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Fully funded PhD position in Neural Learning / Robotics / Evolutionary Neural Networks
by Andrea Soltoggio June 25, 2015

June 25, 2015

A fully funded PhD position is available at the Deep Automation, Learning and Evolution Lab at Loughborough University, UK, on the topics of Neural Learning / Robotics / Evolutionary Neural Networks. Loughborough University is ranked 11th in the 2016 UK League Table Ranking (http://www.thecompleteuniversityguide.co.uk/loughborough/performance , and is located in Loughborough, a town well connected to London by a 1h20m journey by train. Research. The focus is on developing new neural learning algorithms with possible applications to a variety of automation and machine learning problems, e.g. vision, robotics, autonomous vehicles, manufacturing technology. We seek an outstanding candidate, capable of defining their own research project and bringing novel ideas and initiatives to the lab. Working environment. The student, based at the Computer Science Department, School of Science, will have access to a number of robotic platforms, from humanoid robots, to UAVs and a number of industrial and service robots, as well as a High Performance Computing cluster and GPUs. Interdisciplinary research is encouraged across laboratories, including Aeronautical and Automotive Engineering, the Intelligent Automation Lab, and the Centre for Information Management. The research group collaborates with leading national and international industrial partners. Requirements. The ideal candidate holds (or is about to obtain) a first-class honour undergraduate/postgraduate degree (or equivalent) in Computer Science, Mathematics, Statistics, Electrical or Electronic Engineering, or has authored publications in recognised conferences/journals. Independent working skills are valued as well as the capability of working in a team. Collegiality and interpersonal skills are essential. Excellent English language skills are highly desired (see requirements here http://www.lboro.ac.uk/international/englang/index.htm) Period/Scholarship. Start: October 2015. Duration: 3 years. Scholarship: £14,057 per annum plus tuition fees at the UK/EU rate (currently £4,052 p.a.) Enquiries and applications. Interested candidates are invited to establish a preliminary contact with me (a.soltoggio(a)lboro.ac.uk<mailto:a.soltoggio@lboro.ac.uk>), possibly including a CV, the names and addresses of two referees, and a statement of research interest (maximum 300 words), before submitting the full application at http://www.lboro.ac.uk/study/apply/research/ Best regards, Andrea Soltoggio -- Dr. Andrea Soltoggio Lecturer in Artificial Intelligence Department of Computer Science and Centre for Information Management (CIM) School of Business and Economics Haslegrave Building, N.2.03 Loughborough University LE11 3TU, UK Phone: +44 (0) 1509 635748<tel:%2B44%20%280%29%201509%20635748> Email: a.soltoggio(a)lboro.ac.uk<mailto:a.soltoggio@lboro.ac.uk> Web: http://www.lboro.ac.uk/departments/compsci/staff/dr-andrea-soltoggio.html

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Job: Post-doctoral Scientist - Investigating the Feasibility of Controlling Hearing-aid Directionality Using In-Ear Electrodes to Measure Eye Position.
by Bernd Porr June 25, 2015

June 25, 2015

Dear all, this is something for somebody who has a strong background in signal processing / biomed signal processing. If interested please contact Owen Brimijoin <owen(a)ihr.gla.ac.uk>. Best /Bernd Porr -------------------------------------------------------------------- Salary: £27,084 – 29,567 Grade: MRC - 4a Contract Type: Fixed Term, 24 months Hours: Full Time Closing Date:31 July 2015 Interview Date: 26 August 2015 The successful applicant will be based at the MRC/CSO Institute of Hearing Research (IHR) in Glasgow within the Auditory Disability and Impairment group headed by Dr William Whitmer. The successful applicant will join a small group of researchers but will work most closely with Drs Owen Brimijoin (IHR), Bernd Porr (Glasgow Uni), and Graham Naylor (Oticon) on a project investigating the feasibility of using in-ear measurements of eye position to guide hearing aid directionality. The project will use electrooculograms (EOG), optical eye and head tracking, digital signal processing, microphone arrays, as well as our extensive audiological and auditory testing facilities. Your work will consist of writing signal-processing algorithms to combine the output of an EOG amplifier, gyroscopes, and other extra-cochlear signals to yield a reliable measure of eye position that can be used to aim the directional beam of an experimental hearing aid. The work will continue with implementing these algorithms in Matlab and/or C, designing experiments to test benefit, statistical analysis of results, and delivery of these results for dissemination (conference abstracts and presentations, invited lectures and seminars, and published manuscripts in specialized and generic journals). -- http://www.berndporr.me.uk http://www.linux-usb-daq.co.uk http://www.imdb.com/name/nm3293421/ +44 (0)7840 340069

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Deep Learning and Continuous Time Computing - Track at SAC 2016 - Call for Papers
by Davide Zambrano June 24, 2015

June 24, 2015

Dear all, Please consider joining our track at SAC2016. Apologies for cross posting. Best regards. ————————————————————————————————————— ACM Symposium on Applied Computing (SAC) 2016 The 31st Annual ACM Symposium on Applied Computing in Pisa, Italy, April 3 – 8, 2016. (webpage : http://www.acm.org/conferences/sac/sac2016/) Deep Learning and Continuous-Time Computing (webpage : http://event.cwi.nl/sac2016/) ————————————————————————————————————— SAC 2016: For the past thirsty years, the ACM Symposium on Applied Computing has been a primary gathering forum for applied computer scientists, computer engineers, software engineers, and application developers from around the world. SAC 2016 is sponsored by the ACM Special Interest Group on Applied Computing (SIGAPP), and will be hosted by the University of Pisa and Scuola Superiore Sant’Anna University, Italy. Artificial Intelligence (AI) is one of the objectives of Machine Learning: how to create computers capable of intelligent behavior. Deep Learning in artificial neural networks represents a remarkable step toward this direction. Current state-of-the-art AI in the form of deep neural networks has recently demonstrated breakthrough performance in various AI-cognitive tasks, from image and speech recognition to natural language generation and playing ATARI games. However, in real-world applications like video processing or robot control, a deep neural network has then to be updated continuously, causing a high computational load. Specialized acceleration hardware is being developed for deep learning in continuous-time environments. In addition, or alternatively, Spiking Neural Networks (SNNs) represent another possible solution for efficient continuous-time representation and computing in deep neural networks. This Track aims to consolidate the current state-of-the-art in deep learning, continuous-time computing, spiking neural networks and related acceleration hardware tools (such as GPUs, SpiNNaker or Neuromorphic Silicon systems) showing recent and future progresses of this rising and growing research field. ————————————————————————————————————— Topics of interests: Deep learning Continuous-time learning Spiking Neural Networks Asynchronous computation Large scale parallel simulations and computing Neuromorphic computing ————————————————————————————————————— Important Dates are published on the Conference or Track webpages. ————————————————————————————————————— Track Program Committee: Sander Bohte, CWI Amsterdam (NL) (Track Chair — email to s.m.bohte(a)cwi.nl ) Davide Zambrano, CWI Amsterdam (NL) (Track Chair — email to d.zambrano(a)cwi.nl ) Thomas Nowotny, University of Sussex (UK) Steven Furber, University of Manchester (UK) Karl Tuyls, University of Liverpool (UK) Shih-Chii Liu, University of Zurich/ETH Zurich (CH) Robert Babuska, Delft University of Technology (NL) Andre Gruning, University of Surrey (UK) Max Welling, University of Amsterdam (NL) Narayan Srinavasa, HRL Laboratories LLC (USA) Eleni Vasilaki, University of Sheffield (UK) ————————————————————————————————————— Important notice: Paper registration is required, allowing the inclusion of the paper, poster, or SRC abstract in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for including the work in the ACM/IEEE digital library. No-show of registered papers, posters, and SRC abstracts will result in excluding them from the ACM/IEEE digital library. ————————————————————————————————————— Dr. Davide Zambrano PostDoc at CWI, Amsterdam (NL) MSc in Biomedical Eng. - PhD in Biorobotics D.Zambrano(a)cwi.nl Centrum Wiskunde & Informatica (CWI) Science Park, 123 1098 XG - Amsterdam

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Gordon Research Conference on Eye Movements
by Emilio Salinas June 24, 2015

June 24, 2015

Readers of this list may be interested in the upcoming Gordon Research Conference on Eye Movements. This year's theme, "Integrating Perception and Action for Optimal Vision", promises to provide fresh perspectives on core oculomotor issues. The meeting is meant as an immersive experience in which participants share ideas over meals and jointly participate in scheduled and unscheduled social activities. The format provides unparalleled opportunity for participants at all career stages to share their most novel findings, foster new collaborative efforts, and chart the future directions of oculomotor research. WHAT: Call for applications for the 2015 Gordon Research Conference on Eye Movements (main meeting) and Gordon Research Seminar on Eye Movements (1-day forum for students and postdocs) DEADLINE FOR APPLICATIONS: June 28th WHEN: July 26-31 (GRC), July 25-26 (GRS) WHERE: Bentley University, Waltham MA (just outside of Boston) HOW: Apply online - GRC application; GRS application DETAILS: http://www.grc.org/programs.aspx?id=14523 Emilio Salinas, on behalf of Terry Stanford & John Van Opstal (GRC Chairs) Doug Crawford & Marc Sommer (GRC Vice-chairs) Jaime Kaminer and Martin Bohlen (GRS Chairs)

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Rapid image categorization via edge co-occurrences
by James A. Bednar June 23, 2015

June 23, 2015

We are pleased to announce the publication of an open-access paper demonstrating a novel method for categorizing images using the statistics of their edge co-occurrences. The success of this low-level method in matching both correct and incorrect classifications by humans suggests a reinterpretation of longstanding claims for rapid hierarchical processing in the visual cortex. Laurent U. Perrinet Institut de Neurosciences de la Timone Aix Marseille Universite, CNRS James A. Bednar Institute for Adaptive and Neural Computation University of Edinburgh _______________________________________________________________________________ Laurent U. Perrinet and James A. Bednar. Edge co-occurrences can account for rapid categorization of natural versus animal images. Scientific Reports, Nature Publishing Group, 5:11400, 2015. http://dx.doi.org/10.1038/srep11400 Abstract: Making a judgment about the semantic category of a visual scene, such as whether it contains an animal, is typically assumed to involve high-level associative brain areas. Previous explanations require progressively analyzing the scene hierarchically at increasing levels of abstraction, from edge extraction to mid-level object recognition and then object categorization. Here we show that the statistics of edge co-occurrences alone are sufficient to perform a rough yet robust (translation, scale, and rotation invariant) scene categorization. We first extracted the edges from images using a scale-space analysis coupled with a sparse coding algorithm. We then computed association for different categories (natural, man-made, or containing an animal) by computing the statistics of edge co-occurrences. These differed strongly, with animal images having more curved configurations. We show that this geometry alone is sufficient for categorization, and that the pattern of errors made by humans is consistent with this procedure. Because these statistics could be measured as early as the primary visual cortex, the results challenge widely held assumptions about the flow of computations in the visual system. The results also suggest new algorithms for image classification and signal processing that exploit correlations between low-level structure and the underlying semantic category. -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

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POSTDOCTORAL RESEARCHER IN SYSTEMS NEUROSCIENCE
by Santamaria, Cookie June 22, 2015

June 22, 2015

POSTDOCTORAL RESEARCHER IN SYSTEMS NEUROSCIENCE The BioCircuits Institute (BCI) and Departments of Physics, Chemistry/Biochemistry, Bioengineering, and Psychology and Neurobiology at the University of California, San Diego invite applications for a postdoctoral position in systems neuroscience, for experiments leading to the neuromorphic engineering of cognitive abilities. The ideal candidate will have experience with electrophysiology, with awake behaving animals, with neural modeling, and/or with biologically inspired integrated circuits and systems. Close interaction with other project researchers in computational and theoretical neuroscience, nonlinear dynamical systems, and neuromorphic engineering is involved. We will accept applications immediately. To be considered, please submit your complete application by Friday, 31 July 2015. We will begin making selections from the completed applications on 3 August 2015. The Committee will continue to accept and review completed applications as they are received until the position is filled. Appointments are for two years (in one-year increments) with the possibility of a third. Send your statement of qualifications and interest with curriculum vitae, your two most significant publications and three letters of reference to Tim Gentner, Henry Abarbanel, Gert Cauwenberghs, Katja Lindenberg, Mikhail Rabinovich, and Terrence Sejnowski via email to: <postdoc.muri(a)gmail.com<mailto:postdoc.muri@gmail.com>>. A Ph.D. or equivalent doctoral degree is required prior to the appointment. UCSD is an EO/AA employer.

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Development of model description languages
by Erik De Schutter June 22, 2015

June 22, 2015

Postdoctoral researcher and staff scientist positions are available in the Computational Neuroscience Unit (https://groups.oist.jp/cnu) of Prof. Erik De Schutter at the Okinawa Institute of Science and Technology Graduate University. We are looking for a postdoc with a computer science or engineering background who is interested in the development of XML-based methods for model description and simulation. You will collaborate with international colleagues on further development of NIneML (http://nineml.net) and deploy it within the research group. Previous experience related to collaborative projects in computational neuroscience or systems biology preferred. You will interact with other researchers and students in the lab who are working on cerebellar modeling projects or analyzing cerebellar recordings. We offer attractive financial and working conditions in an English language graduate university that emphasizes interdisciplinary research, located on the beautiful subtropical island Okinawa. Send curriculum vitae, a summary of research interests and experience, and the names of three referees to Prof. Erik De Schutter at erik(a)oist.jp

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SPIKY and PySpike – Two free software packages for monitoring spike train synchrony
by Thomas Kreuz June 21, 2015

June 21, 2015

Dear all, we would like to draw your attention to our two most recent papers and to two new software packages. *1. Two new papers:* This paper provides a detailed description of *SPIKY* (see 2.) and introduces our new measure *SPIKE-synchronization*: • Kreuz T, Mulansky M, Bozanic N: SPIKY: A graphical user interface for monitoring spike train synchrony. JNeurophysiol <http://jn.physiology.org/content/113/9/3432> 113, 3432 (2015) [PDF] <http://www.fi.isc.cnr.it/users/thomas.kreuz/images/Kreuz_JNeurophysiol_2015…>. An overview of all three of our measures (*ISI-distance, SPIKE-distance and SPIKE-synchronization*) and their mathematical properties can be found in • Mulansky M, Bozanic N, Sburlea A, Kreuz T: A guide to time-resolved and parameter-free measures of spike train synchrony. IEEE Proceedings (in press) and arXiv [PDF] <http://arxiv.org/pdf/1502.02027v2.pdf> (2015). *2. SPIKY, graphical user interface (Matlab) for monitoring spike train synchrony* Implementations of ISI-distance, SPIKE-distance, and SPIKE-Synchronization Distances, time profiles, distance matrices, selective averaging, triggered averages, dendrograms, etc. Plotting, movie generation Spike train generator, event detector (for continuous data such as EEG) Matlab with C backend (MEX) Matlab fallback if no MEX-compiler is not available Extensive documentation includes many illustrative movies Matlab source codes and all relevant papers are available on our *SPIKY download page* http://www.fi.isc.cnr.it/users/thomas.kreuz/Source-Code/SPIKY.html For further information about new features and updates please check the *SPIKY Facebook page* https://www.facebook.com/SPIKYgui Here you'll also find a lot of documentation including many images and movies that illustrate how to use SPIKY. All of these movies can also be found on the *SPIKY Youtube channel* https://www.youtube.com/user/SPIKYgui1 *3. PySpike, open source Python library hosted on github* Implementations of ISI-distance, SPIKE-distance, and SPIKE-Synchronization Library of functions to compute distances and profiles (bivariate and multivariate), distance matrices, selective averages, etc. Helper functions for plotting, spike train generation Cython backend for optimal performance (factor 100-200 over plain Python) Python fallback if Cython is not available Extensive unit-tests that cover the API as well as the numerics Automatic build and test runs Documentation The github issues system can be used to file bug reports or request new functionality and features. *PySpike webpage* http://www.pyspike.de *PySpike github page* https://github.com/mariomulansky/PySpike Any feedback on both the papers and the software packages is very welcome. Best wishes, Thomas Kreuz -- Institute for complex systems, CNR Via Madonna del Piano 10 50119 Sesto Fiorentino (Italy) Tel: +39-349-0748506 Email: thomas.kreuz(a)cnr.it Webpage: http://www.fi.isc.cnr.it/users/thomas.kreuz/

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Research Associate Position in Computational Neural Modeling (Duke University)
by Angel V. Peterchev June 21, 2015

June 21, 2015

RESEARCH ASSOCIATE in COMPUTATIONAL NEURAL MODELING DUKE UNIVERSITY Department of Biomedical Engineering and Department of Psychiatry & Behavioral Sciences An opportunity exists to join a research team working to understand and advance transcranial magnetic stimulation (TMS). TMS is a non-invasive form of brain stimulation used widely as a neuroscience research tool as well as a treatment for psychiatric and neurological disorders (FDA approved for depression since 2008). We have an ongoing NIH-funded project that combines computational modeling at several scales with single neuron recordings in pre-clinical models. We seek a highly-motivated individual who is interested in developing and applying computational models of TMS. The parallel experimental component of the study provides unique opportunities to validate and calibrate computational models. This is a full-time position with University Benefits and provides exceptional opportunities for interdisciplinary research and career development. This position will be jointly mentored by Angel V. Peterchev, PhD<https://sites.google.com/site/dukebrainstimulation/> (Department of Psychiatry & Behavioral Sciences, School of Medicine) and Warren M. Grill, PhD<http://www.bme.duke.edu/faculty/warren-grill> (Department of Biomedical Engineering, Pratt School of Engineering), providing exposure to both clinical and engineering research settings. A PhD in biomedical engineering, electrical engineering, neuroscience, physics, or math is required, as are excellent communication skills. Previous experience in computational neural modeling is required, and previous experience with neural stimulation is desirable. For consideration submit a CV and the names and contact information of three professional references as a .pdf file attachment to: Angel V. Peterchev, PhD Assistant Professor of Psychiatry & Behavioral Sciences, Biomedical Engineering, and Electrical & Computer Engineering angel.peterchev(a)duke.edu<mailto:angel.peterchev@duke.edu> Duke University is an equal opportunity / affirmative action employer.

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Congratulations to the Winners of the 2015 Best Illusion of the Year Contest!
by Susana Martinez-Conde June 19, 2015

June 19, 2015

Congratulations to the winners of the 11th annual Best Illusion of the Year Contest <http://illusionoftheyear.com/> ! Online voters around the world chose the best illusions of the year from Thursday, June 11th 7pm EST to Friday, June 12th 7PM EST. First Place and an award of $3,000 USD went to "Splitting Colors <http://illusionoftheyear.com/2015/splitting-colors/> ," a color illusion by Mark Vergeer from KU Leuven, Belgium. Second Place and an award of $2,000 USD went to "Ambiguous Garage Roof <http://illusionoftheyear.com/2015/ambiguous-garage-roof/> ," a perspective illusion by Kokichi Sugihara from Meiji University, Japan. Third Place and an award of $1,000 USD went to "The Day it Rained on Lowry <http://illusionoftheyear.com/2015/the-day-it-rained-on-lowry/> ," a motion illusion by Michael Pickard from VisuallyDirectedDesign.com in the UK. Enjoy the winning illusions and all Top 10 Finalists <http://illusionoftheyear.com/cat/top-10-finalists/2015/> at http://illusionoftheyear.com Illusion submissions <http://illusionoftheyear.com/about-the-contest/submission-instructions/> are now accepted for the 12th edition of the Best Illusion of the Year Contest, to be held in 2016. On behalf of the Executive Board of the Neural Correlate Society: Jose-Manuel Alonso, Stephen Macknik, Susana Martinez-Conde, Luis Martinez, Xoana Troncoso, Peter Tse The Neural Correlate Society is a tax-exempt 501(c)3 non-profit organization, whose mission is to promote the public awareness of neuroscience research. ----------------------------------- Susana Martinez-Conde, PhD Professor of Ophthalmology, Neurology, and Physiology & Pharmacology Director, Laboratory of Integrative Neuroscience Scholar, Empire Innovator Program State University of New York (SUNY) Downstate Medical Center 450 Clarkson Ave, Brooklyn NY 11203, USA Email: <mailto:smart@neuralcorrelate.com> smart(a)neuralcorrelate.com Phone: +1 718-270-4520 <http://smc.neuralcorrelate.com/> http://smc.neuralcorrelate.com

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