- Comp-neuro - lists.cnsorg.org

Faculty Position in Computational Neuroscience at the University of California, Irvine
by Jeff Krichmar Sept. 14, 2014

Sept. 14, 2014

Dear Computational Neuroscientists, The following job position may be of interest to many of you. ************************** University of California, Irvine Faculty Position in Computational Neuroscience The Department of Cognitive Sciences (www.cogsci.uci.edu) at the University of California, Irvine (UCI) invites applications for a faculty position at the Associate or Full Professor level. We are especially interested in candidates who use mathematical, computational, or robotics approaches to study the neural basis of cognition in any of these areas: (1) vision, hearing, and attention; (2) memory and decision-making; (3) learning and development; (4) language. Applicants whose research relates to human behavior are preferred. A strong record of publications and extramural funding is essential. Exceptional candidates at the Assistant Professor level will also be considered. The online application includes: A cover letter, CV, research and teaching statements, 3 recent publications, and contact information for 3-5 referees. Interested candidates can apply for the position at: https://recruit.ap.uci.edu/apply/JPF02452. To ensure full consideration, please complete the application by November 15, 2014. The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer committed to excellence through diversity. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy. ************************** Best regards, Jeff Krichmar Department of Cognitive Sciences 2328 Social & Behavioral Sciences Gateway University of California, Irvine Irvine, CA 92697-5100 jkrichma(a)uci.edu http://www.socsci.uci.edu/~jkrichma

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postdoctoral position in Systems Neuroscience at the University of Pennsylvania
by Maria Geffen Sept. 12, 2014

Sept. 12, 2014

POSTDOCTORAL POSITION IN SYSTEMS NEUROSCIENCE University of Pennsylvania, Philadelphia PA A postdoctoral position is available in the Laboratory of Auditory Coding under direction of Dr. Maria Neimark Geffen at the University of Pennsylvania School of Medicine to study the neural mechanisms of hearing and emotional learning in the auditory cortex of awake rodents. We invite applications from talented, energetic and enthusiastic candidates with (or expecting) a Ph.D. in life sciences. The techniques include electrophysiological recordings, imaging and optogenetics in awake behaving rodents. Experience in either electrophysiology, imaging or behavioral studies is required. Computational skills are a plus. Please visit http://www.med.upenn.edu/hearing for more information. Our laboratory is part of the Hearing Sciences Center a at the Department of Otorhinolaryngology, Department of Neuroscience and the Mahoney Institute of Neurological Sciences. University of Pennsylvania has a very interactive and diverse systems neuroscience community. The University of Pennsylvania is within walking distance of the downtown of Philadelphia, which provides for a vibrant cultural urban environment. Please submit your application, including a CV, a brief statement of past and future research interests, links to recent publications, and recommendation letters (a letter from Ph.D. advisor is required) to Dr. Maria Neimark Geffen at mgeffen(a)med.upenn.edu .

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Henry Rutgers Term Chair in Computer and Data Science
by Bart Krekelberg Sept. 11, 2014

Sept. 11, 2014

Rutgers University - Newark (RU-N) seeks outstanding candidates to serve as Henry Rutgers Term Chair in Computer and Data Science, with a specific focus on computational methods in machine learning, or statistical modeling of complex data sets in the sciences, engineering, business, or medical fields. Recruitment is at the associate professor level; however, exceptional candidates qualifying for the full professor rank may be considered. This recruitment is part of the Rutgers University Strategic Plan to strengthen Rutgers leadership in burgeoning fields, and part of the new transdisciplinary research Institute for Data Science, Learning, and Applications (I-DSLA). I-DSLA brings together computer scientists, cognitive scientists, philosophers, and domain experts in neuroscience, environmental science, chemistry, medicine, business, and other professions. The new hire will be poised to leverage these experts as well as a new high performance computing cluster on the RU-N campus, to advance knowledge about learning from data. Applicants should hold a Ph.D. in Computer Science, Computational Statistics, or a related field and have a record of excellent scholarship, as demonstrated by significant publications and funding. They should be open to collaborative research within the RU-N community and will be expected to help build a group of faculty in areas related to I-DSLA, maintain an active externally-funded research program, teach undergraduate and graduate courses, and mentor Ph.D. students. Rutgers, The State University of New Jersey, is a leading national public research university and the state's preeminent, comprehensive public institution of higher education. Rutgers, the State University of New Jersey, is an Equal Opportunity / Affirmative Action Employer. Qualified applicants will be considered for employment without regard to race, creed, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, genetic information, protected veteran status, military service or any other category protected by law. As an institution, we value diversity of background and opinion, and prohibit discrimination or harassment on the basis of any legally protected class in the areas of hiring, recruitment, promotion, transfer, demotion, training, compensation, pay, fringe benefits, layoff, termination or any other terms and conditions of employment. Applicants should apply no later than November 1st, 2014. To receive detailed instructions on how to apply, please email hrsearch(a)rutgers.edu with the subject line 'How to apply'. --- Bart Krekelberg, PhD Associate Director, Center for Molecular and Behavioral and Neuroscience Associate Director, Rutgers Brain Imaging Center Associate Professor, Rutgers University Newark, NJ 07102 USA T: 973 353 3602 W: vision.rutgers.edu E: bart(a)vision.rutgers.edu

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Postdoctoral position available in the Niv Lab at Princeton
by Yael Niv Sept. 11, 2014

Sept. 11, 2014

A postdoctoral position is available in the lab of Dr. Yael Niv in the Princeton Neuroscience Institute and the Department of Psychology at Princeton University (http://www.princeton.edu/~nivlab) for a collaborative project with the lab of Geoffrey Schoenbaum at NIDA. Research in the Niv lab focuses on computational modeling of learning and decision making at the systems level (reinforcement learning, Bayesian inference), and model-driven behavioral and functional imaging experiments of human learning and decision making. Research in the Schoenbaum lab utilizes rodent models to study learning and decision making, as well as addiction. We seek an exceptionally talented candidate who is intensely interested in understanding decision making and addiction, has proven experience in empirical investigations of learning and decision making (and corresponding task design), has expertise in computer programming and modeling, and has a keen interest in reinforcement learning and normative models of behavior. Background in studies of addiction, functional imaging and/or rodent work is an advantage. Anticipated start date is January 2015 though there is considerable flexibility. This is a one-year position with the possibility of renewal, pending satisfactory performance. Essential Qualifications: PhD in psychology, neuroscience or equivalent. Proven experience with computer programming. Preferred Qualifications: The ideal candidate will have robust experience with fMRI (event related designs and model-based analysis techniques) or with studies of rodent decision making (Pavlovian and instrumental conditioning), will be proficient in programming (Matlab or equivalent), and will have experience with computational modeling (machine learning, reinforcement learning, Bayesian models). To apply, please visit the website https://jobs.princeton.edu (requisition # 1400567) and create an online application. Applicants must submit a cover letter stating background and research interests and citations of at least two representative publications, a CV, and contact information for at least two references. Princeton University is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. This position is subject to the University’s background check policy.

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Joint Neuroscience-Math tenure-track faculty position at UT Austin
by Ila Fiete Sept. 10, 2014

Sept. 10, 2014

Dear Colleagues, UT Austin is initiating a multi-faculty (cluster) search for tenure-track faculty in computational and theoretical neuroscience, to build on existing efforts here in that direction. I request that you pass on word of this search to exceptional senior postdocs who bridge math and neuroscience and are ready to start junior faculty positions. Attached below is the text of the search advertisement, and details on how to apply. Best regards, Ila --------------- The Departments of Neuroscience and Mathematics at the University of Texas at Austin are seeking a leader in the field of mathematical neuroscience or mathematics applied to neuroscience, for appointment as a tenure-track assistant professor. Areas of interest include, but are not limited to, the intersection of neuroscience with dynamical systems, partial differential equations, algebraic geometry, statistics, information theory, stochastic processes, and applied and computational topology. This search is part of a multi-faculty hiring initiative in Computational and Theoretical Neuroscience at UT Austin -- including a position in Psychology and a joint position between Neuroscience and Computer Science, with the aim of building on existing strengths in the field to create a Computational and Theoretical Neuroscience center. The successful candidate will orchestrate an outstanding program of independent research and contribute to an environment of diversity in higher education through research, teaching, and service. She or he will have joint membership in both departments and teach one course in each department. The position will include full access to the Texas Advanced Computing Center supercomputers, and the option to join various multi-disciplinary advanced computing and neuroscience centers on campus. Qualified applicants with a Ph.D. or equivalent and two or more years of post-graduate experience will be considered for appointment. Applications will be reviewed starting September 5, 2014, until the position is filled. Please submit applications through the MathJobs website: https://www.mathjobs.org/jobs/jobs/6059 <https://www.mathjobs.org/jobs>. A complete application will include: 1. Statement of research interests. 2. Curriculum vita. 3. Letters of reference from at least 3 individuals. 4. Statement of teaching philosophy and experience, with evidence of teaching excellence. UT Austin is an equal opportunity employer committed to excellence through diversity. We strongly encourage applications from all qualified individuals including women and minorities. UT Austin is responsive to the needs of dual career couples and is dedicated to work-life balance through an array of family-friendly policies (http://www.utexas.edu/provost/policies/family/) For further inquires related to this search, please email Kathleen Pantalion (kpantalion(a)mail.clm.utexas.edu <mailto:kpantalion@mail.clm.utexas.edu>). -- ________________________________ Ila Fiete Associate Professor Center for Learning and Memory The University of Texas at Austin Phone: 512.232.8439

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Job Posting: Neuroscience Image Processing Scientist at Northwestern University
by Xue Wang Sept. 9, 2014

Sept. 9, 2014

The Department of Radiology at Northwestern University Feinberg School of Medicine is seeking a full-time Neuroscience Image Processing Scientist. Under the direction of the Medical Director of the Neurological Testing Center and the Director of Neuroimaging Research, the Neuroscience Image Processing Scientist will be responsible for coordinating imaging for use in epilepsy surgery and other functional neurosurgical procedures. Assignments will require close interaction with neuroradiology and neuroimaging collaborators to develop and implement more advanced functional imaging techniques. The primary effort will be focused on the development and implementation of clinical tools; however, there is dedicated time for independent research. Northwestern has very active clinical and research programs in Neurology and Neuroimaging. Imaging resources include 10 clinical and 4 dedicated research high field MRI systems, a PET/CT system, high density EEG and TMS. There is a very active and rapidly expanding Neurosurgery group with strong collaborations with BrainLab, and a supportive clinical environment for research. Candidates should have an MD or PhD in neuroscience, medicine, physics, psychology or a related field, and excellent communication skills. Experience with analysis of structural, diffusion, fMRI including resting state, MEG, PET, SPECT, and EEG data is required. The ability to co-register multi-modality diagnostic (EEG, MEG) studies with SISCOM, MRI, fMRI, DTI and PET studies is a must. Experience in planning stereo EEG electrode placement, surgical guidance, and proficiency with PRISM software, CURRY Neuroimaging Suite, and BrainLab surgical navigation systems, is desired. The position is funded for an initial two-year time period, with a high likelihood of long term employment. Salary is based on the NIH scale and benefits are highly competitive. Position is available on July 1, 2014, and applications will be accepted until the position is filled. Applicants should send curriculum vitae, references and cover letter to: Todd B. Parrish, Ph.D. Department of Radiology 737 N. Michigan Ave, 16th Floor Chicago, IL 60611 toddp(a)northwestern.edu Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes, including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States

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2014 SFN Meeting Workshop: NSG Portal for parallel simulations
by Ted Carnevale Sept. 9, 2014

Sept. 9, 2014

What: Using the Neuroscience Gateway Portal for Parallel Simulations A Satellite Symposium at the 2014 Society for Neuroscience Meeting Where: Location to be announced in downtown Washington, DC When: 9 AM - Noon on Saturday, November 15, 2014 Speakers to include: A. Majumdar, S. Sivagnanam, and T. Carnevale Registration deadline: Friday, October 31, 2014 Do you have a large scale modeling project that exceeds the speed or capacity of your local hardware? Have you tried to use high performance computing (HPC) resources at your own institution, but found the process too difficult because of administrative or technical barriers? If yes, this workshop is for you. In a single morning session, you will learn how to use the Neuroscience Gateway Portal (NSG) http://www.nsgportal.org/ which is designed for neuroscientists who need to use HPC resources for large modeling projects. It simplifies every aspect of the process, from getting allocations of free CPU time to uploading your model, launching and monitoring jobs, and downloading results. The NSG already has several parallel simulators installed, including Brian, NEST, NEURON, PGENESIS and PyNN. Space is limited, so sign up quickly. See http://www.neuron.yale.edu/neuron/static/courses/nsg2014/nsg2014.html for further details and the registration form. Support: The NSG project is supported by a grant from the National Science Foundation. NSG provides its users free allocations of CPU time on HPC resources under the auspices of XSEDE (Extreme Science and Engineering Discovery Environment), which is also supported by NSF.

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PhD position in Neurocomputational modeling of language processing
by Hartmut Fitz Sept. 8, 2014

Sept. 8, 2014

A PhD position is available at the Max-Planck Institute for Psycholinguistics in Nijmegen, the Netherlands, within the 'Language in Interaction' consortium. The PhD candidate will participate in a team effort to understand the neurobiology underlying language processing by building computer models for sentence processing based on recurrent networks of spiking neurons. The goal is to develop a model with processing memory based on vector representations of words which are incrementally interpreted in terms of thematic roles ("who did what to whom"). A core objective will be to investigate the computational role of different neuronal models, connectivity types, neurobiologically motivated adaptation mechanisms, and different methods for calibrating the model's read-out units. Closing date: 30 September 2014 For more information see: https://www.languageininteraction.nl/jobs/phd-positions.html https://www.languageininteraction.nl/jobs/id-2nd-phd-call-general.html

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Postdoc opportunity at Stanford in Causal Brain Network Analysis
by Wei Wu Sept. 5, 2014

Sept. 5, 2014

Dear fellow researchers, The Etkin Lab at Stanford University is currently seeking to fill a postdoc position for causal brain network analysis. Please find below the job requirement and contact info. Thank you for your attention! Postdoc opportunity at Stanford in Causal Network Analysis – from Concurrent TMS/fMRI to Transdiagnostic Imaging of Psychiatric Disorders The Laboratory of Amit Etkin, MD PhD at Stanford University is currently accepting applications for a postdoctoral research fellowship focused on causal network analyses using fMRI in healthy individuals and patients with a range of psychiatric disorders. The focus of this position is on application of network analysis tools (e.g. graph theory, network-based statistics, etc) to fMRI data, including both causal circuit mapping experiments with concurrent transcranial magnetic stimulation (TMS) and fMRI, as well as resting-state data from patients across the mood, anxiety and stress disorders represented, and across the lifespan. The successful applicant will have a PhD in Cognitive Neuroscience, Neurophysiology, Psychology, Computer Science, Statistics or related fields. Experience with analysis of fMRI data or with causal network analysis tools is required. Additional programming experience is a plus. Duties will also include manuscript preparation, presentation of findings at conferences, management of research assistants and contribution to the preparation of grants. Laboratory and Stanford resources include research-dedicated 3T and 7T MRI scanners, concurrent TMS/fMRI setups and concurrent TMS/EEG setups. Salary commensurate with experience. More information about our ongoing studies can be found at: http://etkinlab.stanford.edu. To apply, please send a curriculum vitae, a statement describing research interests and relevant background and three letters of recommendations, as well as relevant reprints/preprints of research articles to: Amit Etkin, MD, PhD Department of Psychiatry and Behavioral Sciences Stanford University amitetkin(a)stanford.edu

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New software for neuronal model fitting
by Szabolcs Káli Sept. 5, 2014

Sept. 5, 2014

Dear Colleagues, We are pleased to announce the availability of the first public (beta) version of Optimizer, an interactive software tool for fitting the parameters of neuronal models. Optimizer was developed in Python, and has the following main features: - efficiently fits the free parameters of arbitrary neural (or other) models using advanced nonlinear optimization algorithms - all aspects of the optimization problem (including the model, its free parameters, the target data, the simulation and recording protocol, the error function) and the fitting process itself can be conveniently controlled from a graphical user interface (GUI) - full internal support for models implemented in the Neuron simulator (while other models can be also optimized using a "black box" approach) - choice of 7 different (tunable) optimization algorithms, including a customized evolutionary (genetic) algorithm, differential evolution, simulated annealing, the basinhopping algorithm, random search, and two local search methods - choice of 11 different error functions for the comparison of simulated and experimental (target) data, including generic ones as well as several feature-based ones which are appropriate for the comparison of membrane potential traces containing action potentials; error functions can be combined with arbitrary weights - the software is easily extensible in various ways to support novel scenarios A paper describing the software, several use cases, and comparisons with other model fitting tools, has been recently published in Frontiers in Neuroinformatics (the abstract and citation details are included at the end of this message): http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00063/abstract The software can be downloaded using git from https://github.com/vellamike/optimizer where you can also find instructions for installing the software and its dependencies. The current version of Optimizer has been verified to work under several recent Linux distributions. Alternatively, a compressed archive containing the software and various examples can be downloaded from https://github.com/vellamike/optimizer/releases/tag/v2.0-beta The documentation of the software is available at http://optimizer.readthedocs.org/en/latest/ Finally, we wish to encourage everyone interested in fitting neuronal models to try the software and provide feedback. If you find that your favorite optimization algorithm or error function is not currently included in Optimizer, it can probably be added with relatively little effort, especially given an existing implementation of the algorithm or function itself, and we would be very interested in collaborating on such an extension. We are also interested in learning about the model fitting problems encountered by potential users; we would be happy to advise users on whether and how Optimizer may be used to solve particular problems; in addition, future development of the software will be guided by the feedback that we receive. Best regards, Szabolcs Káli and Péter Friedrich Friedrich P, Vella M, Gulyás AI, Freund TF and Káli S (2014) A flexible, interactive software tool for fitting the parameters of neuronal models. Front. Neuroinform . 8 :63. doi: 10.3389/fninf.2014.00063 Abstract: The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool.

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Job/Fellowship Opportunity: Big Data IT Management and Automation in NeuroMorpho.Org
by Rubén Armañanzas Sept. 4, 2014

Sept. 4, 2014

George Mason University, Krasnow Institute for Advanced Study in Fairfax, VA (USA), invites applications for a full-time doctoral student graduate research assistant position available immediately in the Center for Neural Informatics, Structures, and Plasticity (krasnow1.gmu.edu/cn3) headed by Prof. Giorgio Ascoli. To be considered for this position, applicants must apply to the PhD program in Bioengineering at George Mason University (http://volgenau.gmu.edu/doctoral-degrees) following the instructions below. The successful applicant will join a collaborative multidisciplinary team at the cutting edge of the development and dissemination of digital tools and resources for neuroscience. The Ascoli Lab is funded by the National Institutes of Health, the National Science Foundation, the Office of Naval Research, the Air Force Office of Scientific Research, the Intelligence Advanced Research Projects Activity, and Keck. This position is particularly suited for computationally minded researchers seeking exposure to the burgeoning field of big data in neuroinformatics. The candidate will join the NeuroMorpho.Org project -- a free, public, centralized repository of neuronal digital reconstructions. NeuroMorpho.Org has firmly established itself as a powerful resource for the neuroscience community, with millions of downloads and data usage in over 200 publications by other labs since its 2006 public release. Its version 5.7 contains over 148,000 internal data files pertaining to more than 11,000 neuronal reconstructions contributed by 144 laboratories worldwide from 24 species and 95 brain regions. The pre-doctoral fellow will work within the CN3 research group and will be tasked with a variety of activities including design of new Information Technology (IT) solutions to enhance the performance of existing software and hardware infrastructure. Due to the growing pace of the field, the recipient will be also responsible for tuning and implementing the next generation support for Big Data handling of digital neuronal reconstructions. Desired qualifications include: 1. proficiency in C/C++, Java and Python; 2. experience in Unix/Linux server administration; MySQL design and administration; web technologies and API web services; content management systems; and 3. a BS/MS in Computer Science, Information/Systems/Software Engineering or a similar field. Knowledge in task analysis automation and interest in neuroscience are a plus. The position includes a $22,000/year 12 months-stipend (20 hours/week during academic year, 40 hours/week during summer) in addition to health insurance and up to 18 credits per year of tuition coverage in the Volgenau school of Engineering. To apply, please follow the PhD application instructions (http://volgenau.gmu.edu/how-to-apply) Include the wording "/Neuroinformatics fellowship in Prof. Giorgio Ascoli's lab/" in both your research/interest statement and cover letter. After submitting the application material, please also forward a copy of your resume, research/interest statement, and cover letter directly to ascoli(a)gmu.edu <mailto:ascoli@gmu.edu> with subject "Bioengineering PhD candidate". Beyond the frontiers of neuronal types

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Postdoctoral position at the University of Pittsburgh
by Brent Doiron Sept. 3, 2014

Sept. 3, 2014

Applications are invited for a Simons foundation funded postdoctoral position(s) in the Mathematics and Neuroscience departments of the University of Pittsburgh. The project will involve the collection, analysis, and modeling of large-scale multi-unit recordings from cortex, with an emphasis on understanding how visual attention modulates neural response. Of specific interest is elucidating the neural mechanisms that underlie the control of neural variability, as well as its consequences on neural function. Successful candidates will either be members of the working group of Dr. Brent Doiron and will be in tight collaboration with the Dr. Marlene Cohen, or vice versa, depending on the fit of the applicant. Theoretical candidates should expect to be members of the Doiron group, while candidates with an experimental focus would be in the Cohen group. Please visit www.math.pitt.edu/~bdoiron and www.cohenlab.com for a list of recent work from the Doiron and Cohen groups. The successful candidate(s) will be integrated into the Center for the Neural Basis of Cognition (http://www.cnbc.cmu.edu) a large and vibrant community of neuroscientists spanning many departments across the University of Pittsburgh and Carnegie Mellon University. The position is funded for several years, with an initial one-year appointment and an expectation of extension to at least three years, given satisfactory performance. The salary is competitive, and the start date is negotiable (January 2015 is optimal). Applicants with a PhD in Mathematics, Applied Mathematics, Neuroscience, Statistics, Biology, Psychology or a related discipline, and ideally with experience in computing, computational neuroscience, statistical analysis, or in vivo recording should send a CV including a list of publications, a research statement, and reference contact information to bdoiron(a)pitt.edu The University of Pittsburgh is an Affirmative Action, Equal Opportunity Employer, and women and members of minority groups under-represented in academia are especially encouraged to apply. -- Associate Professor of Mathematics Center for the Neural Basis of Cognition University of Pittsburgh 301 Thackeray Hall Pittsburgh, PA, 15260 www.math.pitt.edu/~bdoiron

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Tenure Track Faculty Position in Neuroscience at Rutgers University - Newark
by Bart Krekelberg Sept. 3, 2014

Sept. 3, 2014

The Center for Molecular & Behavioral Neuroscience (CMBN) at Rutgers University seeks outstanding candidates for a tenure track Assistant Professor position in NEUROSCIENCE. Applicants should hold a Ph.D. degree in Neuroscience or a related field and have completed at least two years of post-doctoral training. The ideal candidate for this position asks fundamental hypothesis-driven questions about brain structure and function and is open to establishing collaborative research efforts within the Rutgers neuroscience community. Research areas of particular interest are executive control, sensory-motor integration, learning and memory, and emotional regulation. The successful applicant will likely use a broad range of experimental approaches in non-human primates, humans, and/or rodents, and methods including electrophysiology, optogenetics, and functional imaging. The assistant professor will be expected to maintain an active externally-funded research program, to teach undergraduate and graduate courses in neuroscience, and to mentor Ph.D. students in the Behavioral and Neural Sciences program. Rutgers, The State University of New Jersey, is a leading national public research university and the state's preeminent, comprehensive public institution of higher education. Rutgers is dedicated to conducting research that breaks new ground; to teaching that meets the highest standards of excellence; and to providing services, solutions, and clinical care that help individuals and the local, national, and global communities where they live. CMBN is located in Newark NJ, a short drive from New York City. CMBN is part of a large community of neuroscientists at Rutgers Newark, with additional researchers in the Departments of Biological Sciences and Psychology as well as in the Rutgers University New Jersey Medical School. Collectively, these researchers represent all levels of analysis in neuroscience (http://www.neuroscience.newark.rutgers.edu) Applicants should apply as soon as possible, but no later than 10/20/2014. Rutgers is an Equal Opportunity/Affirmative Action Employer and has a strong commitment to diversity. Women and members of underrepresented minorities are especially encouraged to apply. Rutgers-Newark is noted for its exceptionally diverse student population. To receive detailed instructions on how to apply, please send an email to search(a)cmbn.rutgers.edu with the subject line 'How to apply'. --- Bart Krekelberg, PhD Associate Director, Center for Molecular and Behavioral and Neuroscience Associate Director, Rutgers Brain Imaging Center Associate Professor, Rutgers University Newark, NJ 07102 USA T: 973 353 3602 W: vision.rutgers.edu E: bart(a)vision.rutgers.edu

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IWSYP’14 - I International Workshop on Synaptic Plasticity
by Thiago Matos Pinto Sept. 3, 2014

Sept. 3, 2014

Dear colleagues, Please see the information below about an upcoming workshop on synaptic plasticity. Best wishes, Thiago *** I International Workshop on Synaptic Plasticity - IWSYP’14 *** University of São Paulo, Ribeirão Preto, São Paulo State, Brazil Workshop dates: September 8th - 9th 2014 Organizers: Thiago Matos Pinto and Antonio Roque Participation is free of charge! This workshop is a satellite event of the XXXVIII Annual Meeting of the Brazilian Society for Neuroscience and Behavior (SBNeC), which will be held on September 10-13 in Búzios, Rio de Janeiro. The SBNeC meeting will also feature big names in Neuroscience, and will be a preparatory event for the 9th World Congress of the International Brain Research Organization (IBRO), which will take place in Rio de Janeiro in 2015. Confirmed speakers: Chris De Zeeuw (Erasmus Medical Center, Rotterdam, The Netherlands & Netherlands Institute for Neuroscience, Amsterdam, The Netherlands) Freek Hoebeek (Erasmus Medical Center, Rotterdam, The Netherlands) Reinoud Maex (École Normale Supérieure, Paris, France) Ricardo Leão (University of São Paulo, Ribeirão Preto, Brazil) Thiago Matos Pinto (University of São Paulo, Ribeirão Preto, Brazil) Gabriela Antunes (University of São Paulo, Ribeirão Preto, Brazil) Giseli de Sousa (Federal University of Santa Catarina, Florianópolis, Brazil) Cleiton Lopes Aguiar (University of São Paulo, Ribeirão Preto, Brazil) Renan Oliveira Shimoura (University of São Paulo, Ribeirão Preto, Brazil) Bruna Lanzillotta de Mattos (Fluminense Federal University, Niterói, Rio de Janeiro State, Brazil) Luana Chagas (Fluminense Federal University, Niterói, Rio de Janeiro State, Brazil) Querusche Zanona (Federal University of Rio Grande do Sul, Brazil) Fabiana Santana (Federal University of Rio Grande do Sul, Brazil) We look forward to seeing you in Ribeirão Preto. With best wishes, Thiago Matos Pinto, IWSYP'14 Organizer

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Faculty positions in Computer Science at American University
by Mark Laubach Sept. 2, 2014

Sept. 2, 2014

American University, College of Arts & Sciences, Department of Computer Science Computer Science (Assistant, Associate or Full Professor) The Department of Computer Science in the College of Arts and Sciences at American University in Washington, DC invites applications for up to three tenure-track or tenured Assistant/Associate/Full Professors to form a collaborating research team. We seek either a group of researchers who will be hired together, or a senior individual with a vision for filling the other positions. The team’s research expertise may be in any area of computer science. Following the department’s strong recent hires in the interdisciplinary areas of computational neuroscience and persuasive gaming, the university seeks to build computer science’s core program areas, which may include algorithms and data structures, architecture, robotics, databases and information retrieval, human-computer interactions, numerical and symbolic computation, operating systems, programming languages, or software methodology and engineering. Preference will be given to teams or visions that contribute to more than one of the core program areas, and that contribute to the university’s capacity in the area of big data. The Computer Science Department is currently in a period of expansion, and is poised to become a leader in the university’s technology an innovation sectors. To support this trajectory, the department will soon be moving to a new building that is designed to promote inspiration, collaboration, creation and cultivation. QUALIFICATIONS All applicants should have a strong record of (or potential for) externally sponsored research. We are especially eager to recruit candidates with established research partnerships (or the ability to form such partnerships) in the Washington, DC area. Candidates should also have a record of excellence in teaching and mentoring students. Teaching responsibilities will include core courses in computer science and more advanced courses in the applicant’s area of specialty. The Ph.D. in Computer Science or a closely related field is required; post-doctoral or industry experience is preferred. At least one appointment will be at a senior level with tenure. Preference will be given to senior candidates who are able and willing to lead the department, including (but not limited to) the development of a Ph.D. granting program. APPLICATION INSTRUCTIONS Applicants should include a statement (a joint statement for team applications) of research outlining the research focus (or foci) and future plans for developing a nationally competitive, externally funded research program at American University. In addition to a (joint, if applicable) research statement, each applicant should include statements of individual research and teaching experience, a CV, and the names of three references not in the proposed team. Please submit applications via: http://apply.interfolio.com/25813. Review of applications will begin November 3 and continue until the position is filled.

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Postdoc position available
by Olaf Sporns Sept. 2, 2014

Sept. 2, 2014

*Computational Cognitive Neuroscience Lab - Indiana University* *Postdoctoral Fellowship* Applications are invited for an open position as postdoctoral fellow in the Computational Cognitive Neuroscience Lab, Department of Psychological and Brain Sciences, Indiana University Bloomington. The core research focus of the lab is in the area of brain networks and connectomics. The lab works on anatomical and functional data sets from a number of species, with a strong emphasis on human brain connectivity and connectome data. Ongoing projects in the lab involve applications of models and tools from network science, graph theory, complex dynamics and information theory to basic and clinical/translational neurobiological questions. A description of the lab and current research areas can be found at www.indiana.edu/~cortex <http://www.indiana.edu/%7Ecortex> . Applicants should (a) have (or be in the final stages of obtaining) a PhD or equivalent degree in a field relevant to the research focus of the lab (e.g. neuroscience, neuroimaging, applied mathematics, computer science or bioengineering); (b) have a strong background in computational methods and programming (including advanced skills in Matlab); and (c) have strong enthusiasm for using computational approaches to understand neurobiological problems. Candidates with background in networks or graph theory, experience in processing and analyzing neuroimaging or electrophysiological recordings, exposure to "big data" approaches relevant to brain function, and a strong record of publication are especially encouraged to apply. The postdoctoral fellow will join a very active and interdisciplinary research group, and will be expected to engage and interact with a growing number of network and complex systems scientists at Indiana University and beyond. The lab maintains close ties and collaborations with scientists in the IU Imaging Research Facility (housing a 3T Siemens MR scanner), the Center for Complex Networks and Systems at the School of Informatics and Computing, the Medical School campus, and at other institutions nationally and internationally. All lab members have access to excellent computational facilities. The potential start date is negotiable, and the position is initially offered for a 1-year term which is renewable upon mutual agreement.Salary levels will follow NIH guidelines. Please email application materials (cover letter, a full CV with a list of publications, and 3 letters of reference) to Olaf Sporns at osporns(a)indiana.edu <mailto:osporns@indiana.edu> . -- Olaf Sporns -- @spornslab Department of Psychological and Brain Sciences Programs in Neuroscience and Cognitive Science Indiana University Bloomington, IN 47405

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NIPS 2014 - Final Call for Demonstrations
by Hugo Larochelle Sept. 2, 2014

Sept. 2, 2014

The Neural Information Processing Systems Conference 2014 http://nips.cc/Conferences/2014/ has a Demonstration Track running in parallel with some of the evening Poster Sessions, December 8-11, 2014, in Montreal, Quebec, Canada. Demonstration Proposal Deadline: Monday September 15, 2014, 11pm Universal Time (4pm Pacific Daylight Time). http://nips.cc/Conferences/2014/CallForDemonstrations Demonstrations offer a unique opportunity to showcase: - Hardware technology - Software systems - Neuromorphic and biologically-inspired systems - Robotics or other systems, which are relevant to the technical areas covered by NIPS (see Call for Papers http://nips.cc/Conferences/2014/CallForPapers) Demonstrations must show novel technology and must be run live, preferably with some interactive parts. Unlike poster presentations or slide shows, live action and interaction with the audience are critical elements. Submissions: Submission of demo proposals at the following URL: https://nips.cc/Demonstrators/ You will be asked to fill a questionnaire and describe clearly: - the technology demonstrated - the elements of novelty - the live action part - the interactive part - the equipment brought by the demonstrator - the equipment required at the place of the demo Evaluation Criteria: Submissions will be refereed on the basis of technical quality, novelty, live action, and potential for interaction. Demonstration chair: Hugo Larochelle <demonstration-ch...(a)lists.nips.cc<http://lists.nips.cc>> http://nips.cc/Conferences/2014/CallForDemonstrations

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Open Postdoc Position in Brain-Computer Interfaces
by Michael Tangermann Sept. 2, 2014

Sept. 2, 2014

Dear colleagues, may I ask you to please circulate the following job offer in your labs and email lists? Thanks a lot and best greetings from Freiburg, Michael OPEN POSITION FOR A POSTDOCTORAL FELLOW: ======================================== Type: Postdoc Position Topic: Brain-Computer Interfaces in Cognitive Rehabilitation after Stroke (speech & attention deficits) Where: BrainStateDecoding lab of Dr. Michael Tangermann (Computer Science Dept., University of Freiburg, Germany) When: ideal start before November 2014; duration: 12 months+ Further information: http://www.bsdlab.uni-freiburg.de/jobs (Please apologize for cross-posting) --- Dr. Michael Tangermann Phone: +49.(0)761.2038423 Fax : +49.(0)761.2038417 University of Freiburg BrainLinks-BrainTools Excellence Cluster Brain State Decoding Lab Albertstr. 23, Room 0.003 79104 Freiburg, Germany http://www.bsdlab.uni-freiburg.de

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Fwd: Register Today for the IPEG-Meeting
by Martijn Arns Sept. 2, 2014

Sept. 2, 2014

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Multiple job listings in Brain-Inspired Computing at IBM Research - Almaden
by John Arthur Sept. 2, 2014

Sept. 2, 2014

IBM’s Brain-Inspired Computing team at IBM Research - Almaden is building a first-of-a-kind modular, scalable, non-von Neumann, ultra-low power, cognitive computing architecture and associated end-to-end ecosystem. We are building state-of-the-art digital spiking neuromorphic Application Specific Integrated Circuits (ASICs) and systems (large-scale and mobile) to solve real-time sensory problems. We have a number of positions in hardware, software, and other technical areas. http://modha.org/blog/2014/08/jobs_braininspired_computing.html To receive full consideration, please apply using the links below to ensure your resume/CV will be directed to the appropriate hiring manager. RES-0683225 Research Staff Member-ASIC and System Design https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683225 RES-0683232 Research Staff Member-Software and Applications https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683232 RES-0683057 Research Staff Member-Software and Applications https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683057 RES-0683578 Research Staff Member-Scalable Systems / Supercomputing Architect https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683578 RES-0683223 Hardware and Systems Engineer https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683223 RES-0683215 Systems Software Engineer https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683215 RES-0683211 Systems Software Engineer https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683211 RES-0683583 Software Engineer: Tools and Programming Languages https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683583 RES-0683592 Development & Delivery Engineer https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683592 RES-0683593 Software Trainer / Coach https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683593 RES-0683227 Technical Writer/Archivist https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0683227

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3 open PhD psoitions at the Neuroinformatics Lab at the Institute of Cognitive Science, University of Osnabrück, Germany [Reminder]
by Gordon Pipa Sept. 1, 2014

Sept. 1, 2014

The Neuroinformatics Research Group (Prof. Dr. Gordon Pipa) of the Institute of Cognitive Science invites applications for 3 Research Assistants (PhD student level), (Salary level E 13 TV-L 50%) to be filled as soon as possible for a period of three years. The position allows for further scientific qualification. We invite applicants that are interested in research in Neuroinformatics, with an emphasis on dynamical systems, machine learning, virtual reality, computational linguistics and electrophysiology. Candidates will participate in a highly international PhD program on cognitive science (with >40 currently enrolled students) and interdisciplinary research projects that can involve cooperation with other disciplines of our institute. Candidates should be highly motivated to understand the structure of neuronal coding and neuronal representations. To study this, we involve different research strategies that range from the development of highly sophisticated data analysis strategies, to modelling of neuronal processes on the level of recurrent networks. The qualification profile of the candidates can range from a purely mathematical neuroscientist, a dynamical systems researcher to interdisciplinary candidates that share interest in performing experiments with the virtual reality combined with EEG and sophisticated machine learning-based analysis of recorded activity (at http://ikw.uni-osnabrueck.de/en/ni/publications you find an overview of recent research topics). Description of Responsibilities: The successful candidate will be involved in several research projects that range from BSc to MSc projects. The position also involves teaching Cognitive Science courses at BSc and MSc level (2 hours/week). Required Qualifications: Candidates are expected to have an excellent academic degree (Master/diploma). Applicants should have an excellent knowledge in the field of machine learning, i.e. generalized linear and state space models, kernel methods, reservoir computing and deep learning. Experience or a strong interest in the fields of complex systems, computational neurosciences, dynamical systems theory and the concepts to study these, i.e. bifurcation and stability analysis, and delay- coupled differential equations, measurements of complexity, are encouraged. Experience or a strong interest in experimental methods such as EEG, and virtual reality are highly welcome. In addition, a strong interest or experience in the estimation of causal interactions from time series is welcome. As a certified family-friendly institution, Osnabrück University is committed to furthering the compatibility between work/studies and family life. As an employer, Osnabrück University is particularly concerned with creating equal opportunities for women and men. Women with relevant qualifications are therefore strongly encouraged to apply for the position. Preference will be given to women with equal qualifications. Furthermore, qualified applicants with disabilities will be favored. Applications with the usual documentation, including two letters of recommendation, should be submitted by e-mail in a single PDF file to the Director of the Institute of Cognitive Science (office(a)ikw.uni-osnabrueck.de) no later than 08.09.2014. An electronic copy should be sent to Prof. Dr. Gordon Pipa (gpipa(a)uni-osnabrueck.de) who can also be contacted for further information. ---------------------------------------------------------------------------- --- Professor and Chair of the Neuroinformatics Department Dr. rer. nat. Gordon Pipa Institute of Cognitive Science, Room 31/404 University of Osnabrueck Albrechtstr. 28, 49069 Osnabrueck, Germany tel. +49 (0) 541-969-2277 fax (private). +49 (0) 5405- 500 80 98 home office. +49 (0) 5405- 500 90 95 e-mail: gpipa(a)uos.de webpage: http://www.ni.uos.de <http://www.ni.uos.de/> Projects: http://www.pipa.biz/Projects_and_Lectures/projects_and_lectures.html research gate: https://www.researchgate.net/profile/Gordon_Pipa/?ev=prf_act google scholar: http://scholar.google.de/citations?user=joR6mgEAAAAJ Personal Assistent and Secretary of the Neuroinformatics lab: Anna Jungeilges Tel. +49 (0)541 969-2390 Fax +49 (0)541 969-2246 Email: anna.jungeilges(a)uni-osnabrueck.de visit us on http://www.facebook.com/CognitiveScienceOsnabruck https://twitter.com/#!/CogSciUOS <https://twitter.com/>

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Tenure Track Assistant Professot in Theoretical and Computational Neuroscience
by Liu, Robert C Sept. 1, 2014

Sept. 1, 2014

Tenure Track Assistant Professor in Theoretical and Computational Neuroscience. The Department of Biology in the Emory College of Arts and Science is seeking applications for a tenure-track position in theoretical and computational neuroscience. Current computational neuroscience research at Emory is anchored in the Department of Biology (http://www.biology.emory.edu<http://http/www.biology.emory.edu/>) and is grounded in experimental preparations and neurobiological questions (http://compneurosci.college.emory.edu) The ideal candidate would be a theorist who bridges into experimental data analysis in systems neuroscience. Innovative approaches to understanding principles of neural coding, neural dynamics, learning, memory, and behavior are of particular interest. The successful candidate is anticipated to have a PhD and postdoctoral experience in a quantitative science, and is expected to contribute to the Biology Department's teaching mission in the context of programs in quantitative theory and methods (http://quantitative.emory.edu) and neuroscience (http://www.nbb.emory.edu) Interactions with experimentalists and other theorists within Emory's rich, collaborative neuroscience community are encouraged. Emory has more than 120 laboratories participating in graduate programs in Neuroscience (http://biomed.emory.edu/PROGRAM_SITES/NS/) and Biomedical Engineering (http://www.bme.emory.edu) and spanning Emory College (Biology, Psychology, Physics, Anthropology), School of Medicine, Yerkes National Primate Research Center and Georgia Institute of Technology. Applications should include a curriculum vitae, a research statement, a teaching statement and three confidential reference letters. Applications and reference letters must be electronically uploaded through Interfolio at http://apply.interfolio.com/25348<http://go.toutapp.com/ecca7f39a80cf3c11e>. The deadline for applying is December 1, 2014; applications received after this date are not guaranteed full consideration. Emory University is an Equal Opportunity/Affirmative Action/Disability/Veteran employer. Women, minorities, persons with disabilities and veterans are encouraged to apply. Robert C. Liu Associate Professor Winship Distinguished Research Professor Emory University Department of Biology Rollins Research Center 1510 Clifton Road NE, Room 2131 Atlanta, GA 30322 Phone: (404) 727-5274 Fax: (404) 727-2880 Email: robert.liu at emory.edu Website: http://www.biology.emory.edu/research/Liu/html/index.php This e-mail message (including any attachments) is for the sole use of the intended recipient(s) and may contain confidential and privileged information. If the reader of this message is not the intended recipient, you are hereby notified that any dissemination, distribution or copying of this message (including any attachments) is strictly prohibited. If you have received this message in error, please contact the sender by reply e-mail message and destroy all copies of the original message (including attachments).

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BRAIN-FETs 2014: 1st Clustering Workshop on Future Emerging NeuroTechnologies, 16-17 Oct 2014, Genova (Italy)
by Giugliano Michele Sept. 1, 2014

Sept. 1, 2014

APOLOGIES FOR CROSS-POSTING Dear Colleagues, Michele Giugliano (U Antwerpen) and Luca Berdondini (Italian Institute of Technology) are organising the 1st Clustering Workshop on Future Emerging NeuroTechnologies<http://www.brainfet.eu>, to be held on 16th-17th October 2014, in Genova (Italy)<http://www.brainfet.eu/travel-info/venue.html>. This workshop aims at clustering a relatively small subset of the European FET community, particularly active on Brain inspired ICT, Neurotechnologies, novel materials, and computational approaches. It is a unique opportunity to learn about ongoing research and to critically contribute in designing next steps in FETs, successfully facing the many challenges that await. The cluster of EC-funded projects who organize the event (see the workshop flyer<http://ec.europa.eu/information_society/newsroom/cf/dae/document.cfm?doc_id…> for the list), is characterized by common efforts, integrating innovative developments on future emerging technologies applied to Neuroscience, and qualified by a synergy among diverse experimental, computational, and engineering approaches. The format of the workshop consists in a two-days event and in a networking evening. Participants from EC-funded Projects are welcome to present their research in a poster session and to meet colleagues with a heterogeneous background and from all over Europe. Interested? Register as soon as possible by filling and submitting the online application form<http://www.brainfet.eu/registration.html>. Admission will be limited to the first 150 participants. The conference registration fee, covering coffee breaks, lunches and the social dinner is: 100 EUR/person. Thanks for your attention, -- Michele Giugliano, PhD Dept. of Biomedical Sciences University of Antwerp Campus Drie Eiken (CDE) - D.T.657 Universiteitsplein 1, B-2610 Wilrijk (Belgium) url: http://www.ua.ac.be/michele.giugliano

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Postdoctoral position studying neurovascular coupling
by Patrick Drew Sept. 1, 2014

Sept. 1, 2014

A postdoctoral fellowship studying the neural circuits involved in neurovascular coupling is available in the laboratory of Patrick Drew. We are looking for an independent, highly motivated scientist to use a combination of optical (two-photon microscopy and intrinsic imaging), optogenetic, and electrophysiological techniques to study neurovascular coupling in awake, behaving mice. The successful applicant will have Ph.D. in neuroscience, biomedical engineering, physiology or a related field, and at least one first author publication. The candidate should have excellent English communication skills, experience with in vivo electrophysiology, optogenetics and/or optical imaging techniques. Strong data analysis and quantitative skills are required. The position is for one year, with possibility of extension up to two additional years contingent on funding. Applications will be reviewed upon receipt and will be accepted until the position is filled. Apply to job #52876 at http://apptrkr.com/504686 More information about the lab can be found at - http://www.esm.psu.edu/~patrick/Drew_Lab/Drew_Lab.html. Applications must be submitted electronically and include a statement of research interests, CV and contact details of three letters of reference to Dr. Patrick Drew: pjd17(a)psu.edu _________________________________ Patrick J. Drew Assistant Professor Center for Neural Engineering Dept. Engineering Science and Mechanics & Dept. Neurosurgery The Pennsylvania State University W-317 Millennium Science Complex University Park, PA 16802 (814) 863-1473 http://www.esm.psu.edu/~patrick/Drew_Lab/

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Call for Papers - Neural Networks special issue on Big Data
by Asim Roy Sept. 1, 2014

Sept. 1, 2014

Apologies for cross posting. Special Issue on Neural Network Learning in Big Data [Special Issue on Neural Network Learning in Big Data] Neural Networks Special Issue: Neural Network Learning in Big Data Big data is much more than storage of and access to data. Analytics plays an important 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 encounter theoretical challenges in scaling up to big data. Plus there are challenges of high dimensionality, velocity and variety for all types of machine learning algorithms. 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. The brain is arguably the best and most elegant big data processor and is the inspiration for neural network learning methods. Neural network 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 for stored big data. For stored big data, neural network algorithms can learn from all of the data instead of from samples of the data. And the same is true for streaming data where not all of the data is actually stored. In general, online, incremental learning algorithms are less vulnerable to size of the data. Neural network algorithms, in particular, can take advantage of massively parallel (brain-like) computations, which use very simple processors, that other machine learning technologies cannot. Specialized neuromorphic hardware, originally meant for large-scale brain simulations, is becoming available to implement these algorithms in a massively parallel fashion. Neural network algorithms, therefore, can deliver very fast and efficient real-time learning through the use of hardware and this could be particularly useful for streaming data in the Industrial Internet. Neural network technologies thus can become significant components of big data analytics platforms and this special issue will begin that journey with big data. For this special issue of Neural Networks, we invite papers that address many of the challenges of learning from big data. In particular, we are interested in papers on 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 online learning to solve real-world big data problems (e.g. health care, transportation, and electric power and energy management). RECOMMENDED TOPICS: Topics of interest include, but are not limited to: 1. Autonomous, online, incremental learning - theory, algorithms and applications in big data 2. High dimensional data, feature selection, feature transformation - theory, algorithms and applications for big data 3. Scalable neural network algorithms for big data 4. Neural network learning algorithms for high-velocity streaming data 5. Deep neural network learning 6. Neuromorphic hardware for scalable neural network learning 7. Big data analytics using neural networks in healthcare/medical applications 8. Big data analytics using neural networks in electric power and energy systems 9. Big data analytics using neural networks in large sensor networks 10.Big data and neural network learning in computational biology and bioinformatics SUBMISSION PROCEDURE: Prospective authors should visit http://ees.elsevier.com/neunet/ for information on paper submission. During the submission process, there will be steps to designate the submission to this special issue. However, please indicate on the first page of the manuscript that the manuscript is intended for the Special Issue: Neural Network Learning in Big Data. Manuscripts will be peer reviewed according to Neural Networks guidelines. Manuscript submission due: December 15, 2014 First review completed: March 1, 2015 Revised manuscript due: April 1, 2015 Second review completed, final decisions to authors: April 15, 2015 Final manuscript due: April 30, 2015 GUEST EDITORS: Asim Roy, Arizona State University, USA (asim.roy(a)asu.edu<mailto:asim.roy@asu.edu>) (lead guest editor) Kumar Venayagamoorthy, Clemson University, USA (gkumar(a)ieee.org<mailto:gvenaya@clemson.edu>) Nikola Kasabov, Auckland University of Technology, New Zealand (nkasabov(a)aut.ac.nz<mailto:nkasabov@aut.ac.nz>) Irwin King, Chinese University of Hong Kong, China (irwinking(a)gmail.com<mailto:irwinking@gmail.com>)

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