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[EAIS 2017] Paper Submission deadline is on Sunday, 15th January 2017 2359 UTC-12hr

by Teng Teck Hou

[Apologies for cross-postings] ################################################## CALL FOR PAPERS IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2017) May 31- June 2, 2017, Ljubljana, Slovenia http://msc.fe.uni-lj.si/eais2017/ ################################################## The 2017 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2017) will be held in Ljubljana (Slovenia), a beautiful medieval town. Ljubljana lies halfway between Vienna and Venice, at the crossroads of different cultures, geographical regions, and historical developments. Compared to other capitals, Ljubljana is very small, very green, and very walking-friendly town, which makes it a great place to explore on foot. It is in the center of Slovenia and enables exploring some of the most popular tourist sights of Slovenia in one day. Visit enchanting Bled, with its medieval castle perched upon the lake, explore mysterious Predjama castle and end the trip by visiting Postojna cave, Slovenia's number 1 attraction. EAIS 2017 will provide a working and friendly atmosphere and will be a leading international forum focusing on the discussion of recent advances, the exchange of recent innovations and the outline of open important future challenges in the area of Evolving and Adaptive Intelligent Systems. Over the past decade, this area has emerged to play an important role on a broad international level in today's real-world applications, especially those ones with high complexity and dynamics change. Its embedded modelling and learning methodologies are able to cope with real-time demands, changing operation conditions, varying environmental influences, human behaviors, knowledge expansion scenarios and drifts in online data streams. EAIS 2017 is organized by the IEEE Technical Committee on Evolving and Adaptive Intelligent Systems, SMC Society. The conference series has a history starting in 2006 in Lake District (England). It was held after that in Witten-Bommerholz (Germany), Nashville (USA), Leicester (England), Paris (France), Madrid (Spain), Singapore, Linz (Austria), Douai (France), and Natal (Brasil). Authors of selected papers will be invited to submit extended versions for possible inclusion in a special issue of the Journal Evolving Systems (Springer). ##############################Important Dates############################## * Paper Submission January 15, 2017 * Paper Decision Notification February 24, 2017 * Camera-Ready Submission March 24, 2017 * Authors registration March 24, 2017 * Conference May 31 - June 2, 2017 ########################################################################### ##########################Keynote Speakers########################## * Plamen Angelov, Professor, Lancaster University, United Kingdom * Fernando Gomide, Professor, University of Campinas, Brazil * Nikola Kasabov, Professor of Computer Sience, Auckland University of Technology, New Zealand #################################################################### ##########################Accepted Special Sessions########################## 1. Computational Intelligence in Control of Power Generating Systems, Transmission and Load Management, Session proposer: Horst Schulte, HTW Berlin Email: Horst.Schulte(a)HTW-Berlin.de ############################################################################ # ############Paper Submission and Publication############ * Papers for EAIS 2017 should be submitted electronically through the Conference website at http://msc.fe.uni-lj.si/eais2017. * Submitted papers will be refereed by experts in the fields and ranked based on the criteria of originality, significance, quality and clarity. ######################################################## ######################################################## IEEE Autonomous Learning Machines Competition ALMA Competition is organized by IEEE SMC Society. The goal of this competition is to increase the level of autonomy of the learning algorithms. Competition Tracks: 1. New data sets and streams that are suitable demonstrators for the topic of the competition. 2. New methods and algorithms for Autonomous Machine Learning in: . Clustering . Classification . Control . Prediction Awards: Track 1 - $1000 Track 2 - $1000 in each category ($4000). Important Dates: 31 January, 2017. Deadline for submitting the algorithms in open source GNU license format. The proposed methods and algorithms must be described in form of papers and submitted to the ALS Competition track of EAIS 2017 and presented at the conference (which will be held in Ljubljana, Slovenia). May 31- June 2, 2017. Results will be announced during the conference EAIS 2017. ######################################################## ##################Topics and Areas of Interest################## This conference solicits papers addressing original works in topics and areas of interest including, but are not limited to: * Basic Methologies Evolving Soft Computing Techniques Evolving Fuzzy Systems Evolving Rule-Based Classifiers Evolving Neuro-Fuzzy Systems Adaptive Evolving Neural Networks Adaptive Evolving Fuzzy Systems Online Genetic and Evolutionary Algorithms Data Stream Mining Incremental and Evolving Clustering Approaches Adaptive Control Adaptive Pattern Recognition Computational Intelligence in Control and Estimation Incremental and Evolving ML Classifiers Adaptive Statistical Techniques Evolving Decision Systems Big Data Advanced Concepts * Problems and Methodologies in Data Streams Stability, Robustness, Convergence in Evolving Systems Online Feature Selection and Dimension Reduction Online Active and Semi-supervised Learning Online Complexity Reduction Computational Aspects Interpretability Issues Incremental Adaptive Ensemble Methods Online Bagging and Boosting Self-monitoring Evolving Systems Human-Machine Interaction Issues Hybrid Modeling Transfer Learning Reservoir Computing Real-world Applications * EIS for On-Line Modeling, System Identification, and Control EIS for Time Series Prediction EIS for Data Stream Mining and Adaptive Knowledge Discovery EIS in Robotics, Intelligent Transport and Advanced Manufacturing EIS in Advanced Communications and Multi-Media Applications EIS in Bioinformatics and Medicine EIS in Online Quality Control and Fault Diagnosis EIS in Condition Monitoring Systems EIS in Adaptive Evolving Controller Design EIS in User Activities Recognition EIS in Huge Database and Web Mining EIS in Visual Inspection and Image Classification EIS in Image Processing EIS in Cloud Computing EIS in Multiple Sensor Networks EIS in Query Systems and Social Networks EIS in Alternative Statistical and Machine Learning Approaches ################################################################ ##########################Organizing Committee########################## * Honorary Chairs Plamen Angelov, UK Dimitar Filev, USA Nikola Kasabov, New Zealand * Conference Chair Igor Škrjanc, chair, Slovenia Sašo Blažic, co-chair, Slovenia * Publication Chairs Edwin Lughofer, Austria Sašo Blažic, Slovenia * Local Arrangement Chairs Dejan Dovžan, Slovenia Milan Simcic, Slovenia * Web & Publicity Chair José A. Iglesias, Spain Teck-Hou Teng, Singapore * Special Session Chair: Radu-Emil Precup, Romania * Program Committee Chair: Igor Škrjanc, Slovenia * International Program Committe Cesare Alippi, Italy Plamen Angelov, UK Rosangela Ballini, Brazil Rashmi Dutta Baruah, India Abdelhamid Bouchachia, UK Jorge Cassillas, Spain Bruno Costa, Brazil Dejan Dovžan, Slovenia Alain Droniou, France Dimitar Filev, USA Nadine Gaertner, Germany Joao Gama, Portugal Fernando Gomide, Brazil Jose Antonio Iglesias Martínez, Spain Lazaros Iliadis, Greece Nik Kasabov, New Zealand Juš Kocijan, Slovenia Ana Kosareva, Germany Rudolf Kruse, Germany Agapito Ledezma, Spain Daniel Furtado Leite, Brazil Andre Lemos, Brazil Chin Teng Lin, Taiwan Edwin Lughofer, Austria Yannis Manolopoulos, Greece Trevor Martin, UK Moamar Sayed Mouchaweh, France Veronika Nesheva, UK Seiichi Ozawa, Japan Witold Pedrycz, Canada Radu-Emil Precup, Romania Jose de Jesus Rubio, Mexico Araceli Sanchis de Miguel, Spain Horst Schulte, Germany Olga Senyukova, Russia Teck Hou Teng, Singapore Marley Vellasco, Brazil Di Wang, UAE Wilson Wang, Canada Ronald Yager, USA ####################################################################### #########################Sponsoring Organizations######################### * IEEE * Laboratory of Modeling, Simulation and Control, University of Ljubljana * Laboratory of Autonomous Mobile Systems, University of Ljubljana ##########################################################################

Jan. 11, 2017

PhD position available at ETH Zürich

by Felix Franke

We are looking for a talented student with a proactive and self-driven nature who will map functional characteristics of retinal ganglion cells across the entire retina. The successful candidate will perform experiments with ex-vivo retinae and state-of-the-art microelectrode array technology in an interdisciplinary research project and will collaborate with scientists in electrical engineering, neurobiology, computational neuroscience and ophthalmic research. The PhD project is set in an interdisciplinary research group providing an exciting scientific environment and linked with several ongoing projects. It will pave the way to a better functional understanding of the organization of retina, including the optics of the eye and the statistics of natural stimuli. In particular, we want to understand if functional properties of retinal ganglion cells follow a spatial organization across the entire retina. The ideal candidate will have strong programming skills (e.g., Matlab, Python, C++), knowledge of statistics and data analysis methods, and a background in Systems Neuroscience, Electrophysiology, Computational Neuroscience, Signal Processing, Optics or related fields. Inquiries should be addressed to Dr. Felix Franke (felix.franke(a)ethz.ch) The position is with the Bio Engineering Laboratory of ETH Zurich in Basel in the group of Prof. Andreas Hierlemann (https://www.bsse.ethz.ch/bel) and begins in March 2017 although the starting date is flexible. The position is fully funded for 4 years. Please apply under https://apply.refline.ch/845721/5083/pub/1/index.html including a CV, short statement of motivation and research interests, and two letters of reference. -- Felix Franke, PhD ETH Zürich, D-BSSE Bio Engineering Laboratory (BEL) http://www.bsse.ethz.ch/bel

Jan. 10, 2017

Save the Date: 3rd Int. Workshop on Machine learning, Optimization & big Data - MOD 2017 Call for Papers - Paper submission deadline: February 28, 2017

by Giuseppe Nicosia

[Apologies if you receive multiple copies of this announcement] [Please kindly help forward it to potentially interested attendees] 3rd International Workshop on Machine learning, Optimization and big Data - MOD 2017 An Interdisciplinary Workshop: Machine Learning, Optimization and Data Science without Borders - SIAF Learning Village - Volterra (Pisa) Tuscany, September 14-17, 2017 http://www.taosciences.it/mod/ modworkshop2017(a)gmail.com ************************* CALL FOR PAPERS ************************* Paper submission deadline: February 28, 2017 http://www.taosciences.it/mod/call-for-papers/ https://easychair.org/conferences/?conf=mod2017 The MOD 2017 workshop will consist of four days of workshop sessions and special sessions. We invite submissions of papers, abstracts and posters on all topics related to Machine learning, Optimization and Big Data including real-world applications for the workshop proceedings: http://www.taosciences.it/mod/call-for-papers/ https://easychair.org/conferences/?conf=mod2017 Please prepare your paper in English using the Lecture Notes in Computer Science (LNCS) template, which is available http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0 Papers must be submitted in PDF. MOD 2017 Types of Submissions When submitting a paper to MOD 2017, authors are required to select one of the following four types of papers: + Long paper: original novel and unpublished work (max. 12 pages in Springer LNCS format); + Short paper: an extended abstract of novel work (max. 4 pages); + Work for oral presentation only (no page restriction; any format). For example, work already published elsewhere, which is relevant and which may solicit fruitful discussion at the workshop; + Work for poster presentation only. The poster format for the presentation is A0 (118.9 cm high and 84.1 cm wide, respectively 46.8 x 33.1 inch). For research work which is relevant and which may solicit fruitful discussion at the workshop. MOD 2017 Post-Proceedings All accepted long papers will be published in a volume of the series 'Lecture Notes in Computer Science' from Springer *after* the Workshop. Instructions for preparing and submitting the final versions (camera-ready papers) of all accepted papers will be available later on. All the other papers (short papers, abstract of the oral presentations, poster presentations) will be published on the MOD 2017 web site. MOD 2017 Submission System All papers must be submitted using EasyChair: https://easychair.org/conferences/?conf=mod2017 The deadline is February 28, 2017 MOD 2017 Important Dates + Paper Submission Deadline: February 28, 2017 + Decision Notification to Authors: May 1st, 2017 + Camera Ready Submission Deadline: June 1st, 2017 + Deadline for early Registration as Presenting Author: June 1st, 2017 + Late registration: June 2 – September 17, 2017 + On-Site registration: September 14-17, 2017 + MOD 2017 Workshop: September 14-17, 2017 We look forward to seeing you in Tuscany! Giuseppe Nicosia & Panos Pardalos - MOD 2017 Chairs. — http://www.taosciences.it/mod/ modworkshop2017(a)gmail.com MOD 2016 Keynote Speakers: Nello Cristianini, University of Bristol, UK George Michailidis, University of Florida, USA Stephen Muggleton, Imperial College London, UK Panos Pardalos, University of Florida, USA http://www.taosciences.it/mod-2016/keynote-speakers/ MOD 2015 Keynote Speakers: Vipin Kumar, University of Minnesota, USA Panos Pardalos, University of Florida, USA Tomaso Poggio, MIT, USA http://www.taosciences.it/mod-2015/MOD 2015 -- Giuseppe Nicosia, Ph.D. Associate Professor of Computer Science Dept of Mathematics & Computer Science University of Catania Viale A. Doria, 6 - 95125 Catania, Italy P +39 095 7383048 nicosia(a)dmi.unict.it http://www.dmi.unict.it/nicosia ================================================================== 4th International Synthetic & Systems Biology Summer School - SSBSS 2017 * Biology meets Computer Science & Engineering * July 17-21, 2017 - University of Cambridge, Robinson College, UK http://www.taosciences.it/ssbss/ Contact Email: ssbss.school(a)gmail.com FB: https://www.facebook.com/ssbss.school/ SSBSS - Synthetic & Systems Biology Summer School Group: https://www.facebook.com/groups/238417586492061/ Computational Synthetic Biology Group: https://www.facebook.com/groups/1014624245288596/ ================================================================== 3rd International Workshop on Machine learning, Optimization & big Data - MOD 2017 September 14-17, 2017 - Volterra (Pisa), Tuscany, Italy modworkshop2017(a)gmail.com http://www.taosciences.it/mod/ ==================================================================

Jan. 9, 2017

Master position in computational neuroscience at INRIA

by Bruno Cessac

Master position in computational neuroscience at INRIA We are seeking an undergraduate student interested in doing a Master thesis, possibly followed by a funded Ph.D. in our group Biovision at INRIA Sophia Antipolis <http://www.inria.fr/en/centre/sophia> lead by Dr. Bruno Cessac. The detailed proposition can be found here https://team.inria.fr/biovision/files/2016/12/M2_Intership_Proposal.pdf In collaboration with experimentalists our group studies how the visual system encodes information about external word. We propose biophysical models, we develop methods coming from theoretical physics and mathematics to analyse them, and we design software inspired from the visual system to mimic its behaviour and to analyse experimental data. Successful applicants should have a strong background in computer science. Physics, mathematics or life science majors with strong skills in computer science (especially C/C++), interested in quantitative modeling work are also encouraged to apply, particularly if they would like to combine experiments and theory in their Master or Ph.D. thesis work. In order to make teamwork in our group enjoyable and fun, the ideal candidate should have a strong work ethic and have demonstrated consistent self-motivation skills. Unfortunately our source of fundings only covers members of the European Community. Prospective students should apply by sending an email to which includes * a letter of motivation, * CV, * and a copy of the current academic transcripts to be sent to bruno.cessac(a)inria.fr Looking forward to your applications! Bruno Cessac

Jan. 9, 2017

several full-time job openings at HRL Laboratories in Malibu, CA

by Pilly, Praveen K

(1) POST DOC RESEARCH STAFF, Machine Learning and Brain-Inspired Computing (2) RESEARCH STAFF, Machine Learning and Brain-Inspired Computing EDUCATION DESIRED: Ph.D. in Applied Mathematics, Neuroscience, Machine Learning, or related fields. ESSENTIAL JOB FUNCTION: To develop, implement, and evaluate novel large-scale brain-inspired computational architectures, including spiking neuromorphic models, to solve complex problems such as resilient sensorimotor control; one-shot learning; visual scene segmentation, recognition, and tracking; spatiotemporal pattern discovery; big data prognostics and diagnostics; grammar learning; etc. Additional job functions include writing invention disclosures, publishing papers, making presentations, and assisting in marketing HRL expertise. KNOWLEDGE AND EXPERIENCE DESIRED: Programming proficiency in C++, Python, or Matlab is required. Knowledge and/or research experience in the development, implementation, and evaluation of various neural networks including spiking neuromorphic models, deep learning models, hierarchical temporal memory models, recurrent neural networks, long short-term memory models, deep reinforcement models. Knowledge of expectation maximization theory, Bayesian inference on graphical models, reinforcement learning theory, control systems, nonlinear optimization, and episodic, semantic, and procedural memory systems is preferred. Any experience with high-performance computing using clusters, GPUs, or FPGAs will be a plus. ESSENTIAL PHYSICAL/MENTAL REQUIREMENTS: Good communication (verbal and written) skills, and active participation in R&D team activities are required. Able and willing to occasionally travel. SPECIAL REQUIREMENTS: U.S. person status required. (3) POST DOC RESEARCH STAFF, Machine Learning and EEG Processing EDUCATION DESIRED: Ph.D. in Applied Mathematics, Neuroscience, Machine Learning, Bio-Statistics, or related fields ESSENTIAL JOB FUNCTION: To develop, implement, and validate real-time pattern recognition algorithms for decoding high-density EEG signals to predict future behavioral performance and inform non-invasive brain stimulation for behavioral enhancement in realistic tasks. Additional job functions include writing invention disclosures, publishing papers, making presentations, and assisting in marketing HRL expertise. EXPERIENCE DESIRED: Research experience in one or more of the following areas: high-density EEG decoding, pattern recognition applied to brain/body signals, machine learning with very limited training data, brain-machine interfaces, neural statistical modeling, closed-loop brain stimulation, and computational neuroscience. Deep understanding of machine learning algorithms applied to EEG is highly desirable. Experience developing innovative solutions based upon the application of relevant research results from a wide variety of sources. Individuals with a keen interest in translating basic neuroscience research into real-world applications are especially encouraged to apply. KNOWLEDGE AND EXPERIENCE DESIRED: Background in one or more of the following areas: machine learning, pattern recognition, statistical data analysis, neural statistical modeling, neurophysiology, peripheral physiology, neuroscience, and sleep/wake states. Programming proficiency in Matlab and/or C++ is required. ESSENTIAL PHYSICAL/MENTAL REQUIREMENTS: Good communication (verbal and written) skills and active participation in R&D team activities are required. Able and willing to occasionally travel. SPECIAL REQUIREMENTS: U.S. person status required. We are proud to be an EOE/Minorities/Females/Vet/Disability employer. We maintain a drug-free workplace and perform pre-employment substance abuse testing. (4) SOFTWARE ENGINEER, Cluster Implementation for Large-Scale Brain Networks EDUCATION DESIRED: Master's degree (or higher) in computer science, engineering, or related fields ESSENTIAL JOB FUNCTION: To implement and evaluate flexible, general-purpose large-scale brain networks on CPU and GPU clusters for real-time operation in real-world applications. Also to visualize large-scale network activity and develop a user interface to set various parameters. Additional job functions include writing invention disclosures, publishing papers, making presentations, and assisting in marketing HRL expertise. KNOWLEDGE AND EXPERIENCE DESIRED: Strong C++ and Python programming skills are required. Experience with/knowledge of brain networks and neural models is highly desired. Experience with threaded programming and MPI, and familiarity with Linux development environment is desired but not necessary. ESSENTIAL PHYSICAL/MENTAL REQUIREMENTS: Good communication (verbal and written) skills, and active participation in R&D team activities are required. SPECIAL REQUIREMENTS: U.S. person status required. We are proud to be an EOE/Minorities/Females/Vet/Disability employer. We maintain a drug-free workplace and perform pre-employment substance abuse testing. The Information and Systems Sciences Laboratory (ISSL) at HRL Laboratories conducts groundbreaking research in three thrust areas: Complex Networks, Secure and Resilient Systems, Autonomy Computing, and Human-Machine Cognition. We create new and innovative capabilities for diverse applications such as cyber-security, unmanned autonomous systems, human performance augmentation, big data analytics, intelligence, surveillance, and reconnaissance, and electronic warfare. The goal of our research in Human-Machine Cognition is to understand how humans process information and effectively interact with the environment to develop smarter autonomous systems, enhance human performance, and develop novel processing systems. Our research starts with the development of large-scale, neurobiologically and behaviorally faithful brain region models. We apply these models along with real-time measurements of brain activity (EEG, fMRI, fNIRS) to create advanced brain-computer interfaces, human decision aids, and neurostimulation-based enhanced training systems. We also use our models to develop novel brain-inspired sensor exploitation, machine learning, and control algorithms, and to develop low size, weight and power brain-based processing hardware for resilient autonomous systems, dexterous robots, and threat warning applications. HRL offers a competitive salary and benefits package, a small company atmosphere, and an ideal work location overlooking the Pacific Ocean. We also provide a collaborative technical culture committed to producing the leading R&D in the world. If interested, please send your resume via email to Dr. Praveen Pilly (pkpilly(a)hrl.com<mailto:pkpilly@hrl.com>) and put the pertinent Job Name in the subject heading. -- Praveen K. Pilly, Ph.D. Research Staff Scientist Information and Systems Sciences Laboratory HRL Laboratories Address: 3011 Malibu Canyon Road, Malibu, CA 90265 Tel: (310) 317-5492 Email: pkpilly(a)hrl.com

Jan. 8, 2017

Multiple Postdoc positions in systems neuroscience at Columbia University

by Qi Wang

Apologies for cross posting. Multiple postdoc positions funded by NIH and DARPA projects are available in the Laboratory for Neural Engineering and Control in the Department of Biomedical Engineering at Columbia University (http://neclab.bme.columbia.edu/) The projects investigate the role of the locus coeruleus (LC) – norepinephrine (NE) system in modulating perception, behavior and learning, and how to accelerate perceptual learning through control of LC activity and peripheral nerve stimulation. We are seeking highly motivated individuals with excellent academic track-record, including first-author publications in peer-reviewed journals. Successful candidates should have, or be in the process of completing, a PhD (or equivalent) in Biomedical Engineering, Neuroscience, Electrical & Computer Engineering, or a related field. Ideal applicants should have a background on electrophysiology, behavioral training of rodents, and quantitative analytical methods. Experiences in optical imaging is a plus. Applicants should demonstrate excellent oral and written communication skills, and the ability to work effectively independently and as part of a multidisciplinary team. Applicants should submit a CV, including a list of publications, a brief description of research interests, and a list of three references. All application materials as well as any inquiries should be sent to qi.wang(a)columbia.edu. Salary will be commensurate to the candidate qualifications. -- ====================================== Qi Wang, Assistant Professor Dept. of Biomedical Engineering Columbia University ET 351, 500 W 120th Street New York, NY 10027 Email:qi.wang@columbia.edu Associate Editor IEEE Transactions on Neural Systems and Rehabilitation Engineering http://tnsre.embs.org/

Jan. 6, 2017

Applications open for Okinawa/OIST Computational Neuroscience Course 2017

by Erik De Schutter

OKINAWA/OIST COMPUTATIONAL NEUROSCIENCE COURSE 2017 Methods, Neurons, Networks and Behaviors June 26 to July 13, 2017 Okinawa Institute of Science and Technology Graduate University, Japan https://groups.oist.jp/ocnc The aim of the Okinawa/OIST Computational Neuroscience Course is to provide opportunities for young researchers with theoretical backgrounds to learn the latest advances in neuroscience, and for those with experimental backgrounds to have hands-on experience in computational modeling. We invite graduate students and postgraduate researchers to participate in the course, held from June 26th through July 13th, 2017 at an oceanfront seminar house of the Okinawa Institute of Science and Technology Graduate University. Applications are through the course web page (https://groups.oist.jp/ocnc) only; January 3 - February 5, 2017. Applicants will receive confirmation of acceptance in March. Like in preceding years, OCNC will be a comprehensive three-week course covering single neurons, networks, and behaviors with ample time for student projects. The first week will focus exclusively on methods with hands-on tutorials during the afternoons, while the second and third weeks will have lectures by international experts. The course has a strong hands-on component based on student proposed modeling or data analysis projects, which are further refined with the help of a dedicated tutor. Applicants are required to propose their project at the time of application. There is no tuition fee. The sponsor will provide lodging and meals during the course and may support travel for those without funding. We hope that this course will be a good opportunity for theoretical and experimental neuroscientists to meet each other and to explore the attractive nature and culture of Okinawa, the southernmost island prefecture of Japan. Invited faculty: • Upinder Bhalla (NCBS, India) • Erik De Schutter (OIST) • Kenji Doya (OIST) • Bard Ermentrout (University of Pittsburgh, USA) • Ila Fiete (University of Texas Austin, USA) • Sonja Grün (Research Centre Jülich, Germany) • Shin Ishii (Kyoto University, Japan) • Jason Kerr (MPI Bonn, Germany) • Bernd Kuhn (OIST) • Subkin Lim (NYU Shanghai, China) • Michele Migliore (Institute of Biophysics, Italy) • David Redish (University of Minnesota, USA) • Reza Shadmehr (Johns Hopkins University, USA) • Greg Stephens (OIST) • Yoko Yazaki-Sugiyama (OIST) • Charles Wilson (University of Texas San Antonio, USA)

Jan. 6, 2017

Columbia Workshop on Brain Circuits, Memory and Computation 2017

by Aurel A. Lazar

Columbia Workshop on Brain Circuits, Memory and Computation 2017 BCMC 2017 March 13-14, 2017 Center for Neural Engineering and Computation 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/2017> is being conducted in conjunction with the workshop. Workshop participants are welcome to attend the hackathon. Organizer and Program Chair Aurel A. Lazar <http://www.ee.columbia.edu/~aurel>, Department of Electrical Engineering, Columbia University. Program Overview (Confirmed Speakers) Dinu Florin Albeanu <http://albeanulab.labsites.cshl.edu/people/>, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY. Vijay Balasubramanian <http://www.sas.upenn.edu/~vbalasub/public-html/Home.html>, Department of Physics, University of Pennsylvania. Albert Cardona <https://www.janelia.org/people/albert-cardona>, Janelia Research Campus, Ashburn, VA. Ann-Shyn Chiang <http://brc.life.nthu.edu.tw/FlyLab/html/leader.html>, National Tsing Hua University, Hsinchu, Taiwan. Jonathan B. Demb <http://eyes.yale.edu/people/jonathan_demb.profile>, Yale School of Medicine. Barry J. Dickson <https://www.janelia.org/people/barry-dickson>, Janelia Research Campus, Ashburn, VA. Anmo J. Kim <http://www.rockefeller.edu/research/faculty/labmembers/GabyMaimon/>, Rockefeller University, New York. Konrad P. Kording <http://klab.smpp.northwestern.edu/wiki/index.php5/People>, Feinberg School of Medicine, Northwestern University. Adam H. Marblestone <http://www.adammarblestone.org/>, Synthetic Neurobiology Group, MIT. Katherine I. Nagel <http://www.nagellab.com/people/>, NYU Medical School. Gerald M. Rubin <http://www.hhmi.org/scientists/gerald-m-rubin>, Janelia Research Campus, Ashburn, VA. Silke Sachse <https://www.ice.mpg.de/ext/index.php?id=hopa&pers=sisa3622>, Max Planck Institute for Chemical Ecology, Jena. Marion Silies <http://www.eni-net.org/members/dr-marion-silies>, European Neuroscience Institute, Göttingen. Andreas S. Thum <https://cms.uni-konstanz.de/neuro/member/?tx_mhkleineidam_pi1%5BpId%5D=5029>, Department of Biology, University of Konstanz. Tim P. Vogels <https://www.dpag.ox.ac.uk/research/vogels-group>, Department of Physiology, Anatomy and Genetics, University of Oxford. More information about BCMC 2017 can be found here <http://fruitflybrain.org/workshops.html>. Aurel http://www.bionet.ee.columbia.edu <http://www.bionet.ee.columbia.edu/>

Jan. 5, 2017

Fwd: Ressearch Assitant McGill University

by Md. Taufiq Nasseef

I am already a member of this comp-neuro mailing list. Could you circulate this one please. Thanks. Best wishes, Taufiq *Please see advertisement below:* *Job Title:* Research Assistant *Hiring Unit*: Dr. Brigitte Kieffer’s laboratory *Work Location*: Douglas Hospital and Research Center - Perry Building 6875, boul. LaSalle *Hours/week*: 35 hours/week – Mon-Fri *Salary*: $27,000 -36,000 (adjusted according to experience) *Start Date:* February 1st 2017 *Description:* The selected candidate will be part of an internationally renowned team of Prof. Brigitte Kieffer (http://douglas.research. mcgill.ca/brigitte-kieffer) and will be a key actor for two team projects. These studies aim at understanding the function of Mu opioid receptors (the receptors for morphine) within brain networks and also test innovative opiates drugs. Methodological approaches include establishment of functional connectivity signatures using fMRI in live mice and also visualize/quantify receptor signaling by fluorescence microscopy. The selected candidate will be responsible for image acquisition and post-processing of the fMRI images as well as participating in the development of a pipeline to analyze multiphoton or confocal microscopy images. *Primary Duties*: Acquisition of fMRI images (Bruker 7 Tesla) Data analysis and image post-processing 3D reconstruction and volume analysis of microscopy (confocal/multiphoton) images *Requirements:* Bachelors degree in Biology/Computer Science or relevant experience. Knowledge in MRI and animal experimentation. Knowledge in coding, OS and languages (Linux, MATlab, Python) Excellent organizational and time management skills. Strong team spirit to ensure optimal interactions with all team scientists. *Comments:* The person will profit from Douglas Research Centre benefits. Applicants are invited to submit their cover letters and resumes via email to: emmanuel.darcq(a)douglas.mcgill.ca We thank all applicants. Only selected candidates will be contacted. ------------------------------------------------------------ ------------------------------- Emmanuel Darcq, PhD Brigitte Kieffer Lab, Douglas Research Centre Dpt Psychiatry, Faculty of Medicine, McGill University Perry room E-3403 6875, boulevard LaSalle Montreal (Quebec) H4H 1R3 CANADA Phone :+1 514 761-6131 ext.: 4772 Avis de confidentialité: L'information contenue dans ce courriel peut être confidentielle et/ou privilégiée. Si vous n’êtes pas le destinataire de ce message, veuillez le détruire et en informer l’expéditeur. Il est interdit de copier ou de modifier ce courriel sans autorisation de l’auteur. Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal n’assume aucune responsabilité du contenu des messages personnels. Notice of confidentiality: The information contained in this email may be confidential and/or privileged. If you are not the intended recipient of this message, please destroy it and advise the sender. It is forbidden to copy or modify this email without the author's consent. The Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal is not responsible for the content of personal messages. -- Md Taufiq Nasseef, PhD Post Doctoral Fellow Brain Imaging Center Douglas Mental Health University Institute McGill University 6875 Lasalle Blvd. Montreal, QC, H4H 1R3 Canada Tel: (514) 862-6907 <%28514%29%20557-2740>

Jan. 4, 2017

Master Internship + PhD at CerCo, Toulouse, France

by Timothée Masquelier

Beating Roger Federer: *Modeling visual learning and expertise through a bioinspired neural network embedded in an electronic device* *Goal:* Internship for student in engineering school / Master degree’s student. The project can lead to a PhD grant. *When:* 5-6 months from February to July 2017 *Topic:* How do expert tennis players, like Roger Federer for example, predict if a ball will bounce in or out the field to decide if it should be played or not? After thousands of trajectory presentations, best champions have developed extraordinary skills in such a task, but little is known on how the visual system turns selective to spatiotemporal properties of the visual stimulus (e.g., 3D position, velocity and acceleration) and learns how to make an efficient use of it. The goal of the project is to build an embedded system – based on FPGA circuits and ARM processor – an artificial neural network which would replicate – and perhaps beat – the visual and anticipatory performances of these expert players. To achieve this goal successfully, we will develop a bio-inspired neural network, based on some of the key properties of human vision: the Smart NeuroCam (GST company) will be used to reproduce the retina functioning. It triggers its message under the form of spikes, in an asynchronous way (without any concept of frame per second), responding to spatial or temporal changes in the pattern of illumination. Several kinds of pre-processing filters can be implemented in VHDL language directly in the FPGA circuits, and the output is then sent to a neural network. The artificial network will learn to use this message, applying a simple learning rule, the Spike-Timing-Dependent Plasticity (STDP). This rule allows each neuron to become selective to a particular property of the stimulus, completely autonomously and with no supervision. Several layers will be built to allow perceiving more and more complex properties of the visual scene. Once the network will be established, its performances will be assessed in different conditions of learning and compared to those of the best tennis players. *The project is funded by a French National Research Agency (ANR)*, involving two sites and several researchers: - Robin Baurès, Benoit Cottereau, Timothée Masquelier and Simon Thorpe, CerCo, Toulouse. - Michel Paindavoine, GST, Dijon. *Where: *The candidate will be based at CerCo, Toulouse (France), and will make the interface with the two sites, with regular trips. The computational neuroscience part will be done at Toulouse, and electronic part at Dijon. *Objectives for the engineering / Master internship:* - Matlab (or Python) based simulations of numerical filters. These filters will be applied to the image processing from which spikes are generated and then sent to feed the neural network and STDP learning mechanism. - VHDL coding to implement these numerical filters into the FPGA circuits of the cameras - C/C++ coding of the neural network and STDP mechanism that should work on an embedded ARM processor system - Experimental tests that will allow evaluating the performance of the whole system, from spikes generation to visual properties learning of the embedded system, to predict tennis ball’s trajectories *Required skills:* - Strong knowledge on electronic, and openness to computational neurosciences - Knowledge in signal-image processing, and artificial neural network - Interest for multidisciplinary research - Ability to turn smoothly autonomous, once the road has been set - Ability to be at the interface of two scientific fields and two working areas - Programming with Matlab and/or Python for simulating the neural network - Programming in VHDL language for FPGA circuits - Programming in C/C++ language for porting the algorithms on ARM microprocessors - French is not a requirement if fluent in English, but willingness to learn would be beneficial *Relevant publications for the project:* - Masquelier, T., Guyonneau, R. & Thorpe S.J. (2009). Competitive STDP-Based Spike Pattern Learning.Neural Comput, 21(5),1259-1276. - Masquelier, T. & Thorpe, S.J. (2007). Unsupervised learning of visual features through spike timing dependent plasticity. PLoS Comput Biol, 3(2):e31. - Cottereau, B.R., McKee, S.P. & Norcia, A.M. (2014). Dynamics and cortical distribution of neural responses to 2D and 3D motion in human. Journal of Neurophysiology 111(3), 533-543. - SmartNeuroCam de GST : https://gsensing.eu/fr/ category/sections/products *Contact:* *Robin Baurès, PhD* Associate Professor CerCo, Université Toulouse 3, CNRS CHU Purpan, Pavillon Baudot 31059 Toulouse Cedex 9 – France Office phone: 0033 (0)5 62 74 62 15 <05%2062%2074%2062%2015> Email : robin.baures(a)cnrs.fr *Pr Michel Paindavoine* GlobalSensing Technologies 14, rue Pierre de Coubertin 21000 Dijon email : michel.paindavoine(a)gsensing.eu

Jan. 4, 2017