals and humans, ranging from single cell recordings to whole brain imaging, in order to identify the core mechanisms that govern the interactions among these scales. Although our knowledge of neural mechanisms, circuits and networks underlying brain dynamics and functions constantly grows, the integration of this knowledge to provide a conceptual framework of emergent behaviour and pattern formation occurring on different levels of spatial organisation remains challenging. Authors are invited to submit original or review articles addressing mechanisms of emergent brain dynamics inferred from the analysis of ECoG/EEG/MEG, on all levels of complexity. Specifically, articles integrating (i) computational neuroscience, and (ii) mathematical models of biologically realistic neuronal networks and machine learning methods are welcome. In this special issue, Guest Editor Dr Steve Mehrkanoon welcomes papers that address many of the challenges of mathematical and computational models of the brain networks and dynamics given the measurement data ECoG/EEG/MEG. The scope of this special issue is interdisciplinary. The list of possible topics includes, but is not limited to: * New developments in computational and mathematical models of mean field theory integrated with ECoG/EEG/MEG modalities. * Multi-modal and combinatorial fusion of ECoG/EEG/MEG data and brain connectivity machine learning. * Development of data-driven machine learning techniques to identify the mechanisms of emergent spatia-temporal dynamics within the framework of network topology. * Development of computational and mathematical models for bridging the scales of brain dynamics. * Cortical network modelling and formal conceptual models of cortical oscillations. * Application of deep learning and machine learning algorithms in functional, structural and effective network analysis and predictive models of brain dynamics. * New cutting-edge numerical analysis and techniques to simulate meso- and macro-scale brain dynamics. * Adaptive mathematical and computational models of network dynamics (e.g., brain development and aging studies). * Statistical methods for assessing individual and population brain connectivity data. Guest Editors 1. Dr Steve Mehrkanoon The University of Queensland Centre for Clinical Research, Faculty of Medicine, School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia Contact: s.mehrkanoon(a)uq.edu.au<mailto:s.mehrkanoon@uq.edu.au> 1. Professor David Liley Centre for Human Psychopharmacology, School of Health Sciences, Swinburne University of Technology, Melbourne, Australia Contact: dliley(a)swin.edu.au<mailto:dliley@swin.edu.au> 1. Dr Siamak Mehrkanoon Department of Electrical Engineering (ESAT), University of Leuven, KU Leuven, Belgium Contact: Siamak.Mehrkanoon(a)esat.kuleuven.be<mailto:Siamak.Mehrkanoon@esat.kuleuven.be> IMPORTANT DATES Extended Submission Deadline: 01/07/2018 Notification Of Acceptance: 31/08/2018 https://tnsre.embs.org/2018/04/13/call-for-papers-special-issue-on-neural-s…) - - - Dr Steve Mehrkanoon Mathematical Neuroscientist, Advance Queensland Research Fellow, Perinatal Research Centre, Faculty of Medicine, Home: http://researchers.uq.edu.au/researcher/14135 Level 4, UQ Centre for Clinical Research, Building 71/918<https://www.google.com.au/maps/place/UQCCR/@-27.448514,153.028703,15z/data=…> Royal Brisbane and Women’s Hospital, Qld 4029 T: +61 7 3346 6012 E: s.mehrkanoon(a)uq.edu.au<mailto:j.wixey@uq.edu.au>

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PhD Position available: Computational methods for longitudinal studies of structural brain connectivity, Deadline 31/5/18
by Emanuele Olivetti May 28, 2018

May 28, 2018

PhD position available (online application details below) Title: Computational methods for longitudinal studies of structural brain connectivity Topic: machine learning / pattern recognition for diffusion MRI data analysis Description: Diffusion MRI provides indirect information of the anatomical structure of the white matter of the brain. Neurological diseases and brain disorders may introduce alterations in such structures. Additionally, after neurosurgery and cognitive rehabilitation, there may be reorganization of the white matter. The goal of this project is to design computational methods to detect and characterize white matter changes over time, disentangling the intrinsic variability of brain recordings from actual anatomical changes, in order to support neuroscientific and clinical inference. References: - https://doi.org/10.3389/fnins.2016.00554 - https://doi.org/10.3389/fnins.2017.00754 Emanuele Olivetti ---------- Forwarded message ---------- From: *PhD CIMeC* <phd.cimec(a)unitn.it <mailto:phd.cimec@unitn.it>> Date: Thu, May 24, 2018 at 10:04 AM Subject: PhD Position available: Computational methods for longitudinal studies of structural brain connectivity, Deadline 31/5/18 To: CIMeC is pleased to announce the opening of a call for 11 fellowships for our international PhD Program in Cognitive and Brain Sciences (CIMeC), commencing November 2018 at the University of Trento, Italy. As you will see from the links below, the PhD call is open to several fields of cognitive neuroscience research. Candidates interested in*Computational methods for longitudinal studies of structural brain connectivity <http://www.unitn.it/drcimec/topic-specific-grants> *should contact *Emanuele Olivetti *at olivetti(a)fbk.eu <mailto:olivetti@fbk.eu>**immediately*.* * *Admissions*: http://www.unitn.it/drcimec/admission <http://www.unitn.it/drcimec/admission> * PhD research areas outline: http://www.unitn.it/drcimec/research-topics <http://www.unitn.it/drcimec/research-topics> * PhD Application*summary*: http://www.unitn.it/drcimec/node/118 <http://www.unitn.it/drcimec/node/118> * PhD*Application*link:https://webapps.unitn.it/Apply/en/MyUnitn/Home/669/dott/cbs34 <https://webapps.unitn.it/Apply/en/MyUnitn/Home/669/dott/cbs34> * PhD Application*Deadline*:*Thursday May 31, 2018, at 4pm (Italian time)* * *CIMeC*:http://www.unitn.it/cimec <http://www.unitn.it/cimec> This year’s research topics proposed by the Doctoral Program Committee for 5 UNITN grants are visible here:http://www.unitn.it/drcimec/research-topics <http://www.unitn.it/drcimec/research-topics>, while the 6 topic-specific grants’ details can be found here:http://www.unitn.it/drcimec/topic-specific-grants <http://www.unitn.it/drcimec/topic-specific-grants> _The CIMeC, it’s doctoral program and UNITN in numbers:_ * 2018 UNITrento ranks among top Italian Universities in THE - Times Higher Education * *4-yr program*(Nov. 1, 2018- Oct. 31, 2022). * Why a 4-yr program <http://www.unitn.it/drcimec/node/117> * Courses are given in English * 11 positions, 100% funded * Salary: starting at approximately €1.200/mo., net * Winners receive a €4887 tax-free research/mobility budget * Why choose UNITRENTO <http://www.unitn.it/en/ateneo/1629/why-choose-the-university-of-trento> Please feel free to browse theFAQ <http://www.unitn.it/drcimec/node/122>pages on our website for further information, or contact the Director of the Programme, Prof. Francesco Pavaniphd.cimec(a)unitn.it <mailto:phd.cimec@unitn.it>. Regards, Leah Mercanti -- Leah Mercanti CIMeC PhD Program Administrator -------------------------------------------------------- CIMeC - Center for Mind/Brain Sciences University of Trento <https://maps.google.com/?q=Trento+Corso+Bettini,+31+I-38068,+Rovereto&entry…> Corso Bettini, 31 <https://maps.google.com/?q=Trento+Corso+Bettini,+31+I-38068,+Rovereto&entry…> I-38068, Rovereto <https://maps.google.com/?q=Trento+Corso+Bettini,+31+I-38068,+Rovereto&entry…> (TN) Tel: +39 0464 80 8617 Fax: +39 0461 28 8690 Skypename: lleahhatwork Email: phd.cimec(a)unitn.it <mailto:phd.cimec@unitn.it> http://www.unitn.it/drcimec/ -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

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Professorship in Computational Neuroscience
by Steuber, Volker May 25, 2018

May 25, 2018

Professor of Computational Neuroscience University of Hertfordshire School of Computer Science, College Lane Campus, Hatfield, UK Salary £58,293 to £67,437 pa depending on skills and experience FTE: Full time position working 37 hours per week (1.0 FTE). Closing date: 21 June 2018 Duration of Contract: Permanent. Applications are invited for an exceptionally well qualified Professor of Computational Neuroscience of international standing, who shares our commitment to research-informed teaching, embraces the research impact agenda, and values collegiality. Applicants will strengthen existing activity within the School and develop it further, enhancing the research strengths and external reputation of the School of Computer Science and contributing significantly to its performance in future research assessments and collaborations with commercial and public partners. The successful applicant will complement the research conducted by the Biocomputation Research Group within the Centre for Computer Science and Informatics Research. As well as providing research supervision at PhD and MSc level, the School of Computer Science offers modules in neural computing and machine learning on the BSc and MSc programmes. Applicants must hold a PhD (or equivalent) in a relevant subject, possess excellent communication skills in English, an internationally excellent research record and reputation, including publications of the highest quality suitable for submission to the REF. Applicants must show evidence of experience and success in research/commercial income generation, engagement with the research impact agenda, engagement with key stakeholders in the Computational Neuroscience community, and management and leadership ability.? Interview Date: Week commencing 17 September 2018. The University offers a range of benefits including a pension scheme, professional development, family friendly policies, child care vouchers, a fee waiver of 50% for all children of staff under the age of 21 at the start of the course, discounted memberships at the Hertfordshire Sports Village and generous annual leave. The University is situated in Hatfield, in the green belt just north of London. Applications must be made online https://www.herts.ac.uk/contact-us/jobs-and-vacancies/academic-vacancies?, reference 016195?. For informal enquiries contact Dr Volker Steuber (v.steuber(a)herts.ac.uk, Head of Biocomputation Research Group, Associate Dean Research) or Prof William Clocksin (w.clocksin(a)herts.ac.uk, Dean of School of Computer Science).

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PhD Studentship in Multilevel modelling of neuronal function: combining metabotropic pathways and membrane excitability in-silico for the quick screening of drugs
by Tsaneva-Atanasova, Krasimira May 25, 2018

May 25, 2018

PhD Studentship in Quantitative Pharmacology and Neuroscience: Multilevel modelling of neuronal function: combining metabotropic pathways and membrane excitability in-silico for the quick screening of drugs University of Reading - School of Pharmacy Supervisors: Dr Francesco Tamagnini (Pharmacy), Dr Marcus Tindall (Mathematics & Statistics), Prof Krasimira Tsaneva-Atanasova (University of Exeter, College of Mathematics, Engineering and Physical Sciences). Project overview: Neurons work as information relays. They integrate information received from the environment at the subcellular scale, generating an appropriate electrophysiological response. The understanding of electrical processes happening at the plasma membrane level has been clarified by Hodgkin and Huxley, combining experimental recordings to mathematical modelling of equivalent electrical circuits. However, quantitative models describing the effects of cell signalling on the cellular response are lacking. Adenosine is a neurotransmitter binding both A1 (Gi) and A2 (Gs) receptors. A1 and A2 stimulation results in altered neuronal excitability via K+ permeability changes. In this project, we aim to combine a mathematical model of adenosine receptor signal transduction (Tindall) with the Hodgkin-Huxley model of a neuron (Tsaneva-Atanasova), to generate an in-silico multiscale model of electrophysiological response to chemical stimulation. We will test the predictive capability of the model with whole-neuron patch-clamp recordings (Tamagnini). The mathematical models formulated during the project will utilise the theory of differential equations (ordinary and partial) solved and analysed both numerically and analytically (e.g. dynamical systems theory, asymptotic methods). The successful candidate will be involved in the design and undertaking of wet laboratory experiments for informing the mathematical models. The final aim of this project is to develop and validate a software capable of predicting changes to an artificial neuron based on its exposure to varying concentrations of a given ligand. Eligibility: * Applicants should hold or expect to gain a minimum of a 2:1 Bachelor Degree or equivalent in Mathematics, Engineering or Neuroscience related subjects. The applicant will have a strong background in mathematics and computer coding (Matlab, Python, C++) and a keenness to engage with and learn wet lab techniques (i.e. pipetting, solution making, single cell electrophysiology); * This studentship is open to UK/EU students only. Funding details: * Starts 10/2018; * 3-year award; * Tuition fees plus stipend (Research Council UK 2018/19 rate is currently £14,777). How to apply: To apply for this studentship, please submit an application for a PhD in Pharmacy at http://www.reading.ac.uk/graduateschool/prospectivestudents/gs-how-to-apply…. Important notes: 1. Please quote the reference ‘GS18-018’ in the ‘Scholarships applied for’ box which appears within the Funding Section of your online application. 2. When you are prompted to upload a research proposal, please omit this step. Application deadline: 30th June 2018. Further enquiries: Please note that, where a candidate is successful in being awarded funding, this will be confirmed via a formal studentship award letter; this will be provided separately from any Offer of Admission and will be subject to standard checks for eligibility and other criteria. For further details, please contact: f.tamagnini(a)reading.ac.uk.<mailto:f.tamagnini@reading.ac.uk>

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Faculty position at UNAM Institute of Neurobiology (Mexico)
by Fidel Santamaria May 24, 2018

May 24, 2018

Computational and Genomic Neuroscience at UNAM The Institute of Neurobiology, UNAM (www.inb.unam.mx<http://www.inb.unam.mx>) invites applications for two tenure-track positions, one in Computational Neuroscience and another one in Genomic Neuroscience. We seek experienced scientists with proven record of publications to develop innovative research programs employing on-campus high performance computing resources to complement the current neuroscience research at the Institute. The successful applicants will be expected to establish externally funded research programs, to engage in intramural collaborative projects, to supervise undergraduate and graduate students, and to teach basic and advanced courses in their field of expertise. Applicants should send their CV, addresses of three references, a five-page research proposal and a one-page statement on their views on teaching to ataulfo(a)unam.mx<mailto:ataulfo@unam.mx>. The application deadline is August 15th, 2018. We encourage applications from women. Instituto de Neurobiología Universidad Nacional Autónoma de México Laboratorio de Neurobiología Molecular y Celular (D15) Juriquilla, Querétaro, QRO CP 76230 Tel. +52 (442) 238-1064 Email ataulfo(a)unam.mx<mailto:ataulfo@unam.mx> atanez(a)gmail.com<mailto:atanez@gmail.com> Skype atanez1

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Post-baccalaureate research position in neuronal mechanism of episodic memory at Max Planck Florida Institute for Neuroscience
by Yingxue.Wang＠mpfi.org May 23, 2018

May 23, 2018

*** Apologies for cross posting*** Post-Baccalaureate Research Experience Summary The Wang Lab at the Max Planck Florida Institute for Neuroscience (links to website<https://yingxuewang.org/>) is inviting applications for the post-baccalaureate research program. This one-year program provides research experience and exposure to students who have graduated from college and are planning to apply to graduate school. We seek highly motivated and independent individuals to join our effort focused on the neuronal mechanisms of learning and episodic memory. Essential Duties & Responsibilities The Wang Lab investigates the circuit underpinnings of episodic memory. In particular, we intend to isolate the hippocampal neuronal activities that are independent of sensory inputs and potentially represent memory traces. We seek to understand how elements of the hippocampal circuit cooperate to generate the internally generated neuronal activities and support the formation and retrieval of memory. Our investigation employs a combination of in vivo electrophysiological, advanced two-photon imaging, optogenetic, and pharmacological approaches, and couples experiments with computational modeling. We encourage applications from candidates who are interested in applying multidisciplinary approaches to examine circuit mechanisms of memory. Education and/or Experience The ideal candidates should have an upcoming or recent bachelor degree in neuroscience or related fields. Candidates holding a degree in electrical engineering, biomedical engineering, computer science, or physics and interested in understanding the neuronal mechanisms of learning and memory are also welcome to apply. Previous experience with in vivo electrophysiology and/or two-photon imaging, quantitative data analysis and computer programming is preferred. Excellent communication skills and an ability to work well in a team are required. Additional Information Max Planck Florida Institute for Neuroscience is part of the Jupiter Neuroscience Research Campus that also includes the Scripps Research Institute Florida and Florida Atlantic University. It provides a flourishing interdisciplinary research environment for neuroscience. Interested candidates are encouraged to send the following documents to Dr. Yingxue Wang (email address: Yingxue.Wang(a)mpfi.org<mailto:Yingxue.Wang@mpfi.org>): - Curriculum vitae - A statement of motivation and interests (1-2 pages) - Academic certificates and transcripts - The names and contact information of two references Please find more details about this program at https://www.maxplanckflorida.org/education/training-programs/pre/. The official application deadline has already passed. Please address the request directly to the above email address. Best regards, Yingxue Wang Research Group Leader Max Planck Florida Institute for Neuroscience

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Postdoctoral Position in Brain-Computer Interfaces
by Tomislav Milekovic May 23, 2018

May 23, 2018

The research group Dr. Tomislav Milekovic at the University of Geneva is offering a postdoctoral position financed by the Wyss Center for Bio and Neuroengineering and the Swiss National Science Foundation to work on restoring communication and independence of people with tetraplegia and locked-in syndrome using brain-computer interfaces. The successful applicant will work to develop and advance brain-computer interfaces based on electroencephalography (EEG) and intracortical microelectrode array recordings. The ideal candidate will have: 1. Experience in assembling and maintaining brain-computer interface systems 2. Leading brain-computer interface experiments with human or animal subjects 3. Experience in the quantitative analysis of electrophysiological neural signals (EEG, ECoG, LFP, spikes) 4. Background in computational/theoretical neuroscience, physics or mathematics 5. Experience in developing and using neural decoders 6. Experience in C/C++ software development The qualified candidate will benefit from joining a very dynamic and multidisciplinary group working at the interface of neuroscience, engineering and prosthetics. They will collaborate with several labs of the Campus Biotech in Geneva, and be strongly supported by the Wyss center for Bio and Neuroengineering led by Prof. John Donoghue. University of Geneva provides state-of-the-art facilities is one of the leading technical universities worldwide. In addition, University of Geneva offers competitive postdoctoral salaries ranking among the highest in the world. Applications including a CV and the statement of research interests should be sent to tomislav.milekovic(a)unige.ch<mailto:tomislav.milekovic@unige.ch>.

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Postdoc position in neuronal mechanism of episodic memory at Max Planck Florida Institute for Neuroscience
by Yingxue.Wang＠mpfi.org May 23, 2018

May 23, 2018

*** Apologies for cross posting*** Postdoctoral Fellow Summary The Wang Lab at the Max Planck Florida Institute for Neuroscience (links to website<https://yingxuewang.org/>) is inviting applications for postdoctoral positions. Our group seeks highly motivated and independent individuals to join our effort focused on the neuronal mechanisms of learning and episodic memory. Essential Duties & Responsibilities The Wang Lab investigates the circuit underpinnings of episodic memory. In particular, we intend to isolate the hippocampal neuronal activities that are independent of sensory inputs and potentially represent memory traces. We seek to understand how elements of the hippocampal circuit cooperate to generate the internally generated neuronal activities and support the formation and retrieval of memory. Our investigation employs a combination of in vivo electrophysiological, advanced two-photon imaging, optogenetic, and pharmacological approaches, and couples experiments with computational modeling. We encourage applications from candidates who are interested in applying multidisciplinary approaches to examine circuit mechanisms of memory. Education and/or Experience The ideal candidates should have an upcoming or recent Ph.D. or MD/Ph.D. in neuroscience or related fields. Candidates holding a Ph.D. in electrical engineering, biomedical engineering, computer science, or physics and interested in understanding the neuronal mechanisms of learning and memory are also welcome to apply. Previous experience with in vivo electrophysiology and/or two-photon imaging, quantitative data analysis and computer programming is highly preferred. Excellent communication skills and an ability to work well in a team are required. Additional Information Max Planck Florida Institute for Neuroscience is part of the Jupiter Neuroscience Research Campus that also includes the Scripps Research Institute Florida and Florida Atlantic University. It provides a flourishing interdisciplinary research environment for neuroscience. We offer outstanding benefits and salary compensation above the NIH scales. Interested candidates are encouraged to send the following documents to Dr. Yingxue Wang (email address: Yingxue.Wang(a)mpfi.org<mailto:Yingxue.Wang@mpfi.org>): - Curriculum vitae with a list of publications - A statement of research experiences and interests (1-2 pages) - The names and contact information of three references Personal contact can be addressed to the above email address prior to the application.

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PhD studentships in Neuromorphic computing and Data Science
by Schmuker, Michael May 23, 2018

May 23, 2018

We are offering a several PhD studentships in the Biocomputation group at the University of Hertfordshire. Details here: https://www.herts.ac.uk/__data/assets/pdf_file/0007/209365/Data-Science-and… Our group translates processes from the brain into algorithms for efficient computing. A particular area of interest is Neural Data Science, where we extract information from complex data sets obtained in neuroscience. Our goal is to shed light on how the brain is processing information and to cast this knowledge into efficient algorithms for pattern recognition and signal processing. We implement such algorithms by leveraging so-called neuromorphic hardware, i.e., specialised computer chips that mimic the massively parallel architecture of the brain, which greatly accelerate brain-inspired neural computing. We are looking for highly motivated candidates with a keen interest in squeezing every bit of information out of complex data sets, to understand how the brain copes with the relentless onslaught of sensory information, and to implement those aspects on a new computer architecture. A diverse choice of topics is available, including but not limited to: • Data mining in neuronal imaging using matrix factorisation and machine learning • Brain-inspired pattern recognition using supervised and unsupervised learning • Olfaction-inspired signal processing and odor recognition for electronic gas sensors It is also possible to suggest topics. Candidates should have excellent programming skills and also some experience in data mining. Previous exposure to low-level hardware programming (e.g. microcontrollers, GPUs) and/or computer engineering is a plus. We collaborate with world-leading neuroscience labs in the UK and abroad to investigate how the brain is processing dynamic sensory information. As a member of the Human Brain Project we pioneer the use of neuromorphic hardware for Data Science. This guarantees a stimulating research environment for a project that aims not only at generating theoretical insight but also validating the findings with experimental scientists and pursuing applications in the real world. Successful candidates are eligible for a research studentship award from the University (approximately GBP 14,777 per annum bursary plus the payment of the standard UK student fees). Applicants from outside the UK or EU are eligible, but will have to pay half of the overseas fees out of their bursary. Please contact Principal Investigator Dr. Michael Schmuker prior to application to scope out a project proposal that is tailored to your background, via email: m.schmuker(a)herts.ac.uk. More info and instructions how to apply are available at https://www.herts.ac.uk/study/schools-of- study/computer-science/our-research/the-phd-programme-in-computer-science . The next short-listing process for studentship applications will begin on 25 June 2018. — Dr Michael Schmuker AFHEA Reader in Data Science Biocomputation Group University of Hertfordshire http://biomachinelearning.net

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PhD position in systems/computational neuroscience, Leicester, UK
by Okun, Michael (Dr.) May 22, 2018

May 22, 2018

A PhD position is available at Centre for Systems Neuroscience, Leicester, UK. The project will focus on organisation and mechanisms of resting state cortical dynamics, particularly in the infraslow (0.01 - 1 Hz) timescales. Additional details are available at https://www.findaphd.com/search/ProjectDetails.aspx?PJID=97389 or by contacting Michael Okun (m.okun(a)le.ac.uk) The deadline for applications is 7th of June.

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OMG- Emotion Recognition Challenge - Final Results
by Pablo Barros May 22, 2018

May 22, 2018

Dear all, I would like to share with you all the results of our first OMG- Emotion Recognition Challenge. Our challenge is based on the One-Minute-Gradual Emotion Dataset (OMG-Emotion Dataset), which is composed of 567 emotion videos with an average length of 1 minute, collected from a variety of Youtube channels. Each team had a task to describe each video with a continuous space of arousal/valence domain. The challenge had a total of 34 teams registered, from which we got 11 final submissions. Each final submission was composed of a short paper describing the solution and the link to the code repository. The solutions used different modalities (ranging from unimodal audio and vision to multimodal audio, vision, and text), and thus provide us with a very complex evaluation scenario. All the submissions were based on neural network models. We split results into arousal and valence. For arousal, the best results came from the GammaLab team. Their three submissions are our top 3 CCC arousal, followed by the three submissions from the audEERING team, and the two submissions from the HKUST-NISL2018 team. For valence, the GammaLab team stays still in first (with their three submissions), followed by the two submissions of ADSC team and the three submissions from the iBug team. Congratulations to you all! We provide a leaderboard on our website ( https://www2.informatik.uni-hamburg.de/wtm/OMG-EmotionChallenge/ ), which will be permanently stored. This way, everyone can see the final results of the challenge, have a quick access to a formal description of the solutions and to the codes. This will help to disseminate knowledge even further and will improve the reproducibility of your solutions. We also provide a general leaderboard which will be updated constantly with new submissions. If you are interested in having your score in our general leaderboard, just send us an e-mail following the instructions on our website. I would also to invite you all to the presentation of the challenge summary during the WCCI/IJCNN 2018 in Rio de Janeiro, Brasil. Best Regards, Pablo -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html https://www.inf.uni-hamburg.de/en/inst/ab/wtm/

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Call for Papers: Special Session on Computational Methods for Neuroimaging Analysis, 6-8 September, Portugal
by Tiago Azevedo May 22, 2018

May 22, 2018

Dear all, Below find the call for papers for the special session "Computational Methods for Neuroimaging Analysis". It will be be held during the 15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, at Caparica, Portugal, from 6 to 8 September. **Important Dates** Paper submission deadline: 10 June 2018 Acceptance notification: 9 July 2018 Author registration due: 20 July 2018 Camera ready due: 29 July 2018 Conference: 6-8 September 2018 **Link** https://eventos.fct.unl.pt/cibb2018/pages/special-sessions **Aim and scope** There is an increasing need for the application of machine learning (ML) techniques which can perform image processing operations such as segmentation, coregistration, classification and dimensionality reduction in the field of neuroimaging. Although the manual approach often remains the golden standard in some tasks (like segmentation), ML can be utilised to automate and facilitate the work of researchers and clinicians. Frequently used techniques include support vector machines (SVMs) for classification problems, graph-based methods for brain network analysis and recently artificial neural networks (ANNs). Deep ANNs, i.e. deep learning, have proved to be very successful in computer vision tasks owing to the ability to automatically extract hierarchical descriptive features from input images. It has also been used in the medical and neuroimaging domains for automatic disease diagnosis, tissue segmentation and even synthetic image generation. The issue, however, is the relative sample paucity in typical neuroimaging datasets which leads to poor generalisation considering the high number of parameters employed in typical deep neural networks. Consequently, parameter- efficient design paradigms ought to be created. Another approach to investigate degeneration is the study and mapping of the neural connections in the brain known as the connectome. The connectome can be seen as a matrix representing all possible pairwise connections between different neural areas. Researchers study both the structural and functional connectivity in order to understand important brain patterns, such as how the connectome impacts the dynamics of disease spreading, ageing and learning. Topics of interest includes but are not limited to: • Machine learning techniques for segmentation, coregistration, classification or dimensionality reduction of neuroimages   • Deep learning for neuroimaging analysis   • Brain network analysis   • Applications of graph theory to MRI and fMRI data   • Applications of machine learning methodologies for neurodegenerative disease studies   • Computational modelling and analysis of neuroimaging   • Methods of analysis for structural or functional connectivity   • Development of new neuroimaging tools **Session chairs** Tiago Azevedo, University of Cambridge, UK Giovanna Maria Dimitri, University of Cambridge, UK Pietro Liò, University of Cambridge, UK Angela Serra, University of Salerno, Italy Simeon Spasov, University of Cambridge, UK

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