October 2015 - Comp-neuro - lists.cnsorg.org

10 Open PhD Positions in Frankfurt, Germany: International Max Planck Research School for Neural Circuits

by Jochen Triesch

Call for Applications IMPRS for Neural Circuits The International Max Planck Research School (IMPRS) for Neural Circuits was funded in 2011 by the Max Planck Society and offers ten positions every year for excellent students holding a relevant Master´s or Bachelor´s degree to perform research resulting in a PhD. The program is taught in English. All positions are completely funded by the school and/or participating Labs. The common focus of the IMPRS for Neural Circuits will be the understanding of neural circuits (from the simple to the large and complex), at all scales required to achieve this understanding. This ambitious objective will require analyses at the molecular, cellular, multi-cellular, network and behavioral levels, with the full understanding that macroscopic phenomena (spatial patterns, dynamics) can be scale-dependent, and that reductionism is not always sufficient as a method. In the IMPRS for Neural Circuits we offer a multidisciplinary program to excellent doctoral students with backgrounds in neuroscience, mathematics, physics, computer science, (bio) chemistry, biology and medicine as well as research experience in the participating institutions of the Frankfurt Neuroscience community (see website for participating Faculty members). Students will participate in a tailor-made educational program including research rotations and neuroscience classes but also in trainings in transferable skills. We welcome excellent students to apply to the program. Till January 15, 2016, it will be possible to apply for a position starting in the Fall of 2015. You can apply via our electronic registration system. After the deadline, the Faculty members will select around 25 students to participate in the interview symposium in Frankfurt (March 2016). Shortly after the symposium, the students will receive a letter with an offer or rejection. More information can be found on our website www.imprs.brain.mpg.de. Please send an email to Dr. Arjan Vink, arjan.vink(a)brain.mpg.de, if you have more specific questions. -- Prof. Dr. Jochen Triesch Johanna Quandt Research Professor Frankfurt Institute for Advanced Studies http://fias.uni-frankfurt.de/~triesch/ Tel: +49 (0)69 798-47531 Fax: +49 (0)69 798-47611

Oct. 25, 2015

[INNS-BigData 2016] Call for Papers

by Teng Teck Hou

[Apologies for cross-postings] ########################################### The INNS Big Data conference 2016 October 23-25, 2016, Thessaloniki, Greece CALL FOR PAPERS ########################################### Homepage: http://www.innsbigdata.org ########################################### Big data is not just about storage of and access to data. Analytics play a big role in making sense of that data and exploiting its value. But learning from big data has become a significant challenge and requires development of new types of algorithms. Most machine learning algorithms can't easily scale up to big data. Plus there are challenges of high-dimensionality, velocity and variety. The neural network field has historically focused on algorithms that learn in an online, incremental mode without requiring in-memory access to huge amounts of data. This type of learning is not only ideal for streaming data (as in the Industrial Internet or the Internet of Things), but could also be used on stored big data. Neural network technologies thus can become significant components of big data analytics platforms and this inaugural INNS Conference on Big Data will begin that collaborative adventure with big data and other learning technologies. Thus the aim of this conference is to promote new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms), implementations on different computing platforms (e.g. neuromorphic, GPUs, clouds, clusters) and applications of Big Data Analytics to solve real-world problems (e.g. weather prediction, transportation, energy management). Awards ########################################################### * Best papers will be selected and awarded as follows: - Best regular paper - Best student paper * This will be based on a combination of reviewers' comments, presentations and importance and quality judged by a panel. * Best paper awards (500 Euros) are donated by the sponsor Springer Verlag, Germany and will be commemorated by a certificate. ########################################################### Important Dates ########################################################### Special Session Proposals February 15, 2016 Tutorials and Workshops Proposals February 15, 2016 Paper Submission March 21, 2016 Paper Decision Notification May 16, 2016 Camera Ready Submission of papers June 13, 2016 ########################################################### Co-Sponsors * International Neural Network Society (INNS) * Springer Plenary Speakers * Francesco Bonchi, Yahoo Research Labs and ISI, Italy * Piotr Mirowski, Google DeepMind, London, UK * Hany Choueri, The Chief Data Scientist, Bank of England, UK (tbc) Advisory Board * Walter Freeman, University of California, Berkeley, USA * Ali Minai, University of Cincinnati, USA * Danil Prokhorov, Toyota Tech Center * Theodore Trafalis, University of Oklahoma, USA * Kumar Venayagamoorthy, Clemson University, USA * Bernard Widrow, Stanford University, USA General Chairs * Plamen Angelov, Lancaster University, UK * Yannis Manolopoulos, Aristotle University, Greece PC Chairs * Lazaros Iliadias, Democritus University, Greece * Asim Roy, Arizona State University, Tempe, USA * Marley Vellasco, PUC-Rio, Rio de Janeiro, Brazil Special Sessions Chairs * Alessandro Ghio, University of Genoa, Italy * Irwin King, Chinese University of Hong Kong, China Tutorials/Workshops Chair * Nikola Kasabov, Auckland Universitty of Technology, New Zealand * Bernardete Ribeiro, University of Coimbra, Portugal Poster Session Chairs * Yi Lu Murphy, University of Michigan-Dearborn, USA * Liang Zhao, University of Sao Paulo, Brazil Awards Chair * Araceli Sanchis de Miguel, Carlos III University, Spain Competitions Chair Adel Alimi, University of Sfax, Tunisia Panel Chair * Leonid Perlovsky, Harvard University, Boston, USA Sponsors/Exhibit Chairs * James Dankert, BAE Systems, USA * Rosemary Paradis, Lockheed Martin, USA Publication Chairs * Danilo Mandic, Imperial College, London, UK * Mariette Awad, American University of Beirut, Lebanon International Liaison * De-Shuang Huang, Tongji University, Shanghai, China * Petia Georgieva, University of Aveiro, Portugal Publicity Chairs, * Teng Teck Hou, Singapore Management University, Singapore * Simone Scardapane, The Sapienza University of Rome, Italy * Jose Antonio Iglesias Martinez, Carlos III University, Spain Paper Submission and Publication ########################################################### * Original works submitted as a regular paper limited to a maximum of 10 pages in Springer format will be published in the proceedings to be available electronically as a Springer book to download for delegates. * It will be peer-reviewed by at least three PC members on the basis of technical quality, relevance, originality, significance and clarity. * At least one author of an accepted submission to the conference should register with a regular fee to present their work at the conference. ########################################################### Topics and Areas include, but not limited to: * Autonomous, online, incremental learning - theory, algorithms and applications in big data * High dimensional data, feature selection, feature transformation - theory, algorithms and applications for big data * Scalable algorithms for big data * Learning algorithms for high-velocity streaming data * Big data streams analytics * Deep neural network learning * Machine vision and big data * Brain-machine interfaces and big data * Cognitive modeling and big data * Embodied robotics and big data * Fuzzy systems and big data * Evolutionary systems and big data * Evolving systems for big data analytics * Neuromorphic hardware for scalable machine learning * Parallel and distributed computing for big data analytics (cloud, map-reduce, etc.) * Big data and collective intelligence/collaborative learning * Big data and hybrid systems * Big data and self-aware systems * Big Data and infrastructure * Big data analytics and healthcare/medical applications * Big data analytics and energy systems/smart grids * Big data analytics and transportation systems * Big data analytics in large sensor networks * Big data and machine learning in computational biology, bioinformatics * Recommendation systems/collaborative filtering for big data * Big data visualization * Online multimedia/ stream/ text analytics * Link and graph mining * Big data and cloud computing, large scale stream processing on the cloud

Oct. 25, 2015

MIT postdoc position in AI/neuroscience/physics

by Max Tegmark

The MIT Physics Department invites applications for a postdoctoral research position to work with Professor Max Tegmark on the physics of cognitive systems, in close collaboration with Tomaso Poggio, Edward Boyden and others associated with the Center for Brains, Minds & Machines (https://cbmm.mit.edu/about/people) Research interests at the interface of theoretical physics, computational neuroscience and artificial intelligence are a strong plus. Candidates interested in exploring ways to test theories with the state-of-the-art data we are measuring here are particularly welcome. Applicants should upload a curriculum vitae, a list of publications, a brief description of research interests and goals at https://academicjobsonline.org/ajo/jobs/6492 and should arrange for three letters of recommendation to be uploaded to this site by December 1, 2015. A Ph.D. in physics or physics-related discipline, such as AI or computational neuroscience, is required by the start of employment. Any inquiries should be sent to tegmark(a)mit.edu. MIT is an Affirmative Action/Equal Opportunity employer committed to diversity and inclusion.

Oct. 25, 2015

NEURAL COMPUTATION - November 1, 2015

by Terry Sejnowski

Neural Computation - Volume 27, Number 11 - November 1, 2015 Available online for download now: http://www.mitpressjournals.org/toc/neco/27/11 ----- Article STICK: Spike Time Interval Computational Kernel, a Framework for General Purpose Computation Using Neurons, Precise Timing, Delays, and Synchrony Xavier Lagorce, Ryad Benosman Letters Visual Decisions in the Presence of Measurement and Stimulus Correlations Manisha Bhardwaj, Samuel Carroll, Wei Ji Ma, and Kresimir Josic Hierarchical Error Representation: A Computational Model of Anterior Cingulate and Dorsolateral Prefrontal Cortex. William H. Alexander, Joshua W Brown Bayesian Feature Selection With Strongly-regularizing Priors Maps to the Ising Model Charles K. Fisher, Pankaj Mehta A Novel Parameter Estimation Method for Boltzmann Machine Takashi Takenouchi Bandit-Based Task Assignment for Heterogeneous Crowdsourcing Hao Zhang, Yao Ma, and Masashi Sugiyama ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp SUBSCRIPTIONS - 2015 - VOLUME 27 - 12 ISSUES Student/Retired $75 Individual $134 Institution $1,075 MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs(a)mit.edu ------------

Oct. 24, 2015

2x Post-Doctoral Positions (Faisal Lab @ Imperial College London)

by Faisal, Aldo A

Dear Colleagues We are looking to hire two 3-year PostDoctoral Research Fellows in the areas of computational neuroscience, eye movements & motor control with the opportunity of translating their basic research into immediately useful clinical applications for movement impaired citizens. The projects focus on two core areas of our lab: 1. action intention decoding from natural eye movements (and translation into control of robotic manipulators with spinal cord injury patients). 2. quantifying natural sensory and movement statistics of humans in daily life using our wearable technology to capture 70% of sensory input and 90% of movement output in people's life. and characterise these in terms of hierarchical structure of behaviour and sparse coding of movement. The ideal backgrounds for these Research Fellowships are computational neuroscience or computational motor control. The hardware and translation aspects for these projects are being custom-developed for the Research Fellows by our industry partners. Similarly, work with patients is supported by our clinical partners. Our Brain & Behaviour Laboratory is truly multi-disciplinary, dynamic and co-located between the Department of Bioengineering and the Department of Computing at Imperial College in the centre of London. Out of 5 post-docs and research fellows we sponsored in the past, 3 are now in faculty (UCL, Imperial) or research group leader positions in industry (Toshiba Research Labs). http://www.jobs.ac.uk/job/AME198/research-associate/ The positions will be advertised till filled. regards Aldo --- Aldo Faisal Director Brain & Behaviour Lab Dept. of Bioengineering & Dept. of Computing Imperial College London and MRC Clinical Sciences Centre London www.FaisalLab.org

Oct. 23, 2015

postdoctoral position (Pillow lab @ Princeton)

by Jonathan Pillow

Postdoctoral position in Statistical & Computational Neuroscience ----------------------------------------------------------------------------------------- A postdoctoral position in computational and statistical neuroscience is available in the lab of Jonathan Pillow at Princeton University. The Pillow lab's research focuses on the statistical modeling of neural data and of information processing in neural populations. Current research projects include: - point process regression models for neural encoding - latent variable models of neural population activity - statistical methods for high-dimensional data (fMRI, spike sorting, Ca-imaging) - active learning methods for adaptive closed-loop experiments - Bayesian models of perception and behavior - models of sensory coding and decision-making The Pillow lab develops statistical models and methods for characterizing statistical structure underlying neural activity. We collaborate closely with a variety of experimental labs in order to use these methods to study information processing in the nervous system. For more information, please visit: http://pillowlab.princeton.edu/ Environment ---------- The Pillow lab is located in the Princeton Neuroscience Institute, and is affiliated with the Center for Statistics and Machine Learning and the department of Psychology. Princeton has a vigorous and rapidly growing neuroscience community, with an energetic mix of junior and senior faculty who use imaging, electrophysiology, genetics, psychology, statistics, and computer science techniques to study the brain. Princeton has excellent programs in engineering, mathematics, machine learning. To Apply -------- Applicants should have a Ph.D. in a quantitative discipline (eg, Neuroscience, Engineering, Computer Science, Statistics, Mathematics, Physics) by the time they start the position. Desired qualifications include familiarity with Bayesian statistical methods and/or probabilistic models of neural data, and experience with programming in Matlab, Python, or other languages. Applicants should have creativity, independence, enthusiasm for research, and a high level of mathematical expertise. Applicants should submit: (1) 1-2 page research statement (2) a current CV (3) the names and contact details of 2-3 references. Inquiries and applications may be addressed by email to Jonathan Pillow ( pillow(a)princeton.edu) Application review will begin November 1 and continue until the position is filled.

Oct. 22, 2015

All-Level Faculty Positions in Interdisciplinary Research in Computer Vision, Neurally-inspired Computing and Data Science

by Ralf Haefner

All-Level Faculty Positions in Interdisciplinary Research in Data Science The University of Rochester has made data science the centerpiece of its 5-year strategic plan, committing to 20 new faculty lines in diverse areas, a new building, and the establishment of the Goergen Institute for Data Science. We are currently seeking applicants for tenure track or tenured positions in interdisciplinary research areas within data science. This search complements department-specific searches in data science currently underway. The interdisciplinary search focuses on recruiting candidates who are excited about engaging in collaborative research that connects advances in computational models and methods to the humanities, sciences, or medicine. Successful candidates will receive a primary appointment in one of the departments supporting the search, and a secondary appointment in at least one other department. Departments and programs supporting this search include Biomedical Engineering, Brain & Cognitive Sciences, Computer and Electrical Engineering, Computer Science, Digital Media Studies (a program of Art & Art History, English, and History), Linguistics, and Political Science. Potential cross-appointments with the School of Medicine and Dentistry will also be considered. Focus areas for this year’s interdisciplinary search are: ● Neurally-inspired Computing: Research in artificial neural networks, including the fundamental theory of deep learning, practical applications to tasks such as perception, or as a tool for modeling and understanding biological neural networks. ● Computer Vision and Image Analysis: Research in the theory and applications of computational methods of image or video understanding, with a particular interest in applications to biomedicine or the humanities. ● Computational Linguistics: Research in the theory or applications of natural language processing, with a particular interest in applications to linguistics, the social sciences, or the humanities. Apply online at: https://www.rochester.edu/faculty-recruiting <https://www.rochester.edu/faculty-recruiting>. Direct questions about the search (but not applications) to michelle.vogl(a)rochester.edu <mailto:michelle.vogl@rochester.edu>. For more information about the Goergen Institute for Data Science, visit http://www.rochester.edu/data-science <http://www.rochester.edu/data-science>. Applicants should hold a PhD and will be required to supply a set of refereed scholarly publications, names of references, and research and teaching statements. The application will ask applicants to select a set of disciplines most relevant to their research area. Review of applications at any rank will begin immediately and continue until the positions are filled. For full consideration, applications should be completed by January 15th, 2016. The University of Rochester is a private, Tier I research institution located in western New York State. It consistently ranks among the top 30 institutions, both public and private, in federal funding for research and development. The university has made substantial investments in computing infrastructure through the Center for Integrated Research Computing (CIRC) and the Health Sciences Center for Computational Innovation (HSCCI). The university includes the Eastman School of Music and the University of Rochester Medical Center, a major medical school, research center, and hospital system. The greater Rochester area is home to over a million people, including 80,000 students who attend the 8 colleges and universities in the region. The University of Rochester has a strong commitment to diversity and actively encourages applications from candidates from groups underrepresented in higher education. The University is an Equal Opportunity Employer.

Oct. 21, 2015

Post-Doctoral position in brain imaging – University of Geneva

by Narly Golestani

Applications are invited for a Post-Doctoral position in the Brain and Language Lab (www.brainandlanguagelab.org<http://www.brainandlanguagelab.org/>) at the University of Geneva. The position is for 2 years (or more), and will be at the new Biotech Campus (http://www.campusbiotech.ch/en/) Candidates should have a degree in Cognitive Neuroscience, Biomedical Engineering, Computational Neuroscience or a related field, and should have solid experience in brain imaging data analysis, computational modelling, pattern recognition, machine learning, statistics and programming. The projects will involve the use and development of computational morphometry and of computational modeling to study auditory cortex structure and function in healthy individuals, in experts and in individuals with dyslexia. The salary is competitive, starting salary at ~ 69, 000 CHF/year (~81, 000 CHF/year as of August 2016) depending on experience. The position is available immediately, and applications will be considered until the position is filled. Informal inquiries can be addressed to Narly Golestani (Narly.Golestani(a)unige.ch) Applications including a CV, a statement of research interests, and the names and full contact details of three referees should be sent to: Narly.Golestani(a)unige.ch<mailto:Narly.Golestani@unige.ch>.

Oct. 21, 2015

Faculty position in Cognitive Science/Computational Modelling - University of Sheffield

by Tom Stafford

*Chair/Reader/Senior Lecturer or Lecturer in Cognitive Science/Computational Modelling * Department of Psychology, University of Sheffield, UK Closing Date *24th November 2015* The Department of Psychology is looking for an outstanding scholar (at any level of seniority) in the area of Cognitive Science and Computational Modelling, to enhance its world-leading research portfolio in cognitive, computational and systems neuroscience and in brain-based robotics and its emerging activities in high volume data processing, online behavioural measurement, and virtual and mixed-reality systems. You should have a PhD (or equivalent qualification) in a relevant discipline, have an excellent publication record for your career stage/level and be able to evidence of the ability or potential to attract independent research funding. The ability to organize and carry out teaching, supervision and research training to a high standard is also essential. You will join a vibrant department, which is amongst the largest in the UK, which importantly has been consistently ranked as one of the outstanding research departments in all seven UK Research Assessment Exercises to date. We have one of the largest centres of postgraduate psychology research in the country and were ranked 7th in the UK for research income in the ESRC’s 2011 Psychology International Benchmarking exercise. The post is available from 1 April 2016. *For* further details visit: http://www.sheffield.ac.uk/jobs Job reference: UOS011888 For informal enquiries please contact Tony Prescott <https://www.sheffield.ac.uk/psychology/staff/academic/tony-prescott> ( t.j.prescott(a)sheffield.ac.uk) or Paul Overton <https://www.shef.ac.uk/psychology/staff/academic/paul-overton1> ( p.g.overton(a)sheffield.ac.uk) *About the University* Sheffield University <http://www.shef.ac.uk> is a World Top 100 University and home to 25,000 of the brightest students in the world. Twenty-four per cent of our students come from outside the UK. Our graduates and former staff include five Nobel Prize winners, an Olympic gold medallist and Britain’s first female astronaut. The Department of Psychology <http://www.sheffield.ac.uk/psychology/> at Sheffield is among the largest in the UK and has been consistently ranked as one of the outstanding research departments in all seven UK Research Assessment Exercises to date. For example, over 80% of our department’s research was classed as internationally excellent or world leading in the 2014 Research Excellent Framework (REF). The Department occupies a purpose-built 5-floor building (with annexes), which is being fully refurbished next year following considerable capital investment (~£10M) by the University. Facilities include a child development laboratory, high-density ERP and EEG (128 electrode) systems, and a virtual reality suite. The Department also occupies modern office and laboratory facilities at (i) the University's central neuroscience facility, which is fully equipped for state-of-the-art in vivo and in vitro neuroscience and behavioural testing, and includes a small-bore 7T fMRI facility; and (ii) Sheffield Robotics <http://www.sheffieldrobotics.ac.uk>, an interdisciplinary research institute equipped with an engineering workshop, robot platforms including the iCub humanoid, a human-robot interaction laboratory, and a motion capture suite. Across the University the department also actively participates in Insigneo <http://insigneo.org>, the Institute for in Silico Medicine, through its activities in digital organism models; and in the Centre for Assistive Technology and Connected Healthcare <http://www.catch.org.uk> (CATCH) through collaborative research on assistive technologies including companion robots. -- Tom Stafford http://www.tomstafford.staff.shef.ac.uk/ Lecturer in Psychology and Cognitive Science Department of Psychology, University of Sheffield Western Bank, Sheffield, S10 2TP, UK Room 2.24 Tel +44 (0) 114 22 26620 t.stafford(a)shef.ac.uk Office Hour: Thursdays 2pm-3pm during Semester (except reading week) NOTES FOR UNDERGRADUATE STUDENTS: please read this before emailing me http://tomstafford.staff.shef.ac.uk/email.htm ---------------------------------------------------------------

Oct. 21, 2015

Postdoctoral positions at the interface of algebraic topology and theoretical neuroscience at Penn State.

by Vladimir Itskov

Applicants are invited for postdoctoral positions at the interface of theoretical neuroscience and algebraic topology or applied algebra. An ideal candidate is a mathematics Ph.D. with background in areas such as algebraic topology, geometry, commutative algebra, or combinatorics. Prior familiarity with neuroscience is not required, but interest in learning the relevant background is expected. The postdoctoral fellow will engage in the development of novel mathematical methods for understanding neural coding and neural networks. To apply for this position, please submit your application via the mathjobs.org website in response to the job ad http://www.mathjobs.org/jobs/jobs/7575 The closing date for applications is November 15, 2015. See also http://sites.psu.edu/mathneurolab/ for more information.

Oct. 20, 2015