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Comp-neuro: Postdoc/Assistant Professor & visiting professor positions
by Maro Machizawa Oct. 27, 2015

Oct. 27, 2015

Dear potential applicants on the Comp-neuro mailing list, Please see below for an announcement for: A position of postdoc/assistant professor (research) and visiting opportunities for associate/full professors at the Center for KANSEI Innovation at Hiroshima University, Japan. Looking forward to hearing from motivated candidates. Best Wishes, --- The Center for KANSEI Innovation, newly launched in 2013 at the Hiroshima University (one of top ten Japanese universities), is seeking computational/mathematical neuroscientists from overseas. Under the new, exciting scheme of government-funded project, COI STREAM, our mission is to innovate research developments foreseeing 10 years in the future. The center’s mission is to drive radical innovation on KANSEI— a Japanese term corresponding to emergent properties of our feelings, sensations, or emotions that are expressed and embedded in our complex neural and physiological responses. One of our primary missions is to create brain emotion interfaces, which is to bridge mental gaps amongst people, enriching our mental quality of life. The center is fully equipped with our own MRI scanner (Siemens Verio 3T) with EEG, eye-tracker, TMS, and tACS/tDCS facilities, as well as several physiological-measurement equipments, plus a shared access to an MEG facility. Full-time research lecturer (assistant professor)/Postdoc: The successful candidate for the full-time positions has expertise in mathematical models on data collected from multimodal environment (i.e., fMRI and EEG as well as various physiological responses). Expertise in machine learning, computational engineering, and/or brain computer interface is necessary. High interpersonal skills are expected as well to interact with a large group of talented, interdisciplinary colleagues from universities and industries with various backgrounds in a friendly, open-minded environment. Contract will be updated annually. The position is available now. Visiting professor (on sabbatical): We are also seeking visiting professors on a sabbatical with background including but not limited to computational/mathematical neurosciences. Expertise in other fields related to neuroscience and engineering are welcome. A period to visit is negotiable, but until year 2020. For both positions, salaries are depending on your experiences and a regulation set by the Hiroshima University Faculty Members employed under annual salary system. About Hiroshima: The center is located at the heart of a beautiful city of Hiroshima, which is the biggest city around the Chugoku region on the main island in Japan. Hiroshima is well known for its fruitful resources for activities, nature, and high-quality cuisines. Our website: http://coikansei.hiroshima-u.ac.jp/en/ For more details, or to apply (with your CV), send an email to: recruit(a)coikansei.hiroshima-u.ac.jp --- Maro Machizawa, PhD (Neurology) Assistant Professor Dept. Psychiatry & Neurosciences Center for KANSEI Innovation TEL: +81(0)82-257-1722; FAX: +81(0)82-257-1723

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CfP: ICLR 2016 - Conference Track (updated)
by Hugo Larochelle Oct. 26, 2015

Oct. 26, 2015

Update: Submissions and the review process, with a single round of reviewing, will again this year be supported by CMT rather than OpenReview.net<http://OpenReview.net>. We hope to use OpenReview.net<http://OpenReview.net> in the near future. ------------------------------------------------------------------- 4th International Conference on Learning Representations (ICLR 2016) ------------------------------------------------------------------- Website: http://www.iclr.cc/ Submission deadline for title and abstract: November 12th, 2:00pm Pacific Standard Time, 2015 Submission deadline for arXiv paper ID: November 19th, 2:00pm Pacific Standard Time, 2015 Location: Caribe Hilton, San Juan, Puerto Rico, May 2-4, 2016 Overview -------- It is well understood that the performance of machine learning methods is heavily dependent on the choice of data representation (or features) on which they are applied. The rapidly developing field of representation learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. We take a broad view of the field, and include in it topics such as deep learning and feature learning, metric learning, kernel learning, compositional models, non-linear structured prediction, and issues regarding non-convex optimization. Despite the importance of representation learning to machine learning and to application areas such as vision, speech, audio and NLP, there was no venue for researchers who share a common interest in this topic. The goal of ICLR has been to help fill this void. A non-exhaustive list of relevant topics: - unsupervised, semi-supervised, and supervised representation learning - metric learning and kernel learning - dimensionality expansion - sparse modeling - hierarchical models - optimization for representation learning - learning representations of outputs or states - implementation issues, parallelization, software platforms, hardware - applications in vision, audio, speech, natural language processing, robotics, neuroscience, or any other field The program will include keynote presentations from invited speakers, oral presentations, and posters. As usual, ICLR will feature two tracks: a Conference Track and a Workshop Track. However, this year, conference and workshop submissions will be reviewed separately, in two different periods. This call for paper is thus only for conference contributions. Workshop submissions will be received a few months before the conference and be subject to a lighter review. A future call for papers will be sent with more details on the Workshop Track. Note that some of the submitted papers that are not accepted to the Conference Track will be invited to be presented under the Workshop Track. ICLR Submission Instructions ---------------------------- 1. By November 12th (2:00pm Pacific Standard Time) authors are asked to submit through CMT the title, abstract, author list, subject areas and a draft of their paper: https://cmt.research.microsoft.com/ICLR2016Conference/ 2. Then, as soon as possible, authors must post on arXiv their submission: http://arxiv.org<http://arxiv.org/> . 3. Finally, by November 19th (2:00pm Pacific Standard Time), authors must update their submission in CMT with the arXiv ID of their finalized paper. They must also update their PDF submission within CMT. Note that there can be up to 3 days of delay between sending a manuscript on arXiv and receiving your arXiv ID. It is thus important to post your submission on arXiv early. Note also that you can always update your submission on arXiv later on. Submissions without an arXiv ID after November 19th will be automatically removed from CMT. For more information on paper preparation, including the mandatory style files, please see http://www.iclr.cc/ . Submission deadline: November 12th (2:00pm Pacific Standard Time) for title, abstract and preliminary draft, November 19th (2:00pm Pacific Standard Time) for arXiv ID and final submission PDF. Notes: i. Regarding the conference submission's 6-9 page limits, these are really meant as guidelines and will not be strictly enforced. For example, figures should not be shrunk to illegible size to fit within the page limit. However, in order to ensure a reasonable workload for our reviewers, papers that go beyond the 9 pages should be formatted to include a 9 page submission, with supplementary material appended at the end of the manuscript and clearly marked as an appendix, which will be optionally reviewed. ii. Paper revisions will be permitted, and in fact are encouraged, in response to comments from and discussions with the reviewers (see "An Open Reviewing Paradigm" below). An Open Reviewing Paradigm -------------------------- 1. Submissions to ICLR are posted on arXiv prior to being submitted to the conference. 2. Authors submit their paper to the ICLR conference track via the CMT ICLR 2016 conference track website. 3. After the authors have submitted their papers via CMT, the ICLR program committee designates anonymous reviewers as usual. 4. The submitted reviews are published without the name of the reviewer, but with an indication that they are the designated reviews. 5. Anyone can openly (non-anonymously) write and publish comments on the paper. Anyone can ask the program chairs for permission to become an anonymous designated reviewer (open bidding). The program chairs have ultimate control over the publication of each anonymous review. Open commenters will have to use their real names. 6. Authors can post comments in response to reviews and comments. They can revise the paper as many times as they want, possibly citing some of the reviews. Reviewers are expected to revise their reviews in light of paper revisions. 7. The review calendar includes a generous amount of time for discussion between the authors, anonymous reviewers, and open commentators. The goal is to improve the quality of the final submissions. 8. The ICLR program and area chairs will consider all submitted papers, comments, and reviews and will decide which papers are to be presented in the conference track, which will be invited to be presented in the workshop track, and which will not appear at ICLR. 9. Papers that are presented in the workshop track or are not accepted will be considered non-archival, and may be submitted elsewhere (modified or not), although the ICLR site will maintain the reviews, the comments, and the links to the arXiv versions. Organizers ---------- Yoshua Bengio, Université de Montreal, General Chair Yann LeCun, New York University and Facebook, General Chair Hugo Larochelle, Twitter and Université de Sherbrooke, Senior Program Chair Brian Kingsbury, IBM Watson Group, Program Chair Samy Bengio, Google, Program Chair Contact ------- The organizers can be contacted at iclr2016.programchairs(a)gmail.com<mailto:iclr2016.programchairs@gmail.com>

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PDF Job: Computational Modeling of Neural Population Dynamics
by Andrew Pruszynski Oct. 26, 2015

Oct. 26, 2015

Postdoctoral Fellow: Computational Modeling of Neural Population Dynamics We are looking for one full-time postdoctoral fellow for a collaborative project between Dr. Andrew Pruszynski, Dr. Jörn Diedrichsen and Dr. Martinez-Trujillo. This position offers the unique opportunity to analyze and model data from both multi-unit electrophysiological recordings and high-resolution functional imaging studies. The project is primarily computational in nature, involving multivariate analysis and modeling of large-scale neural networks during sensory-motor, decision, and navigation tasks. Our labs use a broad range of methods, including single-unit and multi-unit recordings, behavioural experiments, high-resolution functional imaging at 7T, and computational modelling. Applicants must have a strong mathematical and/or technical background and should have previous publications in computational neuroscience broadly defined. Our laboratories are located at the Brain and Mind Institute and Robarts Research Institute, both at Western University in London, Ontario, Canada. Systems and cognitive neuroscience are key areas of research strength at Western University with more than 25 Principal Investigators and nearly 200 trainees. A PhD degree in neuroscience, psychology, computer science, engineering, kinesiology, or related fields is required. Annual salary depends on the level of experience but will be no less than $42,000. Initial appointments will be for a period of 1 year, with possibility for renewal. Further inquiries and applications including a CV and a statement of research interest should be sent by email to: andrew.pruszynski(a)uwo.ca. Applications will be reviewed on a rolling basis until the position is filled.

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10 Open PhD Positions in Frankfurt, Germany: International Max Planck Research School for Neural Circuits
by Jochen Triesch Oct. 25, 2015

Oct. 25, 2015

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

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[INNS-BigData 2016] Call for Papers
by Teng Teck Hou Oct. 25, 2015

Oct. 25, 2015

[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

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MIT postdoc position in AI/neuroscience/physics
by Max Tegmark Oct. 25, 2015

Oct. 25, 2015

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.

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2x Post-Doctoral Positions (Faisal Lab @ Imperial College London)
by Faisal, Aldo A Oct. 23, 2015

Oct. 23, 2015

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

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postdoctoral position (Pillow lab @ Princeton)
by Jonathan Pillow Oct. 22, 2015

Oct. 22, 2015

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.

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All-Level Faculty Positions in Interdisciplinary Research in Computer Vision, Neurally-inspired Computing and Data Science
by Ralf Haefner Oct. 21, 2015

Oct. 21, 2015

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.

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Post-Doctoral position in brain imaging – University of Geneva
by Narly Golestani Oct. 21, 2015

Oct. 21, 2015

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>.

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