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Neural Processing Letters: 2nd CFP for the Special Issue on "Off the mainstream: advances in neural networks and machine learning for pattern recognition"

by Friedhelm Schwenker

2nd Call for Papers Special issue on Off the mainstream: advances in neural networks and machine learning for pattern recognition to be published in Neural Processing Letters *** Submission deadline: January 31, 2017 *** Guest editors: Edmondo Trentin, University of Siena, Italy (trentin(a)dii.unisi.it) Friedhelm Schwenker, University of Ulm, Germany (friedhelm.schwenker(a)uni-ulm.de) Nemat El Gayar, Cairo University, Egypt (elgayar.neamat(a)gmail.com) Hazem M. Abbas, Ain Shams University, Egypt (hazem.abbas(a)eng.asu.edu.eg) Aims and scope of the special issue: "Mainstream science is about publishing what everyone else is publishing with very small changes. You'd better at least start off that way if you want to get tenure," the sociologist Rodney Stark said. But "big ideas don't come to those who avoid risk", as John Bohannon added. The area of artificial neural networks (ANN) and machine learning (ML) makes no exception to these ends: Mainstream topics, originally stemming from exciting breakthroughs (the "big ideas") that gradually become trends and end-up being mostly over-beaten publishing tracks, have characterized the scientific literature throughout the whole history of these research fields. A few, widely known instances of such (more or less recent) mainstream trends are: - Supervised support vector machine training (in both primal and dual) - Supervised multilayer perceptron training via regular backpropagation - Radial basis functions networks - Bayesian networks (either shallow or deep) - Deep feed-forward and convolutional neural networks - Countless applications of the aforementioned machineries - The “approximation capabilities” of such machineries Based on these premises, this special issue invites paper submissions on real novel research developments in the areas of neural networks and learning machines that (1) are rooted in (or, aimed at) pattern recognition (PR), and that, above all, (2) do not follow in the footsteps of nowadays established trends. Preference (over applications, theoretical analysis, and variants of established techniques) will thus be given to submissions that hand out fresh and innovative ideas/architectures/algorithms, even if they are in their infancy (e.g., possibly lacking of a complete investigation of their theoretical properties). A detailed list of topics of interest would contradict the very perspective of the present special issue. Nonetheless, some general, topical research directions are (to name a few): - New ANN or ML architectures - New ANN, ML, or PR algorithms - New estimation/optimization/assessment techniques for ANNs, ML, or PR - New and sound combination/hybridization of machines - Solutions to new, relevant PR-related problems - New and sound solutions to established PR-related problems If you are not sure on whether your manuscripts matches the aims and scope of this special issue or not, do not hesitate to get in touch with the guest editors at any time. The special issue will comprise (a) papers submitted in response to this call, and (b) extended versions of selected papers from the ANNPR 2016 Workshop (https://neuro.informatik.uni-ulm.de/ANNPR2016/) sponsored by the International Association for Pattern Recognition. Paper submission: Papers must be submitted online via the Neural Processing Letters website (https://www.editorialmanager.com/nepl/default.aspx) selecting the choice that indicates this special issue (identifier: S.I.:Off_mainstream). Prepare your paper following the Journal guidelines for Authors (http://www.springer.com/computer/ai/journal/11063?detailsPage=pltci_1060677) All submitted papers will undergo a regular peer-review process. Important dates: Opening of electronic submission: September 1, 2016 Submission deadline: January 31, 2017 Completion of 1st round of review process: March 31, 2017 Re-submission of revised manuscripts: May 15, 2017 Final decision: June 30, 2017 Tentative publication of the Special Issue: Fall 2017 -- 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

Nov. 9, 2016

Video course on understanding higher cognition in terms of brain anatomy and physiology

by Andrew Coward

A 29 lecture video course on approaches to understanding cognitive processes in terms of brain anatomy and physiology is now available at www.understandinghighercognition.com<http://www.understandinghighercognition.com> The lectures are based on a course given to third year and graduate students in computer science, psychology and neuroscience at the Australian National University in Canberra and also at Simon Fraser University in Vancouver, Canada. Topics covered include: - The nature of understanding: lessons from the computer science approach to understanding complex systems - Major cognitive phenomena: attention; different types of memory; speech and consciousness - Key topics in brain anatomy, physiology and chemistry - Practical pressures on brain architecture exerted by natural selection: resource limits, learning without interference with prior learning, etc; - Architectural forms resulting from the practical pressures - Evidence for the existence of the predicted architectural forms in the brain; how to use the forms to support understanding - Understanding attention and different types of memory: semantic, episodic, priming, working and procedural memory - Understanding specific cognitive tasks - Understanding human consciousness and self awareness. Each lecture is divided into 5 - 10 minute topic videos. Lecture format is mainly images and graphics supported by verbal explanations. Textbook for the course is "Towards a Theoretical Neuroscience: from Cell Chemistry to Cognition<http://www.springer.com/us/book/9789400771062>" <http://www.springer.com/us/book/9789400771062> published by Springer. Access to the lectures is free.

Nov. 7, 2016

Post-Doctoral Position to Research Mediating and Moderating Factors that Determine Transfer of Working Memory Training at UC Riverside and UC Irvine.

by Aaron Seitz

Please forward the below to anyone that you think might be interested. Thanks, -Aaron Post-Doctoral Position to Research Mediating and Moderating Factors that Determine Transfer of Working Memory Training at UC Riverside and UC Irvine. Aaron Seitz (UCR) and Susanne Jaeggi (UCI) are seeking to hire a post-doctoral researcher to work on a project funded by the National Institute of Mental Health entitled ³The Understanding Mediating and Moderating Factors that Determine Transfer of Working Memory Training² (https://ucrtoday.ucr.edu/40627 <https://ucrtoday.ucr.edu/40627> ). This individual is expected to take a lead role in designing and conducting experimental work investigating features of training that differentially lead to learning and transfer of learning, participant characteristics that determine predispositions for different training outcomes, and develop and implement tests that are valid towards assessing potential far transfer of working memory training to ecological settings. This project, which intends to run 31,000+ research participants (online and in lab) on working memory training, aims to generate a robust and reliable dataset on Working Memory training to settle current debates in the field and translate these findings to promote more effective methods of cognitive rehabilitation. Successful candidates should have strong technical skills, management skills, creativity and perseverance required to play a lead role in this sizeable project, and have expertise in one or more of the following areas and knowledge of the others; working memory, cognitive training, perceptual learning, and methods of assessing individual differences and effects of interventional studies. Researchers must possess a doctoral degree in Psychology, Education, Cognitive Science, Neuroscience, or a related field. The University of California offers excellent benefits. Salary is based on research experience. The initial appointment is for 1 year with a possibility of extension. The post-doctoral researcher will be involved at all stages of the proposed research, including setting up experiments, collecting and analyzing data, training and supervision of graduate students and undergraduate research assistants, and dissemination of results at conferences and in research publications. The postdoc will spend equal time on the UCR and UCI campus and work closely with both Seitz and Jaeggi to insure that procedures are coordinated between the sites and that all personnel are properly trained and supervised. The primary appointment will be at the UC Riverside Brain Game Center for Mental Fitness and Well-being (http://braingamecenter.ucr.edu/ <http://braingamecenter.ucr.edu/> ). The Brain Game Center¹s mission is to research, test, and disseminate evidence-based, scientifically optimized brain fitness games that transfer benefits to real-life activities. The Center has recently moved into a 3000 square foot facility that provides an ideal environment for the proposed work with a staff of full time research coordinators, full time programmers and a team of postdocs, graduate students, and an army of research assistants that facilitates the development, testing and dissemination of brain training games and cognitive assessment tools. The Brain Game Center is the only university-based research center focused on research of brain training games, and it has a track record of making tested procedures publically available so that people can try them out for themselves. The post-doc will also spend time at the UCI Working Memory and Plasticity Lab (http://wmp.education.uci.edu <http://wmp.education.uci.edu/> ) whose mission lies in the development of working memory interventions for populations across the lifespan, with the aim to understand the underlying cognitive and neural mechanisms that drive training-related changes using behavioral and neuroimaging methods, as well as transcranial electrical stimulation. The WMP lab currently employs 3 full-time research coordinators, as well as a team of undergraduate research assistants, and graduate students from both, the School of Education and the Department of Cognitive Sciences, and there is a host of ongoing national and international research collaboration providing opportunities for networking and intellectual exchange. Candidates should send a cover letter, CV, relevant publications, and the names of three references with phone numbers and email addresses to: Aaron Seitz aseitz(a)ucr.edu <mailto:aseitz@ucr.edu> ) and/or Susanne Jaeggi (susanne.jaeggi@u <mailto:susanne.jaeggi@gmail.com> ci.edu <http://ci.edu/> ). Review of materials will begin immediately and will continue until the position is filled. ************************************************** Aaron Seitz, Ph.D. Professor of Psychology Director of UCR Brain Game Center University of California, Riverside 900 University Ave. Riverside, CA 92521 Ph: (951) 827-6422 Fax: (951) 827-3985 Email: aseitz(a)ucr.edu Web: http://faculty.ucr.edu/~aseitz/ BGC: http://braingamecenter.ucr.edu **************************************************

Nov. 5, 2016

2 postdoctoral positions at the University of Pennsylvania

by Maria Neimark Geffen

2 postdoctoral positions: Neuronal circuits for dynamic auditory perception. The Geffen Laboratory at the University of Pennsylvania (Philadelphia, PA, USA) has two openings for a postdoctoral researcher (one experimental and one theoretical/computational) to study the neuronal circuits for dynamic auditory perception. There are a number of projects available, including: investigating intra-cortical and subcortical circuits supporting auditory adaptation; identifying neuronal circuits for hearing in the presence of noise; unraveling neuronal circuits controlling learning-driven changes in auditory acuity. We use cutting-edge experimental techniques for investigating population neuronal activity, including two-photon imaging of Calcium activity in behaving, head-fixed rodents, large-scale electrophysiological chronic and acute recordings, optogenetic, pharmacological and behavioral techniques. We are a creative, productive and collaborative group. Please see our lab website for more details on ongoing projects in the laboratory and recent publications ( http://www.med.upenn.edu/hearing <http://www.med.upenn.edu/hearing> ). The ideal candidate will be an energetic, talented, friendly, enthusiastic and creative researcher, who has recently completed (or plans on completing) their PhD and has received training in neuroscience, psychology, chemistry or biology (for the experimental position) or computational neuroscience, physics, mathematics or computer science (for the computational position). Prior experience in systems neuroscience is desired, but a highly successful applicants wishing to switch to neuroscience from other fields will also be considered. Proficiency with Matlab or other scientific computing software is expected. The campus of the University of Pennsylvania <http://www.upenn.edu/> has a wonderful collegiate feel, and the Medical School is located on the main campus, facilitating collaborations across departments. For a sample of events that almost everyone in our lab attends, consider: a weekly lab meeting, a weekly Computational Neuroscience Initiative seminar, a bi-weekly auditory journal club, a weekly interdisciplinary Mind and Brain seminar, and much more. Philadelphia is a vibrant city with a variety of cultural, gastronomical and entertainment attractions. To apply, please send your CV along with a cover letter briefly summarizing your research interests and include pdfs of your recent publications to Prof. Maria N. Geffen mgeffen(a)med.upenn.edu <mailto:mgeffen@med.upenn.edu> .

Nov. 3, 2016

Visit the Bernstein Network at booth #4017 at SfN 2016 for your next career step in Computational Neuroscience

by Kerstin Schwarzwaelder

Dear all, The Bernstein Network Computational Neuroscience will exhibit at the SfN Meeting 2016. Please find us at the "Neuroscience in Germany" booth #4017. The booth will present: * research fields * study and training programs * open positions * research and funding opportunities We are looking forward to welcoming you at booth #4017! Best regards, Kerstin Schwarzwälder -- Dr. Kerstin Schwarzwälder Scientific Coordination / Management Officer Please note: Our email addresses have changed. Please use k.schwarzwaelder(a)fz-juelich.de<mailto:k.schwarzwaelder@fz-juelich.de> Bernstein Network Computational Neuroscience | Bernstein Coordination Site (BCOS) Branch Office of the Forschungszentrum Jülich at the University of Freiburg Hansastr. 9A | 79104 Freiburg, Germany phone: (+49) 0761 203 9589 mail: k.schwarzwaelder(a)fz-juelich.de<mailto:k.schwarzwaelder@fz-juelich.de> web: www.nncn.de<http://www.nncn.de> Twitter: NNCN_Germany<https://twitter.com/NNCN_Germany> YouTube: Bernstein TV<https://www.youtube.com/user/BernsteinNetwork> Facebook: Bernstein Network Computational Neuroscience, Germany<https://www.facebook.com/BernsteinNetwork/> LinkedIn: Bernstein Network Computational Neuroscience, Germany<https://www.linkedin.com/company/bernstein-network-computational-neuroscien…> <https://www.linkedin.com/company/bernstein-network-computational-neuroscien…> ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

Nov. 3, 2016

3 Research fellow positions at the University of Sussex

by Thomas Nowotny

We have 3 open positions for research fellows in Computational Neuroscience, bio-inspired Robotics and Computer Science (GPU accelerated computing). The positions are part of the new Brains-on-Board project (http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/P006094/1) which is a multi-university collaboration aiming to create robotic controllers that will enable autonomous robots with the navigational and learning abilities of a honeybee. The project involves five research groups at the University of Sheffield, Queen Mary University, London, and the University of Sussex performing research whose goal is biomimetic robot control and which will combine autonomous robotics, computational neuroscience, accelerated neural network simulations on GPU architectures and insect neuroscience and behaviour. In Sussex we are seeking to employ a team of 3 research fellows for initially 2 years, with possible extension up to 5 years. We envisage the fellows to start in January 2017. RF 1 (ref 1388) in bio-inspired robotics, will develop insect-derived models of navigation and apply them to autonomous robots. The work will include refining and developing models of insect navigation and testing them on robotic platforms ranging from the Sussex Gantry robot through wheeled robots to autonomous aerial vehicles. A successful candidate will have a keen interest in the interface of computational biology and bio-inspired robotics and a proven track record in working in this area. RF 2 (ref 1389) in Computational Neuroscience, will work on models of associative learning, multimodal integration and decision making in insects. The work will include formulating neuronal network models of the mushroom bodies, central complex and motor areas of the bee brain constrained by experimental data. The models will then be employed and tested on robotic platforms, including wheeled robots and aerial vehicles. A successful candidate will have a keen interest in computational neuroscience and experience with computational modelling. RF 3 (ref 1390) in Computer Science, working on GPU accelerated simulation of brain models and brain-inspired robot controllers, building on our GeNN meta-compiler and the SpineCreator/SpineML API to GeNN. The work will include developing methods for model- and hardware-aware GPU-accelerated simulations methods that will allow us to efficiently simulate both large-scale models in Computational Neuroscience on super-computers and bio-inspired robotic controllers on embedded systems GPU accelerators. A successful candidate will have proven skills in complex software development with a focus on scientific computing. All RFs will work together on the project within Sussex and in the larger Brains-On-Board team. We encourage applicants to apply for multiple positions if they are interested and feel qualified. Please indicate any preferences when applying for multiple positions. In order to apply got to http://www.sussex.ac.uk/aboutus/jobs/1388-1389-1390 where you can find further details and the application form. The closing date is 1 December 2016. For informal enquiries, please contact Prof Thomas Nowotny (t.nowotny(a)sussex.ac.uk<mailto:t.nowotny@sussex.ac.uk>) or Dr Andy Philippides (andrewop(a)sussex.ac.uk<mailto:andrewop@sussex.ac.uk>). With kind regards, Thomas -- Prof Thomas Nowotny Director of Research and Knowledge Exchange School of Engineering and Informatics University of Sussex Falmer, Brighton BN1 9QJ, UK Phone: +441273678593 FAX: +441273877873

Nov. 2, 2016

PhD position @ Blue Brain Project - Plasticity in the neocortex

by emuller

----------------------------------------------------------------------------- PhD position in the Blue Brain Project - Department of In Silico Neuroscience ----------------------------------------------------------------------------- Project title: Principles of biophysical structural plasticity in the neocortex Supervisors: Prof. Henry Markram, Dr. Eilif Muller Keywords: simulation, neocortex, plasticity, network reorganization, assemblies, coding, dendrites, calcium, NMDA Project description: During our lifetimes, our brains undergo continuous changes as a consequence of our experiences. Synaptic plasticity—the biological process by which brain activity leads to long-term changes in synaptic connections—is thought to be central to learning and memory. However, little is known about how this process shapes the specialization of biological neural networks, such as the neocortex. The objective of the present work will be to devise, implement and study data-driven biophysical models of synaptic and structural plasticity for the formation of functional neocortical networks. This project will leverage the Blue Brain Project data-driven reconstruction of a neocortical microcircuit [1], and augment it with data-driven biophysical calcium-based models of synaptic and structural plasticity. The specific objective of this PhD project will be to implement and constrain models of structural plasticity, and study the formation of assemblies, and emergent structure-function relationships in the presence of structured input. The prospective student will join an ongoing collaboration including international experts in biophysical modeling of plasticity and dendrites, topological analysis of network structure, and optimization of neural simulations for large supercomputers. A significant allocation of computing time on a large HPC system will be at the disposal of this project. [1] Markram, H., Muller, E., Ramaswamy, S., Reimann, M. et al. Reconstruction and Simulation of Neocortical Microcircuitry. Cell 163:2, 456-495 (2015). Key external collaborators: Dr. Michael Graupner (CNRS, Université Paris Descartes), Prof. Idan Segev (Hebrew University Jerusalem) This project is offered in the context of the EPFL Doctoral School in Neuroscience (EDNE). Please visit http://phd.epfl.ch/neuroscience-openings for further details, and information on how to apply. Application Deadline: Nov 15th, 2016. For further details on the project contact: Dr. Eilif Muller <eilif.mueller(a)epfl.ch> ------------- Dr. Eilif Muller Section Manager - In Silico Neuroscience - Experimentation EPFL - Blue Brain Project Biotech Campus Chemin des Mines 9 1202 Geneva Switzerland Tel: +41 21 693 0698 Fax: +41 21 693 5350 www: http://bluebrain.epfl.ch/page-77926-en.html www: http://neuralensemble.org/people/eilifmuller

Nov. 2, 2016

Fully funded postdoc position at the University of Geneva

by Jolivet, Renaud

The University of Geneva seeks one postdoc in computational neuroscience to investigate the relation between information transfer at synapses and in neural networks, and concomitant energy consumption. The starting date is May 2017. This position is fully funded by the Swiss National Science Foundation for 24 months. Initial appointment is for one year. Research will be conducted in the medical physics group of the physics section at the University of Geneva, under the supervision of Prof. Renaud Jolivet. * Summary Information transmission in the brain is energetically expensive, yet has to satisfy demands of speed and signal-to-noise reliability. We have recently shown that the strong retinogeniculate synapse relaying information from the retina to the thalamus resolves these competing constraints by maximizing energetic efficiency when transferring information. In their physiological state, these synapses are not set to transmit the maximum amount of information possible: information transmission increases when larger excitatory postsynaptic currents (EPSCs) are injected into the postsynaptic thalamic neuron. However, EPSCs that are larger or smaller than physiological EPSCs decrease the information transmitted per energy used. The physiological EPSC size therefore maximizes energy efficiency rather than pure information transfer across the synapse. In other words, the retinogeniculate synapse trades information for energy savings (http://dx.doi.org/10.1016/j.cub.2015.10.063; http://dx.doi.org/10.1016/j.neuron.2012.08.019) These findings suggest maximization of information transmission per energy used as a design principle in the brain. However, it is unclear how broadly this principle applies. Whether energy efficiency at excitatory synapses is a special property of strong relay synapses, or a more general principle also governing synaptic inputs that contribute more weakly to determining the output of the postsynaptic cell is an open question. These findings also raise the question of what mechanisms are in effect in order to achieve energetic efficiency of information transfer at synapses. This project will address these questions using information theory and simulations of biologically validated neuron models. Applicants must imperatively be self-sufficient programmers (MATLAB preferred) and have a strong background in computational neuroscience. They should be familiar with several of the following topics: information theory, Hodgkin-Huxley models, the NEURON simulation environment, signal processing, models of synaptic plasticity, models of neural networks. Please contact renaud.jolivet(a)unige.ch<mailto:renaud.jolivet@unige.ch> for additional information. * About the University of Geneva (UNIGE) UNIGE is a generalist French-speaking university located in Geneva, Switzerland. The QS World University Rankings 2016 and Times Higher Education World University Rankings 2016/17 respectively rank UNIGE as 95th and 131st worldwide. It ranks 41st worldwide for science (Shanghai Academic Ranking of World Universities in Natural Sciences and Mathematics 2016). It is Switzerland’s second largest university with more than 17000 students of 150 different nationalities and about 4000 researchers of 113 nationalities, who study and work in 9 different faculties. UNIGE trains a large number of PhD students and postdocs in neuroscience. The various research and teaching activities are listed at http://neurocenter.unige.ch/ and at https://www.unil.ch/ln/en/home.html. UNIGE is also developing with other institutions a new campus in Geneva (http://www.campusbiotech.ch/en/) focusing heavily on neuroscience and translational research. Geneva is at the heart of a conurbation with more than 1.25 million inhabitants. It is a global city, a financial center, and worldwide center for diplomacy and research. It has one of the highest quality of life in the world. It offers varied cultural activities and outdoor opportunities being located at one extremity of Lake Geneva, one of the largest lakes in Europe, on the western doorstep of the Alps. The University of Geneva offers competitive salaries and conditions at all levels in a young, dynamic, and multicultural environment. It is an equal opportunity employer and women are encouraged to apply. The official language of the laboratory is English. * How to apply Please send an e-mail to renaud.jolivet(a)unige.ch<mailto:renaud.jolivet@unige.ch> with your resume, list of publications, a one-page statement describing your research interests and career plan, and the names of at least three references. — Prof. Renaud Jolivet CERN, Experimental Physics Department & University of Geneva, Physics Section +41 22 767 24 70 (CERN) +41 22 379 62 75 (UNIGE) +41 79 830 21 29 (mobile) renaud.blaise.jolivet(a)cern.ch<mailto:renaud.blaise.jolivet@cern.ch> https://sites.google.com/site/renaudjolivet/

Nov. 1, 2016

PhD position in cognitive modeling

by Angela Yu

Applications are invited from highly motivated students to conduct PhD research in the Computational & Cognitive Neuroscience Lab, led by Angela Yu, at University of California, San Diego. Candidates must have a strong background in mathematics and/or machine learning, and be committed to applying rigorous mathematical tools to modeling cognitive and neural processes. Experience or interest in carrying out human behavioral experiments (either in person or on Amazon M-Turk) and/or collaborating with other human/animal neuroscience laboratories is also desirable. Current research in the lab ranges across cognitive control, decision-making, visual search, active learning, social cognition, and machine learning. Dr. Yu's group is situated within the Cognitive Science department of UCSD, but Dr. Yu advises students not only from the Cognitive Science, but also from Computer Science & Engineering, Electrical & Computer Engineering, and Neurosciences PhD programs. Interested students should apply directly to one or more of the PhD programs, and indicate Dr. Yu as a potential research advisor in the research statement. They are also encouraged to email Dr. Yu directly to explain why they think their interests/background are a good fit for working with Dr. Yu. ------------------------------------- Angela J. Yu Associate Professor UCSD Cognitive Science www.cogsci.ucsd.edu/~ajyu <http://www.cogsci.ucsd.edu/~ajyu> —————————————————— ----------------------------------- Angela J. Yu Associate Professor UCSD Cognitive Science 858-822-3317 www.cogsci.ucsd.edu/~ajyu -----------------------------------

Oct. 31, 2016

Postdoc position in computational modeling

by Angela Yu

Applications are invited from highly motivated researchers for a postdoctoral position immediately available in the Computational & Cognitive Neuroscience Lab, led by Angela Yu, at University of California, San Diego. Candidates must have a strong background in mathematics and/or machine learning, and be committed to applying rigorous mathematical tools to modeling cognitive and neural processes. Experience or interest in carrying out human behavioral experiments (either in person or on Amazon M-Turk) and/or collaborating with other human/animal neuroscience laboratories is also desirable. Current research in the lab ranges across cognitive control, decision-making, visual search, active learning, social cognition, and machine learning. Accepted candidate would have great latitude in determining own research projects. Dr. Yu's lab is situated within the Cognitive Science department of UCSD, and affiliated with the Computer Science Department, Electrical Engineering Department, Neurosciences Graduate Program, and the Institute of Neural Computation. There are ample opportunities for collaborations with related groups across the UCSD main campus, the medical school, and the Salk Institute. Interested candidates should send a research statement, along with a CV including publications, to Dr. Angela Yu (ajyu(a)ucsd.edu <mailto:ajyu@ucsd.edu>). Candidates are invited to explain in detail how their own research interests dovetail that of Dr. Yu's lab. Two or more letters of references should be sent directly to Dr. Yu. Dr. Yu will be interviewing candidates at the Society for Neuroscience Annual Meeting in San Diego, November 12-16, 2016. ------------------------------------- Angela J. Yu Associate Professor UCSD Cognitive Science www.cogsci.ucsd.edu/~ajyu -------------------------------------

Oct. 28, 2016

MIT postdoc position in AI/neuroscience/physics

by Max Tegmark

The MIT Physics Department invites applications for a postdoctoral research position to work with Professor Max Tegmark on the physics of intelligence, in partnership with Tomaso Poggio, Edward Boyden, Gabriel Kreiman and others associated with the Center for Brains, Minds & Machines (https://cbmm.mit.edu/about/people) and with a network of other collaborators. Research interests at the interface of theoretical physics, artificial intelligence and computational neuroscience are a strong plus. Candidates interested in exploring ways to test theories with state-of-the-art data and simulations are particularly welcome. Applicants should submit a curriculum vitae, a list of publications, a brief description of research interests and goals and should arrange for three letters of recommendation to be uploaded to this site by December 1, 2016. A Ph.D. in physics or physics-related discipline, such as AI or computational neuroscience, is required by the start of employment. Any inquiries should be sent to tegmark(a)mit.edu. MIT is an equal employment opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, sex, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, ancestry, or national or ethnic origin.

Oct. 27, 2016

PhD position: Dimension reduction for neural networks

by Laing, Carlo

Funding is available for a PhD position in "Dimension reduction for neural networks" at Massey University (Auckland, New Zealand). Project description: An essential tool in the study of complex networks is dimension reduction, i.e. the discovery and then computational use of a small number of collective variables which completely describe the behaviour of the network to within some accuracy. Having such a reduced description can allow the drastic acceleration of computational tasks for modelling and predicting network behaviour, and provides a mechanism for discovering which details of a network are essential in determining its behaviour. This project involves the development of reduced models of networks of model neurons, in order to better understand their possible dynamics. An important aspect will involve investigating the role of heterogeneity (both in terms of a network's structure, and the intrinsic dynamics of a single neuron) in the networks' behaviour. The student should have the equivalent of an MSc in Mathematics (or other highly mathematical field such as Physics). A good knowledge of nonlinear dynamics and scientific programming is an advantage; no knowledge of neuroscience is assumed. The scholarship consists of a stipend of NZ$27,500 per year (tax free) plus applicable student fees for 3 years. Applicants must fulfil the PhD eligibility conditions of Massey University. Applicants should send a copy of their curriculum vitae, a statement of interest and the names and contact details of two (2) referees to Associate Professor Carlo Laing (E-mail: c.r.laing(a)massey.ac.nz<mailto:c.r.laing@massey.ac.nz>) Webpage: http://www.massey.ac.nz/~crlaing/ -- Associate Professor Carlo Laing. INMS, Massey University, Private Bag 102-904, NSMC, Auckland, New Zealand. ph: +64-9-414-0800 x 43512. fax: +64-9-443 9790 http://www.massey.ac.nz/~crlaing/

Oct. 25, 2016

PhD position in 'New insights into ADHD through behavioural and modelling studies'

by Eirini Mavritsaki

Dear comp-neuro team, I was wondering if you could please forward the information below to your list about a new PhD position in our lab for February 2017 start. Kind regards, Eirini Mavritsaki PhD available for February 2017 start in 'New insights into ADHD through behavioural and modelling studies' Applications are invited for a 3-year PhD studentship within the Department of Psychology, Faculty of Business Law and Social Sciences, Birmingham City University. Applicants need to demonstrate ability and commitment, including excellent communications skills in written and spoken English. Project Synopsis: There are many limitations on the behaviour of complex neural systems, but one primary constraint is to filter incoming input in order that actions can be programmed to behaviourally relevant stimuli. This is the limit of 'attention'. A major challenge for current-day researchers is to understand how (and why) these limitations arise, especially in conditions like attention deficit hyperactivity disorder (ADHD) where the attentional system is dysfunctional. Our application's main aims is to access differences in visual attention between children diagnosed with ADHD and typically functioning children and the role of diet in this. This Ph.D. thesis aims to do this using a novel interdisciplinary approach, behavioural and computational modelling study together with a food diary. The Ph.D. is part of a bigger research project that is in collaboration with Dr Chrysavgi Tsakona in Russell Hall Hospital. The successful applicant will join the newly-established Centre for Applied Psychological Research (CAP Research) within the Department of Psychology at Birmingham City University. This centre is part of a vibrant and rapidly expanding research community, which offers applicants with an excellent opportunity to develop their research career. The applicant has the opportunity to have teaching experience, to participate to research seminars and to co-supervise undergraduate projects. Candidate Qualification and Specifications: Essential ? The applicant should hold a good undergraduate honours degree (First or 2:1) in psychology or a related social sciences subject. ? A demonstrated understanding of research methods is essential (as evidenced by degree transcript grades for research methods and dissertation modules). ? The applicant will be expected to undertake and pass Disclosure and Barring Service (DBS) checks. ? The applicant should enjoy working with children. ? The applicant should have experience in computational modelling. Desirable ? A Masters' degree in research methods, psychology or a related social sciences subject. ? Work experience (voluntary or paid) in schools or experience working with children. ? Experience in C++ and/or Matlab. ? Access to a car and a valid driving licence. For more information please contact Dr Eirini Mavritsaki (Eirini.mavritsaki(a)bcu.ac.uk) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Eirini Mavritsaki, Ph.D., CPsychol Senior Lecturer in Cognitive Psychology and Director of Research for the School of Social Sciences Department of Psychology Faculty of Business Law and Social Sciences Birmingham City University The Curzon Building 4 Cardigan Street Birmingham B4 7BD eirini.mavritsaki(a)bcu.ac.uk<mailto:eirini.mavritsaki@bcu.ac.uk> 0121 331 6361 Special Issue in Frontiers 'Neuropsychology through the lenses of computational modelling' http://fron.tiers.in/go/r2e3M4 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Oct. 25, 2016

Onsite interviews at SfN for Neural Data Analytics - Post Docs, Staff Scientists and Electrical Engineers

by Platt, Jo Ann

Join our team to revolutionize medicine. The Center for Bioelectronic Medicine at the Feinstein Institute for Medical Research is conducting interviews at the 2016 Neuroscience Meeting in San Diego for multiple positions in the fields of machine learning, neural engineering, neural decoding and data analytics, microfabrication, bioelectronics and biosensing, and neurophysiology. Each successful candidate will work as part of a multidisciplinary team to determine the nature of neural control over molecular, cellular and organ functions of the body, the parts of the brain that regulate those nerves, and the signals that the brain receives to monitor cell and organ function. The candidates will work on projects involving development of novel signal processing and machine learning methods to gain insights into decoding and encoding mechanisms of the brain and peripheral nerves, reinforcement learning approaches used to optimize neural stimulation, techniques to directionally transmit or receive neural signals and numerical and biophysical modeling of neural circuits. Submit your resume to japlatt(a)northwell.edu for consideration and to arrange an onsite interview. Jo Ann Platt The Feinstein Institute for Medical Research Cell: (415) 265-0441 350 Community Drive Manhasset, NY 11030 The information contained in this electronic e-mail transmission and any attachments are intended only for the use of the individual or entity to whom or to which it is addressed, and may contain information that is privileged, confidential and exempt from disclosure under applicable law. If the reader of this communication is not the intended recipient, or the employee or agent responsible for delivering this communication to the intended recipient, you are hereby notified that any dissemination, distribution, copying or disclosure of this communication and any attachment is strictly prohibited. If you have received this transmission in error, please notify the sender immediately by telephone and electronic mail, and delete the original communication and any attachment from any computer, server or other electronic recording or storage device or medium. Receipt by anyone other than the intended recipient is not a waiver of any attorney-client, physician-patient or other privilege.

Oct. 24, 2016

NIH BRAIN THEORIES--POSTDOCTORAL POSITION

by Stephen Jose Hanson

NIH Post-doctoral Fellowship in BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain Applications for an NIH-funded post-doctoral position are invited for the Laboratory of Dr. Stephen José Hanson’s in the Department of Psychology and in RUBIC (Rutgers Brain Imaging Center) at Rutgers University, Newark, N.J. USA. The focus of research and training is in the area of computational neuroscience, and the development of brain network models based on graphical model selection using dynamical search procedures and the modeling of brain signals arising from neuroimaging data (e.g. fMRI). These projects will be performed in the lab of Dr. Hanson and in conjunction with Dr. Glymour’s (CMU) causal discovery research group. The ideal candidate will have a strong background in computation, statistics, probability theory, multivariate analysis and signal processing. Programming skill sets ( e.g., C++, R, Matlab, Debian, python) would be key to a successful candidate. Additionally, having background in neuroscience, neuroimaging or brain science more generally would be important to a successful application. This is a 2 year position with a 3 rd year possible. Starting date is flexible and with earliest start by December 1. Applications will be accepted until a candidate is hired. Inquiries should be addressed to Stephen José Hanson (jose(a)rubic.rutger s.edu). Please also send applications including a CV, statement of research interests, and the names and full contact details of three referees to jose(a)rubic.rutgers.edu. Relevant publications include: Ramsey J., Hanson S.J. Hanson C., Halchenko Y.O., Poldrack R.A., & Glymour C. (2010). Six problems for causal inference from fMRI. Neuroimage, 49, 1545-1558. Hanson, C., Hanson, S.J., Ramsey, J. & Glymour, C. (2013) Atypical effective connectivity of social brain networks in individuals with autism. J. Brain Connect. 3(6):578-89. Hanson, S. J. & Halchenko, Y. O. (2008). Brain reading using full brain support vector machines for object recognition: there is no face- identification area. Neural Computation, 20, 486-503 Poldrack, R.A., Halchenko, Y., & Hanson, S.J. (2010). Decoding the large-scale structure of brain function by classifying mental states across individuals. Psychological Science, 20, 1364-1372 Ramsey, J., Glymour, M., Sanchez-Romero, R. and Glymour, C. (in Press) A million variables and more: The fa st greedy search algorithm for learning high dimensional graphical causal models, with an application to functional magnetic resonance images. International Journal of Data Science and Analytics. Rutgers is an equal employment opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.

Oct. 24, 2016

PhD position in Oxford

by Rafal Bogacz

Dear Colleagues, Applications are invited from UK or EU residents for doctoral studies in computational neuroscience, to start in October 2017. The project will be supervised by Rafal Bogacz and will be carried out within the interdisciplinary team of the MRC Brain Network Dynamics Unit. The research can focus on areas investigated by Rafal Bogacz's Group, including: - models of decision making in the basal ganglia - optimising deep brain stimulation - predictive coding models of the cortex Candidates must have a very strong mathematical or computational background and an excellent undergraduate degree in a relevant discipline (e.g. computer science, engineering, mathematics, physics or neuroscience). An undergraduate 1st class or upper 2nd class degree (or equivalent grade) is required for graduate entry into Oxford. The minimum standards for English apply for applicants. This PhD (DPhil) studentship is funded by the Medical Research Council. To be eligible for a full award (stipend in addition to university/college fees) a student must have settled status in the UK, and must have been ‘ordinarily resident’ in the UK for three years prior to the start of the studentship. For further details about student eligibility requirements for full and fees-only awards, please see: http://www.mrc.ac.uk/skills-careers/studentships/studentship-guidance/stude… Formal applications must be made via the University online application system. The relevant course code is: Doctor of Philosophy in Clinical Neurosciences – RD_CU1. In the covering letter, please describe the research you would like to conduct and clarify how your experience and skills would help you in that work. The closing date for applications is 12.00 noon on Friday 13th January 2017. Best wishes, Rafal

Oct. 24, 2016

Postdoctoral position in theoretical neuroscience - machine learning (RIKEN-BSI Japan)

by Andrea Benucci

RIKEN Brain Science Institute - Japan Laboratory for Neural Circuits and Behavior www.benuccilab.net (Laboratory Head: Andrea Benucci) Research field Our laboratory studies the neural basis of sensory processing and decision-making in mice trained in behavioral tasks. We do so using a combination of computational and experimental approaches (electrophysiology, fluorescence imaging, and optogenetics). Job title and description: Postdoctoral positions The project will focus on using theoretical approaches based on machine learning (specifically on RNN) to capture key computational aspects of cortical processing in large neuronal populations. This work will be done in close collaboration with experimentalists to jointly design new experimental paradigms based on the theoretical simulations. Qualifications We seek exceptional candidates with a strong computational background, especially in the field of recurrent neural network simulations. Candidates should have a Ph.D. in a relevant field (e.g., Computational Neuroscience, Computer Science, Math, Physics). Proficiency in programming (e.g., MATLAB, C++) is necessary. The ideal candidate will be interested in engaging in experimental work as well. Work location The Neural Circuits and Behavior Team is located at RIKEN Brain Science Institute, Wako, Saitama, Japan. The institute is about 15 min away from the main Tokyo metropolitan area by train. Salary and benefits This is a funded position but applicants are strongly encouraged to apply for external funds. The employment contract is renewable on a yearly basis based on performance evaluation up to seven years from the start date. Salary will be commensurate with qualifications and experience. Social insurance will be applied. Free, mandatory membership in the RIKEN Mutual Benefit Society (RIKEN Kyosaikai) will be provided. These and other provisions are in accordance with RIKEN regulations. RIKEN is promoting a Gender Equity Program by taking various measures to create a workplace where both men and women are able to give full rein to their talents and abilities. http://www.riken.go.jp/en/careers/working-at-riken/benefits/ Application and required documents Interested applicants are encouraged to apply as soon as possible. Candidates should provide (1) cover letter, (2) CV and bibliography, (3) the names and contact information of three references (including the current supervisor, if available) with a brief description of your relationship to each reference. Send application to: andrea(a)benuccilab.net Selection process Applications will be reviewed as they are received. Shortlisted candidates will be invited to RIKEN-BSI for an in-person interview. --

Oct. 19, 2016

CFP: FLAIRS 2017, Marco Island, FL,

by bisant＠umbc.edu

CALL FOR PAPERS FLAIRS 2017, Florida Artificial Intelligence Research Symposium Special Tracks on Data mining and Special Track on Cyber Security Marco Island, Florida http://www.flairs-30.info/ Paper submission deadline: November 21, 2016. Notifications: January 23, 2017. Camera ready version due: February 27, 2017. FLAIRS is an interdisciplinary artificial intelligence conference which especially encourages novel ideas and which features a double-blind review process. Data Mining Track This special track will be devoted to data mining with the aim of presenting new and important contributions in this area. Papers and contributions are encouraged for any work related to Data Mining. Topics of interest may include (but are in no way limited to): 1. Applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy. 2. Modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches. 3. Feature extraction and selection. 4. Post-processing techniques such as visualization, summarization, or trending. 5. Preprocessing and data reduction. 6. Knowledge engineering or warehousing. Papers dealing with Cloud-based unstructured data or Cloud-based tool suites, such as Mahout or Apache Spark, are also encouraged. Cyber-Security Track Original high quality papers are sought for leading edge research and applications relating to the application of AI and Cyber Security. Topics of interest may include but are not limited to: · Machine Learning for Intrusion Detection Systems · NLP for text analysis in Cyber Security · Video and CCTV semantic analysis for terrorist or criminal action detection · AI & Biometrics, Internet of Things, and Cloud Computing security · AI & SCADA systems, Network Systems, and Embedded Systems security · Formal and theoretical approaches of intelligent security in WSNs · Legal and policy issues in intelligent security · Integrity, privacy, authentication and access control · Intelligent secure systems in multimedia databases · Social networks security · Intelligent incident response techniques in network and communication systems · Risk analysis and intelligent management · Virtual Private Networks intelligent security · Automated reasoning techniques of incidents and evidence analysis · Evidentiary aspects of digital forensics · Collaborative intelligent investigation · Intelligent systems in management, storage and reassembly · Steganography, watermarking, and forensic techniques in multimedia content processing · Lightweight security techniques · Intelligent Large-scale investigations and Big Data · Innovative non-repudiation techniques · Intelligent vulnerability analysis and assessment · Attacks tracking · Data hiding, tamper detection and recovery techniques · Security of e- healthcare systems and applications Note: We invite original papers (i.e. work not previously submitted, in submission, or to be submitted to another conference during the reviewing process). Submission Guidelines Interested authors should format their papers according to AAAI formatting guidelines. The papers should be original work (i.e., not submitted, in submission, or submitted to another conference while in review). Papers should not exceed 6 pages (or 4 pages for short paper, to be presented as a poster) and are due by November 21, 2016. For FLAIRS-30, the 2017 conference, the reviewing is a double blind process. Author names and affiliations should be Xd out on submitted papers to provide double-blind reviewing. Papers must be submitted as PDF through the EasyChair conference system, which can be accessed through the main conference web site (http://www.flairs-30.info/) Note: do not use a fake name for your EasyChair login - your EasyChair account information is hidden from reviewers. Authors should indicate which special track they are submitting to. The proceedings of FLAIRS will be published by the AAAI. Authors of accepted papers will be required to sign a form transferring copyright of their contribution to AAAI. FLAIRS requires that there be at least one full author registration per paper.

Oct. 18, 2016

BrainModes conference - Brussels, Dec 1 and 2 - final call for abstracts

by Daniele Marinazzo

Dear all Just a reminder and the final call for submitting an abstract for the poster presentation which will take place during the dinner at the BrainModes conference, that this year we will organize in Brussels, at the Royal Flemish Academy of Sciences (KVAB) on* Dec 1 and 2*. BrainModes (www.brainmodes.org) is an annual conference in which methods and models to interpret brain activity, and their applications are discussed. This year the theme will be: Coordinated brain activity: foundations and applications. We are proud of the lineup of speakers this year, including top experts in the field of computational, cognitive and clinical neuroscience. There will be also a workshop organized in Ghent on November 30 on methodological issues and demonstrations. The complete program, the info on registration, abstract submission and location are here http://www.da.ugent.be/brainmodes Please spread this information within your network of students and colleagues, and looking forward to see you. -- Daniele Marinazzo -- Department of Data Analysis Faculty of Psychology and Pedagogical Sciences, Ghent University Henri Dunantlaan 1, B-9000 Ghent, Belgium +32 (0) 9 264 6375 <http://www.da.ugent.be/>http://users.ugent.be/~dmarinaz/ https://twitter.com/dan_marinazzo BRAINMODES 2016 CONFERENCE http://www.da.ugent.be/brainmodes http://helpdesk.ugent.be/e-maildisclaimer.php

Oct. 17, 2016

Two postdoctoral positions at Kyoto U: Brain imaging and simulation

by Hidetoshi Urakubo

Dear all, Integrated Systems Biology Lab at Kyoto U (Japan) invites applications for two post-doc positions. We look forward to your applications and recommendations. The full advertisement is available below. On behalf of Prof. Shin Ishii Hidetoshi Urakubo ============================================== Shin Ishii Lab, Dep Sys Sci, Grad Sch Info, Kyoto U Yoshida-Honmachi 36-1, Sakyo-ku, Kyoto 606-8501 Japan Phone: +81-75-753-4908 Fax: +81-75-753-4907 Email: urakubo-h(a)sys.i.kyoto-u.ac.jp ============================================== 1. Reconstruction and simulation of neural circuits in the brain We invite applications for a post-doc researcher in the areas of 3D image processing, computational neuroscience, and/or neurophysiology. A new collaborative project with U Tokyo has been launched for large-scale 3D imaging of neural networks and their reconstruction/simulation. Thus, the applicant will firstly analyze microscopic 3D images to identify biological neuronal networks in collaboration with Kasai-lab in U Tokyo (http://www.bm2.m.u-tokyo.ac.jp/english/index.html) The project is a part of “Synaptic optogenetics for memory structures”, which is founded by Japan Science and Technology Agency. 2. AI and brain simulation We are seeking a highly motivated post-doc researcher in artificial intelligence (including deep neural networks), brain simulation, and/or high performance computing (HPC). Join us in the "post peta-flops computing" project, a government funded project with the goal of using the K supercomputer and its successor to (1) develop HPC-based frameworks for large-scale neural image processing and to (2) build an innovative and large-scale artificial intelligence that mimics brain’s information processing. For both positions, basic qualifications include PhD in relevant fields with proven track record of peer-reviewed publications, as well as excellent verbal and written communication skills in English and/or Japanese. You will participate in the project with our tenure track and post-doc researchers from various backgrounds including computational neuroscience, systems biology, bioinformatics, mathematical engineering, and machine learning. Our laboratory is also collaborating on daily basis with Advanced Telecommunications Research Institute International (ATR), University of Tokyo, Okinawa institute of science and technology (OIST), RIKEN Brain Science Institute, and other international laboratories. [Job title and Job description] Title: Full-time Researcher / Full-time Research Engineer Begin Date: 1. April 1st 2017 (negotiable) 2. November 1st 2016 (negotiable) Location: Yoshida-Honmachi 36-1, Sakyo-Ku, Kyoto-city, Japan. 606-8501 Contract: Annually renewed based on evaluation. 1. Up to 5 years 2. Up to 3 years Salary: Commensurate with qualifications and experience. Based on Kyoto University’s provision for researchers. Benefits:　Standard social insurance, Days off (weekends, public holidays, End of the year and the New Year, Kyoto University Foundation Day, summer vacation), Sick leave Other miscellaneous provisions are in accordance with Kyoto U regulations. [Application and required documents] Please send the following five materials to the address below, either in printed or electronic form: 1. Complete CV (including technical skills [programming languages, platforms, systems, etc] and corresponding achievements that are relevant to our project) 2. List of publications 3. Reprints of 1 to 3 major publications 4. Document (one or two pages in A4 or letter size) describing: - Summary of your previous research - Interests and proposal for research 5. Two letters of recommendation (including one from the current supervisor, if available) [Selection process] Selection will be made based on application screening and interviews. [Requirements] Applicants must: - have Ph.D. (or be near the completion of the degree). - have strong motivations and ambitions to participate in the research above. [Number of openings] Two [Deadline for application] December 18th 2016 (will remain open if positions are not filled) [Application] Applications and/or any questions should be sent via mail or e-mail to: Integrated Systems Biology Laboratory (Shin Ishii-lab), Graduate School of Informatics, Engineering Bldg #1, Kyoto University Yoshida-honmachi, Sakyo, Kyoto 606-8501, Japan Email: kanae [at] sys.i.kyoto-u.ac.jp http://ishiilab.jp/kyoto/en/ Phone: +81-75-753-4908 Fax: +81-75-753-4907

Oct. 15, 2016

Lecturer/Senior Lecturer in Computer Science (Machine Learning / Biocomputation) (Closing Date 21 October)

by Steuber, Volker

Lecturer/Senior Lecturer in Computer Science (Machine Learning / Biocomputation) School of Computer Science University of Hertfordshire, UK Salary £32,004 to £48,327 per annum depending on qualifications and experience Full time position working 37 hours per week (1.0 FTE) Closing date 21 October 2016 Applications are invited for a Lecturer or Senior Lecturer in the School of Computer Science, University of Hertfordshire. The successful candidate will be expected to contribute to the School's teaching and curriculum development activities, and to strengthen its research activities. We are looking to recruit specifically a computer scientist with background in machine learning or data science related to biocomputation (including computational neuroscience). By Data Science we broadly mean the extraction of meaning from large quantities of data. The successful candidate will also have the flexibility to teach across mainstream topics in computer science. The School has an international reputation for teaching and research, with 58 academic staff, 20 adjunct lecturer staff, and 65 research students and postdoctoral research staff. With a history going back to 1958, the School teaches one of the largest cohorts of undergraduate students in the UK, and also delivers a thriving online computer science degree programme. The person appointed will be expected to contribute to learning and teaching relevant to core computer science topics, participate in curriculum review and development, design and develop new modules, and supervise student projects at all levels. The appointee will strengthen the research culture in the School by pursuing research as part of a larger research team, seeking external funding, publishing papers, supervising research students, and participating in commercial activity as appropriate. Preference will be given to candidates who can contribute to teaching and research as outlined above. Applicants must hold a PhD (or equivalent) in a relevant subject, possess excellent communication skills in English and the ability to teach at undergraduate and postgraduate level. It is desirable that candidates have a track record of publication, external research funding, collaboration across disciplines, experience of different types of assessment and higher education quality assurance. They should also have the ability to play a role in the routine running of the School of Computer Science. Applications should be made through http://www.herts.ac.uk/contact-us/jobs-and-vacancies/academic-vacancies (reference 014050). Informal enquiries may be addressed to Dr Volker Steuber (Head of the Biocomputation Research Group, v.steuber(a)herts.ac.uk) or Professor William Clocksin (Dean of School, w.clocksin(a)herts.ac.uk) Please note that applications sent directly to these email addresses will not be accepted. We are committed to providing a supportive environment. The university also provides an onsite childcare facility and child-centred holiday clubs. The University is required to meet UKVI visa regulations. Applicants who do not currently have the right to work in the UK will have to satisfy UKVI regulations before they can be appointed. ?

Oct. 14, 2016

High Performance Computing Workshop at SFN 2016

by Ted Carnevale

A few seats remain available in the workshop Using the Neuroscience Gateway Portal (NSG) for Parallel Simulations Saturday, Nov. 12 from 9 AM to noon which we are presenting in downtown San Diego as a satellite to this year's SFN meeting. This workshop will show you how to use this NSF-supported resource in your computationally-intensive modeling and data analysis projects. It will also feature presentations from several research teams about how they are using NSG in their own research. The registration fee is $25, but if you have already signed up for the NEURON course on Friday, Nov. 11, you may register for the NSG workshop for only $15. For a description of the workshop and its application form, see http://www.neuron.yale.edu/neuron/static/courses/nsg2016/nsg2016.html The registration deadline is Friday Oct. 28. --Ted

Oct. 13, 2016

Postdoctoral researcher to study cause-effect power of neural systems across spatiotemporal scale

by Hill Sean

Postdoctoral position in the Laboratory for the Neural Basis of Brain States Prof. Sean Hill, École Polytechnique Fédérale de Lausanne (EPFL) Campus Biotech, Geneva, Switzerland The Laboratory for the Neural Basis of Brain States (LNBBS), part of the Blue Brain Project, focuses on understanding cortical and thalamocortical structure and function and the relationship to states of the brain including wakefulness, sleep and anesthesia. LNBBS is part of the EPFL Blue Brain Project (BBP), a Swiss national brain initiative situated on the Campus Biotech in Geneva, Switzerland, applies advanced neuroinformatics, data analytics, high-performance computing infrastructure and simulation-based approaches to the challenge of understanding the structure and function of the mammalian brain in health and disease. A postdoctoral position is available in the laboratory of Prof. Sean Hill (EPFL, http://www.hill-lab.org : http://bluebrain.epfl.ch) in collaboration with the Prof. Giulio Tononi (Wisconsin Institute for Sleep and Consciousness, www.integratedinformationtheory.org ) to study cause-effect power of neural systems across spatiotemporal scales. Immediate funding is available for a project using the framework of integrated information theory [1] to study foundational questions regarding causation and emergence in a detailed model of a cortical column [2]. The model is a comprehensive, multi-scale digital reconstruction of rat somatosensory microcircuitry, consisting of over 31,000 biophysically detailed multi-compartment neurons with 55 layer-specific morphological and 207 morpho-electrical neuron subtypes. Causal properties are explored at micro scales and at multiple macro scales by black-boxing the model in various ways and applying measures of integrated information to the resulting macro level systems [1, 3]. Candidates are expected to have strong training in a discipline such as theoretical biology/neuroscience, physics, mathematics, computer science, or engineering. Experience in information theory, complex systems, and neural modelling software (e.g. Neuron, NEST) are a plus. Programming experience is required (knowledge of MATLAB, Python, and/or C++ is of advantage). Appointments are for an initial 1-year renewable contract, starting as soon as possible or until the position is filled. Candidates should send a CV, brief statement of previous research and future research interests, and email addresses and phone numbers of three references to: Sean Hill, (sean.hill(a)epfl.ch) For more information, contact Sean Hill (sean.hill(a)epfl.ch) or Giulio Tononi (gtononi(a)wisc.edu) [1] Tononi G, Boly M, Massimini M, and Koch C. Integrated information theory: from consciousness to its physical substrate. Nature Reviews Neuroscience (2016). [2] Markram et al. Reconstruction and Simulation of Neocortical Microcircuitry. Cell. 2015 Oct 8;163(2):456-92. doi: 10.1016/j.cell.2015.09.029. [3] Marshall W, Albantakis L, Tononi G (2016) Black-boxing and cause-effect power. arXiv:1608.03461 [q-bio.NC]

Oct. 13, 2016

Two NIH BRAIN Initiative funded computational postdoctoral positions available: Brown University and Mass. General Hospital

by Stephanie Jones

Hello, Can you please post the following ad to the compneuro mailing list? Thank you, Stephanie Two NIH BRAIN Initiative funded computational postdoctoral positions available: Brown University and Mass. General Hospital The field of neuroscience is experiencing unprecedented growth in the ability to record from and manipulate brain circuits in humans and in animal models. MEG/ EEG are the leading methods to non-invasively record human neural dynamics with millisecond temporal resolution. However, it is still extremely difficult to interpret the underlying cellular and circuit level generators of these ‘macro-scale’ signals without simultaneous invasive recordings. Supported by a BRAIN Initiative grant through NIH we have started a collaborative project between Brown University, Yale University and Massachusetts General Hospital (MGH) to develop and a new software tool for circuit level interpretation of human brain activity measured with MEG/EEG. We are hiring two post-docs to join our team. A three-year postdoctoral position at Brown University PI: Dr. Stephanie Jones contact: Stephanie_Jones(a)brown.edu A three-year postdoctoral position at Massachusetts General Hospital PI: Dr. Matti Hämäläinen contact: msh(a)nmr.mgh.harvard.edu The post-docs hired will work among a team of researcher at Brown University, MGH, and Yale University on the design and implementation of a user-friendly, GUI-driven, open-source model of neocortical circuitry for the interpretation of non-invasively measured human brain activity. The neural model will be integrated into existing source localization software (MNE-Python) so that researchers can study the location, time course, and neural mechanisms of their human brain imaging data all in one package. Additionally, the post-docs will work with several test case groups to apply the model in a variety of tasks and clinical conditions. Interested candidates must have experience in Python programming and software engineering. The postdoc at Brown will work more on the computational modeling aspect of the software while the post doc at MGH will concentrate on the integration of MEG/EEG source modeling with computational neural modeling. Candidates with knowledge in computational modeling using NEURON and/or source localization methods will be given preference. Please send a CV, statement of research interests, and three letters of recommendation to contact addresses listed above. ******************************************* Stephanie R. Jones, PhD Associate Research Professor Brown University Department of Neuroscience Stephanie_Jones(a)Brown.edu https://www.brown.edu/research/labs/jones/

Oct. 12, 2016

PhD Position in Computational Cognitive Neuroscience at FIU in Miami

by Fabián Soto

The Computational Cognitive Neuroscience Lab at FIU in Miami (PI Dr. Fabian Soto) is looking for a doctoral student to start in the Fall of 2017. The student will work in the development of new methods to test independent processing of stimulus dimensions in the brain, within a framework that combines general recognition theory (a multidimensional version of signal detection theory) and population encoding models. The developed methods will be applied to the analysis of EEG and fMRI studies on object categorization. Our lab's research focuses on understanding the interplay between learning and visual processes in object categorization. We use a combination of behavioral, computational, and brain imaging techniques. FIU is classified as an R1 (highest research activity) institution by the Carnegie Foundation. It is Florida’s fastest growing public research university, the fourth largest university in the US, and one of the nation’s largest hispanic-serving institutions. FIU has recently established a state-of-the-art neuroimaging center (the Cognitive Neuroscience and Imaging Center), which hosts a research-dedicated 3T Siemens MAGNETOM Prisma MRI scanner and a fully equipped mock scanner for pre-scan and movement training. If you know of any potentially interested candidates with a broad scientific background who are interested in neuroimaging, psychology, and computational modeling, please have them contact Dr. Fabian Soto at fabian.soto(a)fiu.edu. More information about FIU’s Cognitive Neuroscience doctoral program in Psychology is available at http://cn.fiu.edu. The deadline for application is December 1st of 2016. -- Fabian A. Soto Assistant Professor Department of Psychology Florida International University Modesto A. Maidique Campus 11200 SW 8th St, AHC4 460 Miami, FL 33199 Phone: 305-348-8423 Fax: 305-348-6670 Email: fabian.soto(a)fiu.edu

Oct. 10, 2016