- Comp-neuro - lists.cnsorg.org

Postdoc Position Available in Deep Learning for Vision at RIT

by Christopher Kanan

One postdoctoral position is available in the laboratory of Christopher Kanan at the Rochester Institute of Technology (RIT), in Rochester, NY. The lab specializes in applying machine learning algorithms to solve problems in computer vision and related fields. The candidate will be responsible for developing new algorithms for the detecting manipulated and tampered images. They will also work on adversarial networks for image generation and related techniques. Requirements: Ph.D. in computer science or related field; A research record in computer vision and/or machine learning; Familiarity with deep learning The position is initially for one year, but is renewable upon strong performance for an additional year. The salary is significantly above the typical postdoctoral market rate. Applications should be sent by email to ( christopher.kanan(a)rit.edu) and should include a CV, the expected data of availability, and contact information for two references. The starting date is September 2016. *About the lab*: http://klab.cis.rit.edu/ About Rochester, NY Rochester is the third largest city in the U.S. state of New York. The quality of life in the area is excellent. It has a low cost of living and some of the best K-12 public schools in the US.

July 21, 2016

Fwd: Job Advertisement - Postdoctoral Research Associate in Neurophysics and Brain Dynamics

by Paula Sanz-Leon

Postdoc position at the University of Sydney ---------- Forwarded message ---------- From: Cindy Guy <cindy.guy(a)sydney.edu.au> Date: Wed, Jul 13, 2016 at 8:51 AM Subject: Job Advertisement - Postdoctoral Research Associate in Neurophysics and Brain Dynamics To: "brain(a)physics.usyd.edu.au" <brain(a)physics.usyd.edu.au>, " complexity-usyd(a)googlegroups.com" <complexity-usyd(a)googlegroups.com> *Please pass this on to anyone you think may be interested.* Link – Live Advertisement <http://sydney.nga.net.au/cp/index.cfm?event=jobs.checkJobDetailsNewApplicat…> *Closing date: 15 August 2016* POSTDOCTORAL RESEARCH ASSOCIATE IN NEUROPHYSICS AND BRAIN DYNAMICS *Postdoctoral Research Associate in Neurophysics and Brain Dynamics* *ARC Centre of Excellence for Integrative Brain Function School of Physics Reference no. 1100/0616 * *Up to 3 positions studying multiscale, emergent, nonlinear, and critical phenomena in the brain* - *Full-time, fixed term for three years, with further offers available subject to performance, funding and need remuneration package: up to $112K pro rata p.a. which includes leave loading and up to 17% super)* - *The opportunity to work in the Brain Dynamics Group* Applications are sought for up to three Postdoctoral Research Associates (Level A) in the School of Physics and the Australian Research Council Centre of Excellence for Integrative Brain Function (CIBF). This is an opportunity to work in the Brain Dynamics Group of Professor Peter Robinson on projects in the area of his Laureate Fellowship on the Physical Brain and/or research in the area of the CIBF. His group also participates in the Cooperative Research Centre for Alertness, Safety, and Productivity, and the NHMRC-funded Centre for Research Excellence, Neurosleep, and has wide collaborations across the University, Australia, and internationally. The successful applicants will form a team to work on a wide variety of theoretical and computational topics in multiscale, emergent, nonlinear, and critical phenomena in the brain, starting from a physical perspective, with particular focus on nonlinear and stochastic dynamics of brain activity waves, modes, and networks. Key applications will be pursued under the laureate program that involve vision, seizures, imaging, and network evolution; others will be in the CIBF’s focal areas of attention, prediction, and decision. Successful applicants will also be expected to collaborate with interdisciplinary teams of theoreticians and experimentalists to advance these projects. *Essential criteria include:* - an undergraduate major in physics, applied mathematics, or similar field - a theoretical/computational PhD in physics, computational neuroscience, biological modelling, applied mathematics, engineering, or allied field; thesis must have at least been submitted for examination by the time of any interview for this position. - demonstrated ability to program in Matlab or C++ - proved research ability and evidence of self-motivation and research potential, including the ability to conduct research activities under limited supervision - publications in refereed journals *Desirable criteria include:* - familiarity with background areas such as quantum theory, fields, networks, Green functions, critical phenomena, wave theory, control systems, and/or nonlinear dynamics - demonstrated ability to relate theoretical predictions to experimental data and vice versa - experience in brain modelling or computational neuroscience - experience with neural field theory - experience with modelling physical or biological systems - experience in multidisciplinary teams - an ability to start work by 31 January 2017. Since a team is being built, the initial appointment process will begin by appointing the most suitable\person; the remaining people will then be assessed with regard to the areas that remain to be covered by the team as a whole, particularly as no one person is expected to possess the full range of skills described above. The position is full-time fixed term for three years, subject to the completion of a satisfactory probation period for new appointees and satisfactory performance as assessed at the end of the second year. Further offers may be available subject to performance, funding and need. Applications that make a case for a part-time position will also be considered, especially where this advances the Equal Opportunity goals of the University or if the applicant is of unusual merit. This appointment will be for three years with potential for extension subject to ongoing funding. The School of Physics supports a flexible working environment. Subject to visa restrictions, applications will be considered for either a full-time or part-time appointment to this position. -- You received this message because you are subscribed to the Google Groups "Centre for Complex Systems at The University of Sydney" group. To unsubscribe from this group and stop receiving emails from it, send an email to complexity-usyd+unsubscribe(a)googlegroups.com. To post to this group, send email to complexity-usyd(a)googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/complexity-usyd/8AC55DD7-57C5-49A3-B830-7… <https://groups.google.com/d/msgid/complexity-usyd/8AC55DD7-57C5-49A3-B830-7…> . For more options, visit https://groups.google.com/d/optout.

July 21, 2016

PhD Scholarships in complex networks & info theory at USyd

by Joseph Lizier

Dear all, (Apologies for cross-posting) Two PhD scholarships are available to study with Dr. Joseph Lizier in an Australian Research Council DECRA funded project ("Relating function of complex networks to structure using information theory"), within the Complex Systems Research Group in the Faculty of Engineering and IT at The University of Sydney. Both projects involve studying the relationship between complex network structure and dynamics, in terms of information processing. The approach will primarily use information theory (e.g. transfer entropy), with applications to neural data sets: 1. "Inferring information network structure from dynamics" -- http://bit.ly/1SZdnim 2. "Describing network and information processing co-development" -- http://bit.ly/24mp8Vq For any questions, please contact Dr. Lizier (joseph.lizier(a)sydney.edu.au) The closing date for applications is August 14, with the successful candidate to start by Feb 2017 or earlier. Please forward to any interested parties. Regards, --joe -- Dr. JOSEPH LIZIER | ARC DECRA Fellow | Senior Lecturer Complex Systems Research Group Faculty of Engineering and IT THE UNIVERSITY OF SYDNEY Rm 338A, Building J05 | The University of Sydney | NSW | 2006 T+61 2 9351 3208 | F+61 2 9351 3343 | M+61 408 186 901 E joseph.lizier(a)sydney.edu.au | W sydney.edu.au TW @jlizier | W lizier.me/joseph CRICOS 00026A This email plus any attachments to it are confidential. Any unauthorised use is strictly prohibited. If you receive this email in error, please delete it and any attachments. Please think of our environment and only print this e-mail if necessary.

July 18, 2016

Neuroscience Gateway Workshop at SFN 2016 meeting

by Ted Carnevale

Using the Neuroscience Gateway Portal for Parallel Simulation Saturday, Nov. 12 from 9 AM to noon at a site in downtown San Diego This workshop combines didactic presentations and hands-on instruction on how to use the Neuroscience Gateway Portal (NSG) for computationally intensive simulations and data analysis. NSG eliminates most technical and adminstrative barriers to using high performance computing resources, and even gives away free CPU time on parallel supercomputers. Software currently installed on NSG includes Brian, GENESIS, MOOSE, NEST, NEURON, PyNN, Freesurfer, and the Virtual Personalized Multimodal Connectome Pipeline. The registration deadline for this workshop is Friday Oct. 28, but you should sign up early because space is limited. See http://www.neuron.yale.edu/neuron/static/courses/nsg2016/nsg2016.html for more information and a link to the registration form. --Ted

July 18, 2016

NEURON course at SFN 2016 meeting

by Ted Carnevale

Using NEURON to Model Cells and Networks Friday, Nov. 11 from 9 AM to 5 PM at a site in downtown San Diego This course provides a practical introduction to building and using models of neurons and networks with NEURON. Covered topics include basic concepts, workflow for building and using models, speeding up simulations with parallel hardware from multicore personal computers to massively parallel supercomputers, using Python with NEURON, and modeling reactive diffusion with the RxD class. The registration deadline for this course is Friday Oct. 28, but you should sign up early because space is limited. See http://www.neuron.yale.edu/neuron/static/courses/sd2016/sd2016.html for more information and a link to the registration form. --Ted

July 18, 2016

Subject: Postdoctoral position in computational neuroscience

by Szabolcs Káli

Applications are invited for a postdoctoral research position in the Laboratory of Cerebral Cortex Research at the Institute of Experimental Medicine of the Hungarian Academy of Sciences. The institute, located in the center of Budapest, is dedicated to biomedical research in the field of neuroscience, hosts a variety of world-class research groups, and was awarded the title “Centre of Excellence” by the European Commission. The laboratory, led by Prof. Tamás Freund, employs a multidisciplinary approach to investigate the generation of normal and pathological patterns of network activity in the hippocampus, the roles of subcortical inputs in cortical information processing, and the molecular mechanisms of synaptic transmission. The successful candidate will work with Dr. Szabolcs Káli on developing detailed biophysical models of hippocampal neurons and circuits in the context of a large-scale initiative for collaborative work in computational neuroscience. The aim of the project is (1) to further the understanding of the dynamics and computational capabilities of cortical cells and networks, and (2) to create a generic framework and corresponding tools for the reproducible, collaborative development, simulation, and validation of data-driven neural models. The successful applicant is expected to contribute to both aspects of the project, developing morphologically and biophysically detailed models of different types of hippocampal neurons, and constructing anatomically and physiologically faithful models of hippocampal circuits. The work will take advantage of the neuroinformatics, brain simulation, and high-performance computing infrastructure developed by the European Human Brain Project, and the holder of this post is expected to make significant contributions to testing an integrative platform for model development, representation, optimization, and validation. He/she will work closely with experimentalists within the group who provide anatomical and physiological data, and is expected to coordinate model and tool development with collaborators at leading European institutions. The job also offers ample opportunities to develop and maintain contacts with members of the wider (experimental and modeling) community. We are looking for an individual holding a PhD in computational neuroscience (or related discipline), with a keen interest in applying theoretical and simulation tools to understanding neural information processing. The position requires an ability to work independently, but also as a member of a large international research team. The applicant should be able to communicate effectively in English, both in speech and in writing. We also expect the successful candidate to have experience in at least some of the following areas: - developing cellular or network models using neural simulation software (such as Neuron) - analysis of anatomical and/or electrophysiological data sets - programming (in Python, MATLAB, etc.) and collaborative software development - advanced parameter optimization methods (such as evolutionary algorithms) The position is available from September 1, 2016 (the exact starting date is flexible) until March 31, 2018 in the first instance, with the possibility of renewal. The salary is according to local scales for postdoctoral positions in EU-funded projects, and depends on relevant experience. Review of applications will start on August 10, but applications are accepted until the position is filled. Applications should contain a CV, a brief letter of interest, and two references, and should be sent to Szabolcs Káli (kali(a)koki.hu) Informal inquiries about the post are also welcome. -------------------------------------------------------- Szabolcs Káli Laboratory of Cerebral Cortex Research Institute of Experimental Medicine Hungarian Academy of Sciences H-1083 Budapest Szigony utca 43. Phone: +36-1-2109413 Fax: +36-1-2109412 E-mail: kali.szabolcs(a)koki.mta.hu www.koki.mta.hu

July 15, 2016

Call for participation "From Single Neurons to Brain Complexity and Human Behavior" Research Topic (Frontiers)

by PRWTOPAPA FWTEINH

Dear potential authors on the comp-neuro mailing list, [Apologies for cross-posting]In collaboration with Frontiers in Computational Neuroscience, we are organizing a Research Topic titled "From Single Neurons to Brain Complexity and Human Behavior", hosted by Constantinos Siettos, Jens Starke, Konstantinos Michmizos, Foteini Protopapa, Nikolaos Smyrnis. As host editor, I would like to encourage you to contribute to this topic. Please find more information below: Web site: http://frontiersin.org/Computa tional_Neuroscience/researchto pics/From_Single_Neurons_to_ Brain_Complexity_and_Human_ Behavior/5116Deadlines for this Research Topic are: Oct 01, 2016 (Abstract) and Feb 01, 2017 (Manuscript)Description: During brain data acquisition, from the neural to the behavioral scale, the targeted brain function is typically secluded from the influence of other brain functions. Such an approach results in data acquired at a single spatial and temporal scale of the brain and limits the analysis and understanding of the intrinsically multiscale and parallel brain functions. This calls for a paradigm shift from examining the brain as a monolithic structure to examining –and interacting with– the brain holistically. The proposed Research Topic aims to attract papers that will form a new computational infrastructure resource by combining novel integrative methods in Computational Neuroscience. Specifically, the research focus will be on: 1) The development of new methods and algorithms that can deal with multiscale dynamics and integrate data from synchronized behavioral and neural activity; and 2) The improved understanding of the neural dynamics in behavioral states. The understanding of brain functionality across its scales will have an unprecedented health, social and financial impact. The proposed Research Topic will host advanced mathematical modeling efforts and computational approaches that seek to understand how the interplay among cellular, anatomical and neuronal connectome empowers complex brain functions such as vision, attention, memory, learning and emotion. Tools include, but are not limited to, linear and nonlinear time series analysis of single unit recordings, EEG, MEG, fMRI and PET as well as multiscale modeling and analysis of neuronal systems dynamics, causal connectivity analysis (Granger-based, Phase Synchronization, Mutual Information, Transfer Entropy etc), manifold and machine learning methodologies for handling data complexity (PCA, ICA, ISOMAP, Diffusion Maps) etc. We seek to present research efforts that bridge the bottom-up and top-down approaches. A bottom-up research includes modelling the dynamics of neurons and/or networks of neurons to approximate the complex emergent behavior whereas a top-down research would try to reveal how macroscale phenomena observed in integrative EEG, MEG or fMRI signals can be used to infer about the brain organization and ultimately explain the underlying functional mechanisms. Specific areas of interest include but are not limited to: the reconstruction of functional networks that govern the information flow of the brain signals, the identification of distinct spatio-temporal patterns that can suggest the mechanisms of specific higher cognitive functions, and the modeling and analysis of resting-state activity. We will try to cover studies targeting the healthy brain as well as studies targeting neurologic and psychiatric disorders in adults (such as epilepsy, Parkinson’s disease Schizophrenia and other Psychotic disorders) and/or in children and adolescents (such as child epilepsy and autistic spectrum disorders). Let us know if you have any questions about this Research Topic. We look forward to hearing from you soon. With best regards, Constantinos Siettos (ksiet(a)mail.ntua.gr) Associate Professor at National Technical University of Athens (NTUA), Greece.and Foteini Protopapa, Ph.D. ( fwteini104(a)gmail.com ) Research Associate at EPIPSI, Greece.

July 14, 2016

4 PhD / PostDoc positions in the Institute of Neural Information Processing, Ulm University, Germany

by Daniel Braun

In the *Institute of Neural Information Processing* of the Faculty of Engineering, Computer Science and Psychology of Ulm University there will be *4 PhD / PostDoc positions in the field of Learning Systems* from October 2016 in the newly established research group on “Learning Systems”. The group is interested in the mathematical foundations of intelligent behavior in cognitive systems, including both biological and artificial systems, in particular the information-processing principles underlying learning and decision-making. This requires a combined theoretical and experimental approach. In our theoretical line of work we use methods from machine learning, statistics, physics, information theory and decision theory to investigate the effects of limited resources on learning and decision-making (“bounded rationality”). In our experimental line of work we investigate sensorimotor behavior in humans by using virtual reality technology and robotic interfaces to study learning and decision-making quantitatively under controlled conditions. This interdisciplinary approach unites aspects from both basic and applied research. On a basic level we aim at a quantitative understanding of embodied intelligence, in particular the emergence of cognition from sensorimotor interactions by processes of abstraction and structure learning. On an applied level we are interested in both autonomous robotic systems and human-machine-interactions, as sensorimotor learning and decision-making in artificial systems constitute a cutting-edge technical challenge. The research group is supported by the ERC-project BRISC (Bounded Rationality in Sensorimotor Coordination) https://erc.europa.eu/projects-and-results/erc-funded-projects/BRISC funded by the excellence programme of the European Research Council, in which we aim at a novel information-theoretic understanding of sensorimotor interactions in psychological and technical systems. Previous publications of the group can be found under http://www.kyb.tuebingen.mpg.de/research/rg/braun.html Ulm University with its more than 10,000 students is Baden-Württemberg’s youngest university. It offers attractive career prospects in a highly innovative research, teaching and work environment at the same time facilitating the reconciliation of work and family life. Embedded within the novel international “Cognitive Systems”-Master’s course, the research group “Learning Systems” is part of the university’s priority programme on human-machine-interaction. Beyond the university, there are plenty of opportunities to cooperate within the SFB Transregio 62 and with international partners in Great Britain and the United States. The applicants should have a strong mathematical background, hold a Diploma or Master’s degree in natural science, mathematics, economics, psychology, computer science, engineering or similar and have a keen interest in artificial and natural intelligence. The positions are paid according to German tariff TV-L E13. Exceptional candidates with a Bachelor’s degree can also be considered, albeit with an individual pay scale regulation. The University of Ulm is an equal opportunity employer: Handicapped individuals are strongly encouraged to apply, and so are women in areas in which they are underrepresented. The positions will be filled as soon as possible. Candidates should send a CV, a brief statement of interest and a copy of their highest degree to Prof. Dr. Dr. Daniel Alexander Braun daniel.braun(a)uni-ulm.de . -- Prof. Dr. Dr. Daniel Alexander Braun Institute of Neural Information Processing Faculty of Engineering, Computer Science and Psychology University of Ulm James-Franck-Ring D-89081 Ulm Germany phone: +49 (0)731 50 - 24151 <%2B49%20%280%29731%2050%20-%2024158> fax: +49 (0)731 50 - 24156 email: daniel.braun(a)uni-ulm.de

July 13, 2016

POSTDOCTORAL POSITION IN COMPUTATIONAL NEUROSCIENCE AT BROWN UNIVERSITY

by Wilson Truccolo

Applications for an NIH-funded post-doctoral position are invited for the Laboratory of Dr. Wilson Truccolo in the Department of Neuroscience at Brown University, Providence, RI, USA. The positions are for the development of data-driven stochastic models of multiscale neural dynamics in human epilepsy. Data consist of simultaneous intracortical microelectrode array recordings of ensembles of single neurons and local field potentials, as well as ECoGs, during seizure and non-seizure states in individuals with pharmacologically resistant epilepsy. The project involves a collaboration between the labs of Dr. Truccolo and Dr. Sydney Cash (Massachusetts General Hospital, Harvard Medical School, Boston). The ideal candidate will have a strong background in computational/theoretical neuroscience, modeling of stochastic neural dynamics and experiments involving closed-loop electrical stimulation. Related recent publications can be found on the Truccolo lab website ( http://www.truccololab.com/ <http://dl.dropbox.com/u/983891/Truccolo_home.htm>). Inquiries should be addressed to Dr. Truccolo (wilson_truccolo(a)brown.edu) Applications including a CV, statement of research interests, and the names and full contact details of three referees should be sent to wilson_truccolo(a)brown.edu. -- Wilson Truccolo, Ph.D. Pablo J. Salame '88 Goldman Sachs Assistant Professor of Computational Neuroscience Department of Neuroscience & Institute for Brain Science, Brown University Lab website: http://www.truccololab.com/

July 11, 2016

Ph.D. positions in computational neuroscience at ESI

by Martin Vinck

The laboratory of Dr. Martin Vinck at the *Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society *is seeking candidates for Ph.D. positions. Students will work on two classes of problems. First, we aim to solve various methodological / neurostatistical problems for offline and on-line, closed-loop analysis of multivariate neuroscience datasets. Second, we are developing models of visual cortex in order to test specific hypotheses about the relationship between cortical dynamics and computation. PhD students will work together with experimental neuroscientists and apply methods and models to experimental datasets from primate and rodent animal models, including electrophysiological and calcium imaging data. We are primarily looking for students with training in a quantitative discipline (physics, engineering, computer science etc.). Interested candidates are invited to send their application materials in electronic form (PDF format) to martin.vinck(a)esi-frankfurt.de Applications should contain a letter of intent, a detailed curriculum vitae, lists of university courses completed with marks obtained, and the names of at least two scientists who can give references. The advertisement will be valid until positions are filled. Dr. Martin Vinck martin.vinck(a)esi-frankfurt.de Research Group Leader Ernst Struengmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society Deutschordenstr. 46, D-60528 Frankfurt am Main, Germany

July 9, 2016

PhD/postdoc positions at Ernst Struengmann Institute for Neuroscience

by Martin Vinck

Our laboratory at the Ernst Struengmann Institute for Neuroscience in Cooperation with Max Planck Society is seeking candidates for Postdoc and Ph.D. positions. Projects involve the application of parallel, large-scale electrophysiological recording techniques of single units and EEG in combination with closed-loop optogenetic manipulation methods to investigate mechanisms of information encoding and transmission in mice brains. We are particularly interested in the way in which the brain efficiently encodes information, and the way in which sensory predictions established in higher areas influence sensory representations in earlier sensory areas. We are furthermore interested in investigating the role of GABAergic interneurons in selective attention and neuronal oscillations. We address these questions using laminar recordings in combination with optogenetics in mice, as well as through the development of novel tools for the quantitative analysis of large-scale electrophysiological data. Within the ESI, tight collaborations exist with the lab of Prof. Dr. Pascal Fries. Because we are searching for members that can strengthen an interdisciplinary team, we are encouraging students/researchers with a background either in biological/medical sciences or in physics/engineering/mathematics/etc. to apply. The ideal PhD or postdoc candidate has previous experience and strengths either in 1) performing hands-on experimental work and electrophysiological recordings or 2) hardware engineering and quantitative analysis of large-scale data. We are searching for applicants with good communication skills and a high commitment and curiosity about neuroscientific questions. Interested candidates are invited to send their application materials in electronic form (PDF format) to martin.vinck(a)esi-frankfurt.de Applications should contain a letter of intent, a detailed curriculum vitae, lists of university courses completed with marks obtained (only for PhD candidates), and the names of at least two scientists who can give references. The advertisement will be valid until positions are filled. Dr. Martin Vinck martin.vinck(a)esi-frankfurt.de Research Group Leader Ernst Struengmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society Deutschordenstr. 46, D-60528 Frankfurt am Main, Germany

July 9, 2016

Tenured Junior Research/Teaching Faculty Position in Computational Neuroscience at Ecole Normale Superieure in Paris, France

by Boris Gutkin

Tenured Junior Research/Teaching Faculty Position in Computational Neuroscience at Ecole Normale Superieure in Paris, France A tenured junior faculty position is expected to open in the Department of Cognitive Studies (DEC) at the ENS-Paris. The position profile is broad, focusing on computational neuroscience. The recruited candidate will join the Group for Neural Theory, which is part of the Laboratory for Cognitive Neuroscience,DEC, ENS Paris. The candidate is expected to have a strong background in theoretical neuroscience and/or computational neuroscience. The candidate is expected to develop an active research program and integrate into the GNT. Teaching in neuroscience and computational neuroscience shall be done at the ENS within the cognitive sciences masters program. The Laboratory for Cognitive Neuroscience provides opportunities to develop a collaborative research program in computational neuroscience of decision making. Further collaborative opportunities exist within the department and local laboratories involved in electrophysiology and/or psychophysics. The next cycle of recruitment for a Junior Faculty position in computational neuroscience shall be announced in the spring of 2017. In order to apply for the position candidates need to pre-qualify with the National University Council. The deadline for the pre-qualification is in October 2016. Help with putting together the application shall be given to potential candidates who should contact mc.comp.gnt(a)gmail.com

July 8, 2016

Special Issue of Applied Soft Computing on Non-iterative Approaches in Learning

by Teng Teck Hou

Special Issue of Applied Soft Computing (Elsevier) (Impact Factor: 2.8) Submission is open now Special Issue on Non-iterative Approaches in Learning (Includes comparisons with iterative methods) Call for Papers http://www.journals.elsevier.com/applied-soft-computing/call-for-papers/spec ial-issue-on-non-iterative-approaches-in-learning-includ/ Optimization, which plays a central role in learning, has received considerable attention from academics, researchers, and domain workers. Many optimization problems in machine learning are solved by iterative methods which generate a sequence of improving approximated solutions with some termination criteria. These methods usually suffer from low convergence rate and are sensitive to parameter settings (such as learning rate/step size, maximum number of iterations). On the other hand, non-iterative solutions, which are usually presented in closed-form manner, are in general computationally faster than iterative solutions. However, comparative studies with iterative methods are also welcome. The main focus of this special issue is to present the recent advances in non-iterative solutions in learning. Original contributions and surveys are welcome. The special issue aims to promote non-iterative concepts in the field of learning. Even though non-iterative methods have attracted much attention in recent years, there exists a performance gap when compared with older methods and other competing paradigms. This special issue aims to bridge this gap. Besides the dissemination of the latest research results on non-iterative algorithms, it is also expected that this special issue will cover some industrial applications, present some new ideas and identify directions for future studies. The topics of the special issue include, but are not limited to: * Methods with and without randomization * Regression, classification and time series * Kernel methods such as kernel ridge regression, kernel adaptive filters, etc. * Feedforward, recurrent, multilayer, deep and other structures. * Ensemble learning * Moore-Penrose pseudo inverse, SVD and other solution procedures. * Non-iterative methods for large-scale problems with and without kernels * Theoretical analysis of non-iterative methods * Comparative studies with competing iterative methods * Applications of non-iterative solutions in domains such as power systems, biomedical, finance, signal processing, big data and all other areas Submission format and Guidelines Papers will be evaluated based on their originality, presentation, relevance and contribution to the development of non-iterative methods, as well as their suitability and the quality in terms of both technical contribution and writing. The submitted papers must be written in good English and describe original research which has not been published nor is currently under review by other journals or conferences. If used, the previously published conference papers should be clearly identified by the authors (at the submission stage) and an explanation should be provided how such papers have been extended to be considered for this special issue. Guest Editors will make an initial determination on the suitability and scope of all submissions. Papers that either lack originality, clarity in presentation or fall outside the scope of the special issue will not be sent for review and the authors will be promptly informed of such cases. Author guidelines for preparation of manuscript can be found at http://www.journals.elsevier.com/applied-soft-computing/ Manuscripts should be submitted online at: http://ees.elsevier.com/asoc/ Applied Soft Computing Journal is well indexed. Its impact factors are 2.8 (2 years) and 3.2 (5 years). Important dates Manuscript submission: 15th Aug 2016 Revised version submission: 31st Jan 2017 Acceptance notification: 31st March 2017 Expected Publication: Mid 2017 Guest Editors Dr P N Suganthan, Nanyang Technological University, Singapore. epnsugan(a)ntu.edu.sg Prof. Sushmita Mitra, Indian Statistical Institute, India. sushmita(a)isical.ac.in Dr Ivan Tyukin, Department of Mathematics, University of Leicester, UK. I.Tyukin(a)le.ac.uk

July 8, 2016

IEEE CIDM 2016

by Friedhelm Schwenker

CALL FOR PAPERS Paper Submission Deadline: July 18, 2016 IEEE CIDM 2016 IEEE Symposium on Computational Intelligence and Data Mining December 6-9, 2016, Athens, Greece SSCI 2016:http://ssci2016.cs.surrey.ac.uk/CIDM.htm CIDM 2016:http://neuro.informatik.uni-ulm.de/CIDM2016/ IEEE CIDM 2016 organized by the IEEE Computational Intelligence Society Data Mining Technical Committee is part (one of 30 symposia) of the IEEE Symposium Series of Computational Intelligence (IEEE SSCI 2016). IEEE CIDM 2016 will bring together researchers and practitioners from around the world to discuss the latest advances in the field of computational intelligence applied to data mining and will act as a major forum for the presentation of recent results in theory, algorithms, systems and applications. Topics related to all aspects of data mining, such as theories, algorithms, systems and applications, particularly those based on computational intelligence technologies, are welcome; these include, but are not limited to: • Neural networks for data mining • Evolutionary algorithms for data mining • Fuzzy sets for data mining • Data mining with soft computing • Foundations of data mining • Mining with big data • Classification, Clustering, Regression • Association • Feature learning and feature engineering • Machine learning algorithms • Multimedia data mining • Text mining • Link and graph mining • Social media mining • Collaborative filtering • Crowd sourcing • Personalization • Security, privacy and social impact of data mining • Data mining applications Important Dates • Paper submission: July 18, 2016 • Notification to authors: September 12, 2016 • Final submission: October 10, 2016 • Early registration: October 10, 2016 Co-Chairs Carlotta Domeniconi, Georg Mason University, USA Friedhelm Schwenker, Ulm University, Germany Zhi-Hua Zhou, Nanjing University, China -- PD Dr. Friedhelm Schwenker University of Ulm Institute of Neural Information Processing D-89069 Ulm, Germany phone: +49-731-50-24159 fax: +49-731-50-24156 email: friedhelm.schwenker(a)uni-ulm.de www: http://www.uni-ulm.de/in/neuroinformatik/mitarbeiter/f-schwenker.html

July 6, 2016

Postdoctoral position in Computational Neuroscience at IIT (Italy)

by Stefano Panzeri

(apologies for cross posting) We are seeking candidates for a postdoctoral position in computational neuroscience in the Neural Computation Laboratory at the IIT https://www.iit.it/research/lines/neural-computation directed by Stefano Panzeri and located in Rovereto (Trento), Italy. This laboratory aims to crack the neural code using neural network modeling and computational analyses of neurophysiological experiments. The laboratory offers a range of strongly interdisciplinary expertise in computational neuroscience, including information theory and other types of advanced single-trial neural analyses, advanced spectral analysis, and biophysically plausible neural network modeling. The successful candidate will develop and use tools for the analysis of large-scale simultaneous recordings of the spiking activity of cells in the cortex to understand how populations of neurons carry information. The successful candidate would have the opportunity to benefit from an extensive set of existing collaborations with leading neurophysiological laboratories, including those of Nikos Logothetis at Max Planck Tubingen (collaborating on oscillations, sensory information coding and neuromodulation), Tommaso Fellin at IIT (collaborating on Optogenetics, Neurophysiology and Neural coding), Mathew Diamond at SISSA (collaborating on the behavioral impact of information carried by spike timing), and Christopher Harvey at Harvard Medical School (collaborating on neural population dynamics and decision making). We are willing to consider candidates interested in any of the aspects of neural coding of interest to the laboratory. Candidates must hold a PhD in a numerate scientific discipline. They must be highly motivated and creative individuals who want to work in a dynamic, multi-disciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists. For reference to recent work of the lab please see Safaai, H., et al (2015) Modelling the effect of Locus Coeruleous firing on single trial cortical state dynamics and sensory processing. Proc. Natl. Acad. Sci. USA 112(41): 12834–12839 Zuo Y, et al (2015) Spike timing and spike rate make complementary contributions to perceptual decisions in rat S1 and S2 cortex. Current Biology 25: 357-363 Besserve M, Lowe S, Logothetis NK, Scholkopf B, Panzeri S (2015) Shifts of gamma phase across primary visual cortical sites reflect dynamic stimulus- modulated information transfer. PLoS Biology 13(9): e1002257. doi:10.1371/journal.pbio.1002257 Panzeri, S, et al (2015) Neural population coding: combining insights from microscopic and mass signals, Trends in Cognitive Sciences 19: 162-172. Interested candidates should contact Dr. Stefano Panzeri ( stefano.panzeri(a)iit.it <https://mail.iit.it/owa/redir.aspx?C=oajclq8rPE6FcMCJ-lI1Hsu55NFH69II9YBluB…>), emailing their CV, a brief statement of research interests, and names and email addresses of 2 or 3 referees.

July 5, 2016

Associate Professor Position in Data Sciences (Big Data) at the Norwegian University of Life Sciences

by Hans Ekkehard Plesser

Dear Colleagues! The Department of Mathematical Sciences and Technology (IMT) at the Norwegian University of Life Sciences (NMBU) has a permanent, full-time position available for an Associate Professor in Data Sciences (Big Data). The position is part of the University's programme for the recruitment of top researchers, which aims to recruit young researchers with great potential for NMBU. The position will include: • one PhD Position (3 years) • NOK 0.25 million in operating funds Application deadline is 1 October 2016. For details, please see https://www.jobbnorge.no/en/available-jobs/job/127472/associate-professor-i… Best, Hans Ekkehard Plesser -- Dr. Hans Ekkehard Plesser, Associate Professor Section Head Dept. of Mathematical Sciences and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no Home http://arken.umb.no/~plesse

July 5, 2016

2 open PhD positions at TU Dresden, Germany

by Stefan Kiebel

The Department of Psychology at the TU Dresden (Chair of Neuroimaging, PI: Stefan Kiebel) is looking for two PhD students. One of the PhD student positions is in experimental cognitive neuroscience, and one is in computational neuroscience. Both PhD positions will be working at the interface between computational and experimental neuroimaging research in cognitive control and goal-directed action sequences. Detailed information about both positions can be found at: http://tiny.cc/8ii4by Both positions are part of the DFG-funded CRC 940 'volition and cognitive control' (http://www.sfb940.de/en/home.html) The CRC was established in 2012 and will be funded for the next four years. The CRC aims at identifying the cognitive and neuronal mechanism, which underlie the volitional control of goal-directed actions as well as its dysfunctions in selected mental disorders. PhD position 1: The candidate will work as a member of a team in the CRC940-Project A9 on computational modelling of goal-directed actions and explaining dynamics in cognitive control in terms of variations in meta-control parameters. In this project, neuroimaging (fMRI and EEG) experiments will be used to test hypotheses derived using advanced Bayesian models of goal-reaching over multiple trials. http://tiny.cc/8ii4by (PhD position Cognitive Neuroscience) PhD position 2: The candidate will work as a member of a team in the CRC940-Project Z2 on advanced computational modelling of functional magnetic resonance imaging and electroencephalography data. In this project, advanced modelling techniques will be developed and extended to enable testing novel experimental hypotheses using fMRI and EEG. http://tiny.cc/8ii4by (PhD position Computational Neuroscience) --> The application deadline for both positions is the 14th of July. -- Prof. Dr. Stefan Kiebel Technische Universität Dresden School of Science Department of Psychology 01062 Dresden, Germany Tel.: +49 (351) 463-43145 Fax: +49 (351) 463-43147

July 5, 2016

Research Engineer position - Axion/Columbia

by Robert Butera

Passing this on for a colleague - contact the email address in the job ad for more information. RESEARCH ENGINEER Axion BioSystems, Inc. is a life science company located in Atlanta, GA. We design, develop and manufacture instrumentation used for the precise monitoring and control of excitable cells. Axion’s products are used by pharmaceutical and biotech companies, governmental agencies, and universities for drug safety, drug discovery, and disease modeling assays. We are currently seeking an energetic scientist to lead Axion’s efforts in a collaboration with the Institute for Genomic Medicine (IGM) at Columbia University. The objective of the collaboration is to interrogate the genetic mechanisms of epilepsy with multiwell microelectode array (MEA) technology. The newly developed IGM is an integral part of Columbia University’s Precision Medicine Initiative. As part of this Initiative, the IGM performs comprehensive genomic analyses on more than 10,000 patient genomes per year in order to identify new therapeutic targets of neurodevelopmental disorders including epilepsy. In order to understand how the implicated mutation affects disease, the laboratories of David Goldstein and Michael Boland use both primary neurons from mouse models of epilepsy and neurons derived from human induced pluripotent stem cells to study the effects of epilepsy gene mutations on neurodevelopment and neural network behavior. The selected individual will contribute analytical and electrophysiological expertise to complement a highly skilled team of molecular biologists. JOB FUNCTIONS: • Execution of neurophysiological experiments with the multiwell MEA platform. The ability to interpret or debug experiments in real-time is important, such as distinguishing signal from noise or artifacts. • Analysis of large electrophysiological data sets, primarily from the multiwell MEA platform, but also including complementary in vivo data. • Develop experimental hypotheses and identify expected results. Must confirm results through independent analysis and investigate any discrepancies that appear, while understanding the strengths and limitations of model systems (i.e., cellular vs. animal). • Drive innovation of the multiwell MEA assay, leading to new experimental methods and analytical techniques. • Work well in a fast-paced, collaborative environment at Columbia University in New York City, with an ability to communicate well with the Axion team in Atlanta. REQUIREMENTS: • PhD in neuroscience or neuroengineering. A recent post-doc experience is a plus. • Hands-on research experience with electrophysiology techniques. Specific experience with MEA technology is desired. • Biostatistical and data analysis experience. • Experience with software analysis tools such as MATLAB or MiniTAB. • Attention to detail with good documentation and communication skills. • U.S Citizenship or permanent residency required. USEFUL KNOWLEDGE: The following are not required, but will enhance an applicant’s candidacy. • Hands on experience in general biological protocols including knowledge of primary cell dissociation, cell culture protocols, CRISPR, gene editing, and basic molecular techniques. • Experience with screening technologies, such as high-throughput patch clamp or high content imaging. • Knowledge of pharmacology and neurotoxicity research. CONTACT INFORMATION: If you are interested in this position, please send your resume and cover letter to careers(a)axionbio.com

July 1, 2016

CFP: Advances in Biologically Inspired Reservoir Computing

by John Butcher

Dear all, We are seeking papers for a special issue on Reservoir Computing, paper submission deadline is 31st September 2016. For more details see below and http://ispac.diet.uniroma1.it/cognitive-computation-special-issue/ Many thanks *Scope and motivation* *Reservoir computing is a family of techniques for training and analyzing recurrent neural networks, wherein the recurrent portion of the network is assigned before the training process, typically via stochastic assignment of its weights. The non-linear reservoir acts as a high-dimensional kernel space, which generates complex dynamics characterized by sharp transitions between ordered and chaotic regimes. The behavior of this model emulates the functioning of many biological (complex) systems, among which the brain.* *Driven by the conceptual simplicity of the reservoir and by links with neuroscience, computer science and systems’ theory, researchers have achieved remarkable breakthroughs, both in theory and in practice. These include dynamical models for explaining the working behavior of reservoirs, unsupervised strategies for the adaptation of the network, and the design of unconventional computing architectures for its execution.* *The recent upsurge of interest in fully adaptable recurrent networks, far from shifting the attention from the field, has brought renewed interest in reservoir computing models. In our era of extreme computational power and sophisticated problems, it is essential to understand the limits and the potentialities of simple (both deterministic and random) collections of processing units. For this reason, many fundamental questions remain open, including the design of optimal task-dependent reservoirs in a stable fashion, novel investigations on the memory and power capabilities of reservoir devices, and their applicability in an ever-increasing range of domains.* *In light of this, the aim of this special issue is to provide a unified platform for bringing forth and advancing the state-of-the-art in reservoir computing approaches. Researchers are invited to submit innovative works on the theory and implementation of this family of techniques, in order to provide an up-to-date overview on the field.* *Topics* *The topics of interest to be covered by this Special Issue include, but are not limited to:* *-Theoretical analyses on the computational power of reservoir computing.* *-Deep reservoir models.* *-Techniques for the automatic adaptation of the reservoir and the readout.* *-Supervised, unsupervised and semi-supervised training criteria.* *-Non-conventional substrates for the implementations of reservoirs.* *-Parallel and distributed algorithms for reservoir computing.* *-Comparisons between reservoir computing and standard (deep) neural networks.* *-Reservoir computing for reinforcement learning problems.* *-Fundamental links between reservoir computing and neuroscientific findings.* *-Investigation of reservoir dynamic in a phase space of reduced dimensionality.* *-Applicative papers in all areas (including robotics, industrial control, etc.) are welcome, as well as outstanding surveys on specific aspects of the field.* -- Dr John Butcher Neuroscience Research Associate School of Life Sciences Huxley Building Keele University UK ST5 5BG http://www.keele.ac.uk/lifesci/people/researchassistants/johnbutcher/

July 1, 2016

Postdoctoral Scholar in memory neuroscience using computational/modelling approach

by Sze Chai Kwok

Dear all, I am looking to employ a post-doc in memory neuroscience using computational/modelling approach <http://icn.ecnu.edu.cn/Data/View/1066>. Please spread the word to interested parties. Thank you. *Postdoctoral Scholar in **memory neuroscience**using computational/modelling approach * ** A postdoctoral position is available in the Laboratory of Attention and Memory (PI: Sze Chai Kwok) in the Institute of Cognitive Neuroscience at East China Normal University (ECNU) in Shanghai, China. Research will study the theoretical and neurobiological basis of episodic memory. Focus will be on the development of cognitive and/or biophysical network models using cross-species data from both human fMRI (with TMS) and ECoG, extra-cellular LFP / whole-cell recordings (combined with ire/reversible intervention) in awake monkeys performing analogous memory tasks using naturalistic stimuli such as videos. Candidates are expected to take advantage of the Lab’s unique experimental expertise in both humans and macaques. The Lab has active collaboration with groups in UCL, Lyon Neuroscience Research Center, UCLA, and University of Oxford. Appointment is contingent upon completion of a PhD in computer science, mathematics, physics or other quantitative disciplines. Relevant research experience in modelling would be preferable. Salary is commensurate with experience. This postdoc appointment will run for initially a period of two years with a flexible starting date. Interested candidates should initiate informal inquiries and/or send a CV, a statement of research interests, representative first-author publications (in one single PDF), and references to: sk5899(a)nyu.edu <mailto:sk5899@nyu.edu>. Applications are accepted beginning now, and will continue until the position is filled. Sze Chai Kwok, DPhil Associate Professor at East China Normal University Associated faculty at NYU-Shanghai University (<http://shanghai.nyu.edu/research/brain/faculty/sze-chai-kwok>http://shanghai.nyu.edu/research/brain/faculty/sze-chai-kwok) -- ------------------------------ 5x1000 PER LA NOSTRA RICERCA SANITARIA <http://www.hsantalucia.it/modules.php?name=News&file=article&sid=999> la tua firma, il nostro codice fiscale: 97138260589 <http://www.hsantalucia.it/modules.php?name=News&file=article&sid=999> ------------------------------ Le informazioni contenute in questo messaggio sono riservate e destinate esclusivamente alla/e persona/e o all'ente sopra indicati. E' vietato ai soggetti diversi dai destinatari qualsiasi uso, copia e diffusione di quanto in esso contenuto sia ai sensi dell'art. 616 del codice penale che ai sensi della L. 196/03 (privacy). Se questo messaggio Vi e' pervenuto per errore, Vi preghiamo di non leggerlo, di distruggerlo e di comunicarci l'errore via e-mail o telefonando al numero +39 06515011. The information contained in this message is confidential and is intended for the exclusive use of the person(s) or company(s) above addessed. If you are not the intended recipient(s), you are expressly prohibited from using, copying and distributing this message or any part of it in accordance with art. 616 of the criminal code and the law 196/03 (privacy). If you receive this message please don't read it but destroy it and then inform us by e-mail or by phone - number +39 06515011.

July 1, 2016

PhD positions at the CTNSC-UniFe , Ferrara

by Emma Maggiolini

The Center for Translational Neurophysiology of Speech and Communication (CTNSC) at the Istituto Italiano di Tecnologia (IIT) is looking for up to 4 highly motivated, full-time PhD students to work in the core research areas of the Center. The PhD student will work in Ferrara, in an international and multidisciplinary team including biomedical engineers, biologists, computer scientists, psychologists and medical doctors. The PhD positions will cover the following core areas of CTNSC. DEADLINE: 5TH AUGUST 2016 CTNSC Info [ITA/ENG]: https://www.iit.it/centers/ctnsc-unife PhD page [ITA/ENG]: http://www.unife.it/studenti/dottorato/concorsi/selection How to participate to the selection [ITA/ENG]:http://www.unife.it/studenti/dottorato/modulistica/concorsi/32-ciclo/neurosciences.pdf * Functional investigation of innovative neural interfaces Evidences show that using electrophysiological techniques is possible to extract information about brain processes and then translate these signals into commands that could be used to recover the lost capabilities. The purpose of the project is to investigate the in-vivo performance of novel devices - both in-house developed or obtained from collaborating laboratories - with a focus on i) enhanced capability to record neural signals; ii) large charge transfer capability to enhance the stimulation performance and iii) small size to minimize inflammatory reaction and gliosis. The candidate will be involved in the development of a stable and functional interface between living neural tissue and probes in rat model. Techniques: in-vivo single-unit recording and epicortical recording , histological techniques and image analysis, microscopy techniques and data analysis. Requirements: The candidate should have a background in one or more of the following fields: biology, medicine, pharmacology or related disciplines. Programming experience is appreciated but not mandatory. Familiarity with electrophysiological and/or microscopy techniques is of advantage. Contacts: Dr. Emma Maggiolini: emma.maggiolini(a)iit.it<mailto:emma.maggiolini@iit.it> Prof. Luciano Fadiga: luciano.fadiga(a)iit.it<mailto:luciano.fadiga@iit.it> * Animal neurophysiology investigation of sensorimotor functions The discovery of mirror and canonical neurons in monkey premotor and parietal cortex motivated a number of studies on how sensorimotor transformations in the brain may support understanding of action performed by conspecifics. This still constitute a fundamental area of research which is necessary to unravel the basic mechanisms of sensorimotor sharing during social interaction. The candidate working in this core area will investigate, in animal models, the neuronal activity of different (motor and somatosensory) cortical regions, pointing out their topographic organization as well as their role during observation, planning and execution of particular motor acts. Techniques: multidisciplinary approach involving behavioral testing, electrophysiological techniques (intracortical microstimulation, single-unit recording, field potentials recording, electromyography) and histological evaluations. Requirements: The candidate must have a background in the biological fields (biology, medicine, pharmacy and similar). At the end of the three-year period, the Ph.D. student will obtain deep knowledge and experience on in vivo neuroscience. Contacts: Dr. Riccardo Viaro: riccardo.viaro(a)iit.it<mailto:riccardo.viaro@iit.it> Prof. Luciano Fadiga: luciano.fadiga(a)iit.it<mailto:luciano.fadiga@iit.it> * Brain- and multimodal signal- based speech recognition Our approach to speech recognition is an "analysis by synthesis" approach which assumes that in order to recognize speech we need to understand the causal process (i.e., the speech production process) that stems from brain activity and, through coordinated movements of the vocal tract articulators, produces speech sounds. Such approach is largely motivated by work on speech perception carried out at CTNSC and serves two goals. The first goal is to build automatic speech recognition systems that, as humans do, work in very challenging scenarios (e.g., in the so called "cocktail party" scenario) and are able to learn how to recognize speech without relying on huge amount of carefully annotated speech data (as opposed to "data hungry" current recognition systems). The second goal is to recognize speech from one or more modalities that are within the speech production process, e.g., from brain signal or from visual and kinematic signals of the face and the vocal tract. Techniques: Machine learning, deep neural network, multimodal signal processing. Requirements: The successful candidate will have a degree in computer science bioengineering, physics or related disciplines. A background in machine learning and in speech and language processing. Contacts: Dr. Leonardo Badino: leonardo.badino(a)iit.it<mailto:leonardo.badino@iit.it> Prof. Luciano Fadiga: luciano.fadiga(a)iit.it<mailto:luciano.fadiga@iit.it> * Human Neurophysiology investigation of speech and communication abilities by means of micro-electrocorticography Historically, the study of speech processing has emphasized a strong link between auditory perceptual input and motor production output. The main aim of this area is to describe the neural systems involved in this sensorimotor representation linking speech perception and production. To this purpose, we use high-density surface microelectrodes for electrocorticography (micro-ECoG) to record electrical signals directly from the cortical surface in patients during awake surgery for low-grade glioma resection. Micro-ECoG is an important electrophysiological signal recording technique that combines high temporal resolution with good spatial localization. Techniques: Micro-ECoG, direct brain electrical stimulation, functional electrical mapping. Requirements: Applicants are expected to have a degree in biomedical engineering or basic/applied/health sciences. Requirements include a knowledge of neural signal processing and/or neuroimaging skills. Contact: Dr. Luciano Simone: luciano.simone(a)unife.it<mailto:luciano.simone@unife.it> Prof. Luciano Fadiga: luciano.fadiga(a)iit.it<mailto:luciano.fadiga@iit.it> * Human Neurophysiology investigation of speech and sensorimotor communication abilities by means of non-invasive techniques The neural mechanisms underlying speech and sensorimotor communication abilities, during real-life social encounters are mostly unknown. In the classic motor control frame of reference, individuals can be conceived as proactively building models of their action and of their sensory consequence. During interaction, these sensorimotor models can be extended to the social space whereby the control signal becomes the negotiated behavior of other people. The candidate will help in mapping the brain activities responsible for the emergence of such a shared behavior, in the domain of speech (phonological level) or action (upper arm movements). These experiments will inform the next generation of biologically inspired automatic communication recognition systems, essential to augment natural human-human coordination and promote the future of efficient human-robot interaction. Techniques: Electroencephalography (EEG), Electromyography (EMG), body motion kinematics (MoCap), Transcranial Magnetic Stimulation (TMS), transcranial Direct (tDCs) and Alternate (tACs) current stimulation. Requirements: The successful candidate will have a background in neuroscience, experimental psychology, computer science or engineering. Programming skills as well as a strong interest in cognitive neuroscience are fundamental. Electroencephalographic and kinematic data analyses skills are a plus. Contact: Dr. Alessandro D'Ausilio: alessandro.dausilio(a)iit.it<mailto:alessandro.dausilio@iit.it> Prof. Luciano Fadiga: luciano.fadiga(a)iit.it<mailto:luciano.fadiga@iit.it> [Description: cid:image001.jpg@01CC9EC9.BA36CB30] Emma Maggiolini, PhD IIT@unife, Center for Translational Neurophysiology Via Fossato di Mortara 17/19, 44121 Ferrara, Italy Tel. +39 0532 455983 SKYPE ID: lilmay75 e-mail: emma.maggiolini(a)iit.it<mailto:emma.maggiolini@iit.it> www.iit.it<http://www.iit.it/>

June 30, 2016

CNS2016 tutorial on detailed neuronal modelling

by Ben TN

On Saturday July 2 there is an exciting tutorial at the yearly CNS meeting titled: “Detailed modeling of structure and function at the cellular level”. This tutorial will be given by Dr. Ben Torben-Nielsen and Dr. Yann Le Franc. If you are at the CNS meeting, this is your chance to get expert insights into the wondrous world of dendrites and axons, their shape and dynamics emerging on them. The tutorial consists of two parts. In the morning session, Dr. Torben-Nielsen will cover the study of neuronal morphologies; why this is important and how we can study them through analysis and synthesis. In the afternoon session, Dr. Yann Le Franc will discuss the dynamics of ionic conductances. This session focusses on the basics of compartmental modelling and the existing neuroinformatics tools used to advance your workflow in dealing with design, implementation and analysis of detailed models. Both sessions will contain a hands on component. Please bring a laptop with Python/Scipy/Numpy/Matplotlib installed on it. For windows and mac users, we recommended Anaconda (https://www.continuum.io/why-anaconda) as it is an easy way to install all required Python packages. In the afternoon session, we will also use the NEURON simulator (https://www.neuron.yale.edu/neuron/) Please install this package as well with the Python extensions. We can provide guidelines on the installation of these packages during the breaks. Also, if you have structural data of neurons and do not know how to start to analyse them, please bring them along and we can help you out! Kind regards, Ben Dr. Ben Torben-Nielsen Senior Lecturer (Assistant professor) Biocomputation Group University of Hertfordshire, UK

June 30, 2016

CITEC Summer School 2016 on Adaptive Systems - CALL FOR PARTICIPATION

by elisabetta chicca

-------------------------------------------------------------------------------------------------------------- CALL FOR PARTICIPATION *CITEC Summer School 2016 on Adaptive Systems* CITEC, Bielefeld University, Germany, 27th-30th of September 2016 ------------------------------------------------------------------------------------------------------------- Dear young researchers, The CITEC Summer School 2016 is dedicated to the topic of Adaptive Systems: https://www.cit-ec.de/summerschool Adaptivity is the key for coping with tasks or environments whose properties cannot be completely known beforehand - a frequent characteristic of real world situations challenging artificial agents, real robots or biological organisms alike. We offer you an interdisciplary mesh of courses held by an interdisciplinary team of researchers from the Excellence Center Cognitive Interaction Technology to acquaint you with current ideas and research about adaptivity, its foundations, analysis and its synthesis in artificial systems. This year's topic is organized into four major thematic areas: (A) Adaptive Motion (B) Multimodal Learning and Social Interaction (C) Deep Approaches to Relevance Learning (D) Embodiment and Neuromorpic Learning Systems Most of the courses provide the opportunity for hands-on experience, involving experiments or data sets captured in CITEC research labs. You are asked to choose one out of this four. They are complemented by talks of leading invited and local experts. Invited speakers include: - *Ralph Etienne-Cummings**, *Johns Hopkins University, USA - *Kerstin Fischer**, *University of Southern Denmark - *Christian Igel*, University of Copenhagen, Denmark - *Andrew B. Schwartz*, University of Pittsburgh, USA Beyond the courses and the talks of the speakers, attendance will provide you with ample opportunities for discussions, exchange of ideas with your peers and the participating researchers, and for learning more about CITEC. The Summer School continues a series of highly successful CITEC Summer Schools started in 2010 and covering the topics of *The Structure of Cognitive Motion: From Analysis to Synthesis* (2010), *Mechanisms of Attention - From Experimental Studies to Technical Systems* (2011), *Verbal and Non-verbal Interaction: From Experiments to Implementation (*2012), and *Continuous Learning in Living and Artificial Systems* (2013) so far. To apply visit https://www.cit-ec.de/summerschool/application and indicate your area of choice from the above area list (A)-(D). Applications will be open at least until July 29th. For more information, visit http://www.cit-ec.de/summerschool Contact us for questions: summerschool(a)cit-ec.uni-bielefeld.de

June 30, 2016

POSTDOCTORAL POSITION IN COMPUTATIONAL NEUROSCIENCE AT BROWN UNIVERSITY

by Wilson Truccolo

Applications for an NIH-funded post-doctoral position are invited for the Laboratory of Dr. Wilson Truccolo in the Department of Neuroscience at Brown University, Providence, RI, USA. The positions are for the development of data-driven stochastic models of multiscale neural dynamics in human epilepsy. Data consist of simultaneous intracortical microelectrode array recordings of ensembles of single neurons and local field potentials, as well as ECoGs, during seizure and non-seizure states in individuals with pharmacologically resistant epilepsy. The project involves a collaboration between the labs of Dr. Truccolo and Dr. Sydney Cash (Massachusetts General Hospital, Harvard Medical School, Boston). The ideal candidate will have a strong background in computational/theoretical neuroscience, modeling of stochastic neural dynamics and experiments involving closed-loop electrical stimulation. Related recent publications can be found on the Truccolo lab website ( http://www.truccololab.com/ <http://dl.dropbox.com/u/983891/Truccolo_home.htm>). Inquiries should be addressed to Dr. Truccolo (wilson_truccolo(a)brown.edu) Applications including a CV, statement of research interests, and the names and full contact details of three referees should be sent to wilson_truccolo(a)brown.edu. -- Wilson Truccolo, Ph.D. Pablo J. Salame '88 Goldman Sachs Assistant Professor of Computational Neuroscience Department of Neuroscience & Institute for Brain Science, Brown University Lab website: http://www.truccololab.com/

June 28, 2016

Postdoctoral position in graph signal processing for monitoring spatio-temporal dynamics of brain activity

by Nicolas Farrugia

Postdoctoral position in graph signal processing for monitoring spatio-temporal dynamics of brain activity Telecom Bretagne, Brest, France P.I. : Dr. Vincent Gripon Context The present proposal is funded by the Neural Communication project, which is part of the Labex CominLabs. This project started in November 2015 for a duration of two years as a continuation of the Neural Coding project, also founded by the Labex CominLabs from November 2012 to October 2015. The main goal of the project is to propose models for communications between cortical areas in the brain and to develop novel methodologies for identifying spatio-temporal patterns in brain activity. The project takes advantage of the expertise of two internationnaly renowned teams. The first one is led by Fabrice Wendling, director of research at LTSI in Rennes, and aims at proposing innovative methods for extracting connectivity graphs from EEG signals. The second one (host team) is led by Claude Berrou, professor at Télécom bretagne, and aims at proposing novel models for information processing in neural networks. The host team is also active in the new field of graph signal processing. The host team is composed of three permanent researchers as well as two postdocs and six PhD students. The proposed postdoctoral position is meant to take place in Télécom Bretagne, in Brest. The candidate is expected to work in collaboration with people involved in the ERC project Neucod led by Claude Berrou. Proposal It is now well-known that brain activity is structurally organised into functionally connected networks. Using functional MRI on subjects at rest, resting state networks can be defined as sets of spatially distinct brain areas with temporally correlated activity. While having been extensively studied over long time periods (e.g. 6 minutes), such networks are now investigated using dynamic analysis with a temporal resolution of a few dozens of seconds. Other works are interested in applying similar methodologies to monitoring the dynamics when performing cognitive tasks, as it has been shown that task-related functional networks are spatially similar to resting-state networks. Recently, a novel framework has been developed that aim at exploiting graphical structures of the underlying topology the signals are projected onto, called graph signal processing. As a result, it is possible to define ad hoc harmonic operators including convolutions and wavelets. A major advantage of this approach is the ability to detect similar patterns in distinct regions of the network, despite the inhomogeneity of the network topology. We are interested in applying graph signal processing to brain imaging to study special temporal dynamics, both in the resting state and task-related networks using EEG and fMRI. Details The head of the project is Vincent Gripon, permanent researcher with Télécom Bretagne. Please send your curriculum vitae, contacts for two references, as well as a cover letter to vincent.gripon(a)telecom-bretagne.eu. Expected disposable salary is about 30k{\euro} per year, depending on experience. The position starts in September 2016 (or sooner) and finishes in November 2017. The postdoc position is accompanied with overheads for travel expenses covering the participation to international conferences. The candidate must have defended a Ph.D. related to neuroscience, neuroimaging and familiar with signal processing. Programming skills are essential to this position. The deadline for applying to the position is July 17th.

June 28, 2016