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PhD at CerCo, Toulouse, France
by Timothée Masquelier June 20, 2017

June 20, 2017

Beating Roger Federer: *Modeling visual learning and expertise through a bioinspired neural network embedded in an electronic device* *Goal: *PhD grant. *When:* starting from September 2017 (date may be flexible to some extent) *Topic:* How do expert tennis players, like Roger Federer for example, predict if a ball will bounce in or out the field to decide if it should be played or not? After thousands of trajectory presentations, best champions have developed extraordinary skills in such a task, but little is known on how the visual system turns selective to spatiotemporal properties of the visual stimulus (e.g., 3D position, velocity and acceleration) and learns how to make an efficient use of it. The goal of the project is to build an embedded system – based on FPGA circuits and ARM processor – an artificial neural networkwhich would replicate – and perhaps beat – the visual and anticipatory performances of these expert players. To achieve this goal successfully, we will develop a bio-inspired neural network, based on some of the key properties of human vision: the Smart NeuroCam (GST company) will be used to reproduce the retina functioning. It triggers its message under the form of spikes, in an asynchronous way (without any concept of frame per second), responding to spatial or temporal changes in the pattern of illumination. Several kinds of pre-processing filters can be implemented in VHDL language directly in the FPGA circuits, and the output is then sent to a neural network. The artificial network will learn to use this message, applying a simple learning rule, the Spike-Timing-Dependent Plasticity (STDP). This rule allows each neuron to become selective to a particular property of the stimulus, completely autonomously and with no supervision. Several layers will be built to allow perceiving more and more complex properties of the visual scene. Once the network will be established, its performances will be assessed in different conditions of learning and compared to those of the best tennis players. *The project is funded by a French National Research Agency (ANR)*, involving two sites and several researchers: - Robin Baurès, Benoit Cottereau, Timothée Masquelier and Simon Thorpe, CerCo, Toulouse. - Michel Paindavoine, GST, Dijon. *Where: *The candidate will be based at CerCo, Toulouse (France), and will make the interface with the two sites, with regular trips. The computational neuroscience part will be done at Toulouse, and electronic part at Dijon. *Tasks:* - Matlab (or Python) based simulations of numerical filters. These filters will be applied to the image processing from which spikes are generated and then sent to feed the neural network and STDP learning mechanism. - VHDL coding to implement these numerical filters into the FPGA circuits of the cameras - C/C++ coding of the neural network and STDP mechanism that should work on an embedded ARM processor system - Experimental tests that will allow evaluating the performance of the whole system, from spikes generation to visual properties learning of the embedded system, to predict tennis ball’s trajectories *Required skills:* - Strong knowledge on electronic, and openness to computational neurosciences - Knowledge in signal-image processing, and artificial neural network - Interest for multidisciplinary research - Ability to turn smoothly autonomous, once the road has been set - Ability to be at the interface of two scientific fields and two working areas - Programming with Matlab and/or Python for simulating the neural network - Programming in VHDL language for FPGA circuits - Programming in C/C++ language for porting the algorithms on ARM microprocessors - French is not a requirement if fluent in English, but willingness to learn would be beneficial *Citizenship Eligibility:* We discourage Iranian students to apply, since most likely the CNRS will not accept them for security/defense reasons, unfortunately. *Relevant publications for the project:* - Masquelier, T., Guyonneau, R. & Thorpe S.J. (2009). Competitive STDP-Based Spike Pattern Learning. Neural Comput, 21(5),1259-1276. - Masquelier, T. & Thorpe, S.J. (2007). Unsupervised learning of visual features through spike timing dependent plasticity. PLoS Comput Biol, 3(2):e31. - Cottereau, B.R., McKee, S.P. & Norcia, A.M. (2014). Dynamics and cortical distribution of neural responses to 2D and 3D motion in human. Journal of Neurophysiology 111(3), 533-543. - SmartNeuroCam by GST : https://gsensing.eu/fr/ category/sections/products *Contact:* *Robin Baurès, PhD* Associate Professor CerCo, Université Toulouse 3, CNRS CHU Purpan, Pavillon Baudot 31059 Toulouse Cedex 9 – France Office phone: 0033 (0)5 62 74 62 15 <05%2062%2074%2062%2015> Email : robin.baures(a)cnrs.fr *Pr Michel Paindavoine* GlobalSensing Technologies 14, rue Pierre de Coubertin 21000 Dijon email : michel.paindavoine(a)gsensing.eu -- Timothée Masquelier - timothee.masquelier(a)cnrs.fr - http://cerco.ups-tlse.fr/~masquelier/

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PhD student candidate, “Multi-scale epileptic networks”
by Paolo Bonifazi June 15, 2017

June 15, 2017

Thank you for your attention - I apologize for possible multiple posting. At the Biocruces Health Research Institute (Bilbao, Spain) we are looking for a PhD student to develop and carry on a project entitled “Multi-scale epileptic networks”, financed by the Spanish Ministry (MINECO) and leaded by Dr. Paolo Bonifazi (Ikerbasque Tenure Track Researcher at Biocruces, member of the Computational Neuroimaging laboratory leaded by Prof. J. Cortes; http://www.jesuscortes.info) in collaboration with the Cruces University Hospital (Bilbao, Spain), the Ruber International Hospital (Madrid, Spain) and the University of Bari (Italy; Dr. S. Stramaglia). The project, aimed at studying longitudinally the multi-scale topology of human epileptic networks, combines electrophysiological data recorded through deep electrodes (implanted in epileptic patients undergoing surgery), with functional and diffusion MRI (acquired before the electrodes implant and post surgery after about six and twelve months). Depending on the interest of the candidates, the project might also involve epileptic animal model studies (using optogenetics, in-vivo electrophysiology and/or high field MRI, in collaboration with other local research institutions). The motivated Spanish or International candidates, possibly with a background in either Physics, Mathematics, Computer Science or Engineering, should contact as soon as possible (best if within Wednesday the 20th of June) Dr. Paolo Bonifazi (paol.bonifazi(a)gmail.com or paolo.bonifazi(a)osakidetza.eus) for detailed information. The PhD fellowship (for a maximum of 4 years) is funded by the Basque Government and the Ikerbasque Foundation (http://www.ikerbasque.net/) Deadline for the PhD fellowship application is 2nd of July. ==================== Paolo Bonifazi, PhD Ikerbasque Tenure Track Researcher Computational Neuroimaging Laboratory Biocruces Health Research Institute Hospital Universitario Cruces Plaza de Cruces, s/n E-48903. Barakaldo, Spain Tel +34 94 600 6000 (ext. 5298) Email: paol.bonifazi(a)gmail.com; paolo.bonifazi(a)osakidetza.eus http://www.ikerbasque.net/paolo-bonifazi

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Call for Abstracts: Bernstein Conference 2017
by Zrinka Gattin June 14, 2017

June 14, 2017

*Call for Abstracts: Bernstein Conference 201**7* * **New deadline for abstract submission:* June 28, 2017 for abstracts aimed as contributed talks and posters July 31, 2017 abstracts aimed as posters only ************************************************************** Satellite Workshops September 12-13, 2017 Main Conference September 13-15, 2017 PhD Symposium September 12 & 15, 2017 ************************************************************** The Bernstein Conference started out as the annual meeting of the Bernstein Network Computational Neuroscience and has become the largest annual Computational Neuroscience conference in Europe with more than 500 international participants in recent years. This year the conference is organized by the Bernstein Center for Computational Neuroscience Göttingen. The main conference (Sep 13-15, 2017) will be accompanied by satellite workshops (Sep 12-13, 2017) and a PhD symposium (Sep 12 & 15, 2017). An important part of the main conference will be the two poster sessions. We are now inviting the submission of abstracts from all relevant areas. Authors of most accepted abstracts will get the chance for a poster presentation, a small number of abstracts will be selected for contributed talks during the main conference. Please note the earlier submission deadline for authors applying for a talk. All accepted abstracts will be published online and will be citable via Digital Object Identifiers (DOI). *DETAILS FOR ABSTRACT SUBMISSION:* Please note that the submission of an abstract does not replace the conference registration (www.bernstein-conference.de/registration <http://www.nncn.de/de/bernstein-conference/2017/registration>). Poster space is limited and early submission is encouraged. For abstract submission visit: www.nncn.de/en/bernstein-conference/2017/abstracts <http://www.nncn.de/de/bernstein-conference/2017/abstracts> *ABSTRACT SUBMISSION DEADLINES:* Posters to be considered as contributed talks: June 28, 2017 Other posters: July 31, 2017 *TRAVEL GRANTS* To support the participation of young researchers at the Bernstein Conference, the Bernstein Coordination Site offers 10 Travel Grants, each endowed with 500 €. Please find further information under www.nncn.de/en/bernstein-conference/2017/travel-grant <http://www.nncn.de/de/bernstein-conference/2017/travel-grant> *CONFERENCE DETAILS:* Conference registration is *OPEN* Early registration deadline: July 09, 2017 *ACCOMMODATION AND HOTEL RESERVATION:* *We strongly recommend early room booking!* *The number of available accommodation is limited due to several concurrent events. And many Hotels in Göttingen are already booked out for that week!* We arranged for room contingents in a variety of hotels that you may book by yourself by email or phone. Please follow the instructions at our Accommodations Website (http://www.nncn.de/de/bernstein-conference/2017/venue/accommodation) We would like to emphasize that these room contingents will be held open up to different expiration dates depending on the hotel (or until they are filled). Many expiration dates are already mid of June 2017. We strongly encourage participants to share rooms and to book rooms as a group. *We emphasize that it will be very difficult to book accommodation beyond the expiration dates. * Please find a list of the hotels at our Accommodations Website. VENUE Satellite Workshops, Main Conference and PhD Symposium: The Central Lecture Hall (ZHG), Platz der Göttinger Sieben 5, 37073 Göttingen, Germany VENUE Public Lecture: Alte Mensa, Wilhelmsplatz 1, 37073 Göttingen, Germany, September 13, 2017, 8 pm For more information on the conference, please visit the websitehttp://www.bernstein-conference.de We are looking forward to welcoming you in Göttingen! Program chair: Fred Wolf Koordinator: Zrinka Gattin Co-Organizers: Bernstein Coordination Site (BCOS): Alexandra Stein, Kerstin Schwarzwaelder -- Dr Zrinka Gattin Bernstein Center for Computational Neuroscience (BCCN) Goettingen Bernstein Focus Neurotechnology (BFNT) Goettingen PhD Program in Theoretical and Computational Neuroscience Am Fassberg 17 D-37077 Goettingen Phone: +49 (0)551 5176 418 Fax: +49 (0)551 5176 14418 E-Mail:zrinka@nld.ds.mpg.de

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Chair and Director in Neural Computation Research Group - University of Nottingham
by Stephen Coombes June 14, 2017

June 14, 2017

Dear all, The University of Nottingham is looking to appoint an outstanding individual as Chair and Director to lead the development of a new Neural Computation Research Group. This will be a joint appointment between the Schools of Mathematical Sciences and Psychology. For further information please follow the link below to the full job advert: http://www.nottingham.ac.uk/jobs/currentvacancies/ref/PROF176717 The closing date is Friday, 7th July 2017. Best regards, Steve ------------------------------------------------------- Stephen Coombes Professor of Applied Mathematics School of Mathematical Sciences Nottingham, UK Tel: 0115 846 7836 http://www.maths.nott.ac.uk/~sc/ ------------------------------------------------------- This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please send it back to me, and immediately delete it. Please do not use, copy or disclose the information contained in this message or in any attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. This message has been checked for viruses but the contents of an attachment may still contain software viruses which could damage your computer system, you are advised to perform your own checks. Email communications with the University of Nottingham may be monitored as permitted by UK legislation.

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Postdoctoral position on the Inventive Use of Mathematics
by Christian Lebiere June 12, 2017

June 12, 2017

A post doctoral position is available on a NSF project studying how mathematical knowledge is learned and then used in inventive ways. Candidates with a Ph.D. in cognitive psychology, cognitive neuroscience, computer science, or related fields are encouraged to apply. The project has taken many approaches to this question including behavioral studies, neural imaging, and computational modeling. The involvement of the post doc in this position will depend on their strengths, interests, and what they want to lean. The position has funding for at least 2 years. Interested candidates should send inquiries and applications (CV, research interests, references) to John Anderson (ja(a)cmu.edu)

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[INNS-BigData 2018] Call for Papers
by Teng Teck Hou June 11, 2017

June 11, 2017

[Apologies for cross-postings] ########################################################### CALL FOR PAPERS The 3rd INNS Conference on Big Data 2018 April 17-19, 2018, Bali, Indonesia Homepage: http://www.innsbigdata2018.org #######################Description:###################### The International Neural Network Society (INNS) is the premiere organization for individuals interested in a theoretical and computational understanding of the brain and applying that knowledge to develop new and more effective forms of machine intelligence. INNS was formed in 1987 by the leading scientists in the neural network field. Researchers and colleagues who work in the area of big data and machine learning, we are happy to announce "The 3 rd INNS Conference on Big Data and Deep Learning 2018 (INNS BDDL 2018) will be held on April 18 19, 2018 in Sanur Bali, Indonesia. The aim of this conference is to create a valuable and important forum for scientists and engineers throughout the world to present the latest research findings and idea at the forefront of Big Data and Deep Learning. Accepted papers will be published by Elsevier, Scopus indexed. Several papers will be selected for possible publication in top journals. The conference will feature a comprehensive technical program with technical tracks on: Track 1: Big Data Track 2: Big Data Algorithms Track 3: Deep Learning Track 4: Application Areas Important Dates ################################################################### * Tutorial and workshop proposals (Submission) 15 September 2017 * Tutorial and workshop proposals (Decision) 30 September 2017 * Paper submission 2 November 2017 * Decision notification 31 December 2017 * Conference 17 - 19 April 2018 ################################################################### Previous INNS Conference: INNS 2016 in Thessaloniki, Greece INNS 2015 in San Francisco, USA #################### Organizing committees ############### General chairs Seiichi Ozawa, Kobe University, Japan Ah-Hwee Tan, Nanyang Technological University, Singapore Program Chairs Plamen P. Angelov, Lancaster University, UK Asim Roy, Arizona State University, USA Mahardhika Pratama, Nanyang Technological University, Singapore Local Committee Chairs Dieky Adzkiya, Institut Teknologi Sepuluh Nopember, Indonesia Advisory Board Yew-Soon Ong, Nanyang Technological University, Singapore Robert Kozma, University of Memphis, USA Sankar K. Pal, Indian Statistical Institute, India Haibo He, University of Rhode Island, USA Witold Pedrycz, University of Alberta, Alberta, Canada Leszek Rutkowski, Czestochowa University of Technology, Poland Nikola Kasabov, Auckland University of Technology, New Zealand Fernando Gomide, University of Campinas, Brazil Marley Vellasco, Pontifícia Universidade Católica do Rio de Janeiro, Brazil Yoonsuck Choe, Texas A&M University Minho Lee, Kyungpook National University, South Korea Bao-Liang Lu, Shanghai Jiao Tong University, China Irwin King, the Chinese University of Hong Kong, Hong kong Mohammad Nuh, Institut Teknologi Sepuluh Nopember, Indonesia Joni Hermana, Institut Teknologi Sepuluh Nopember, Indonesia Heru Setyawan, Institut Teknologi Sepuluh Nopember, Indonesia Tutorials/Workshop Chairs Igor Skrjanc, University of Ljubljana, Slovenia Sundaram Suresh, Nanyang Technological University, Singapore Poster Sessions Chairs Eko Setiadji, Institut Teknologi Sepuluh Nopember, Indonesia Agus Salim, La Trobe University, Australia Special Sessions Chairs Justin Wang, La Trobe University, Australia Yongping Pan, National University of Singapore, Singapore Panel Chairs Sreenatha Anavatti, University of New South Wales, Australia Mukesh Prasad, University of Technology, Sydney, Australia Achmad Affandi, Institut Teknologi Sepuluh Nopember, Indonesia Awards Chairs Tapabrata Ray, University of New South Wales, Australia Dejan Dovzan, University of Ljubljana, Slovenia Richard J. Oentaryo, McLaren Applied Technologies, Singapore Publication Chairs Edwin Lughofer, Johannes Kepler University, Austria Jose Antonio Iglesias, Carlos III University of Madrid, Spain Moamar Sayed?Mouchaweh, Institute Mines Telecom Lille Douai, France Publicity Chair Simone Scardapane, Sapienza University, Italy Teng Teck Hou, Singapore Management University, Singapore Hendro Nurhadi, Institut Teknologi Sepuluh Nopember, Indonesia International Liaison Chairs Yun Sing Koh, University of Auckland, New Zealand Deepak Puthal, University of Technology Sydney, Australia Wirawan, Institut Teknologi Sepuluh Nopember, Indonesia Webmaster Mohamad Abdul Hady, Institut Teknologi Sepuluh Nopember, Indonesia Andri Ashfahani, Institut Teknologi Sepuluh Nopember, Indonesia Choiru Zain, La Trobe University, Australia ###### Topics and Areas include, but not limited to the following###### >>BIG DATA Autonomous, online, incremental learning in big data High dimensional data, feature selection, feature transformation for big data Scalable algorithms for big data Big data analytics Data stream analytics Parallel & distributed computing for big data analytics (cloud, map-reduce, etc.) Online learning Online multimedia/stream/text analytics Link and graph mining Big data and cloud computing, large scale stream processing on the cloud Big data and collective intelligence/collaborative learning Big data and hybrid systems Big data and self-aware systems Big data and infrastructure Big data visualization >>Big Data Algorithm Neuromorphic hardware for scalable machine learning Evolving systems for big data analytics Evolutionary systems and big data Fuzzy systems and big data Cognitive modelling and big data Probabilistic approach for big data Concept drift detection for big data Granular computing for big data Transfer learning for big data >>Deep Learning Deep belief network Convolutional neural network Long short term memory Deep network architecture Deep autoencoder Deep stacked network Deep learning for natural language processing Deep learning for machine vision Evolving deep network Transfer learning in deep learning Online deep learning >>Application Areas Banking and Securities Communications, Media and Entertainment Healthcare Providers Education Manufacturing & Natural Resources Government Insurances Retail & Wholesale Trade Transportation Energy & Utilities, Etc.

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Postdoctoral position and lab/manager position available in the Zacks lab
by Jeff Zacks June 8, 2017

June 8, 2017

Dear Colleagues, We have two positions available in the lab; one for a postdoctoral fellow, one for a lab manager/research assistant. Please pass these along to any graduating seniors or nearly-done PhD students you think would be appropriate. Thanks! Jeff Zacks Jeffrey M. Zacks, Ph.D. Associate Chair, Department of Psychological & Brain Sciences Professor of Radiology Washington University in Saint Louis 1 Brookings Drive St. Louis, MO 63130-4899 314-935-8454 314-935-7588 (fax) jzacks(a)wustl.edu <mailto:jzacks@wustl.edu> http://dcl.wustl.edu/~jzacks 1) Postdoctoral position in the computational cognitive neuroscience of event cognition Dynamic Cognition Lab, Washington University The Dynamic Cognition Lab, headed by Jeff Zacks, seeks a postdoctoral researcher to work on an ONR-funded project examining comprehension and memory of complex, naturalistic events. This effort will involve computational modeling, behavioral experiments, and pattern-based fMRI. It will engage collaborators at Wash U, and also at UC Davis, Princeton, Harvard, and NYU. The position is funded for three years with potential for extended funding. Ideally, candidates will be available to start in Fall 2017. Potential applicants may want to have a look at the lab web site (dcl.wustl.edu <http://dcl.wustl.edu/>) for information on current related research. (See also psychweb.wustl.edu, and neuroscience.wustl.edu for information on related resources.) A PhD in Psychology or Neuroscience is required for this position. Desirable additional qualifications include: * Previous experience with neuroimaging, especially MVPA * An interest in event cognition and memory * A promising publication record To apply, please send a statement of research interests and CV, and have two letters of evaluation sent by faculty familiar with your work. Email submission is fine; please send application materials or questions about the position to jzacks(a)wustl.edu. If you prefer paper mail the address is: Department of Psychological & Brain Sciences Washington University Saint Louis, MO 63130 2) Lab manager/research assistant Washington University in St. Louis, Psychology Department Seeking a motivated associate to assist with behavioral and functional MRI experiments, starting summer 2017. An ideal candidate would be a newly-graduated undergraduate who has a strong curiosity about cognitive and computational neuroscience, and has relevant coursework and laboratory experience in this area. Duties will include interacting with human participants, data collection and analysis, and also managerial functions such as scheduling facilities and coordinating with other research team members. Required qualification: * Undergraduate degree in psychology, neuroscience, or a related field. Desirable qualifications: * Programming skills * Research experience with human subjects * Experience with functional MRI * Experience with film production This full-time, federally funded position provides a great opportunity to gain experience before going on to an advanced degree. St. Louis is a vibrant, affordable city, and Washington University has a rich community of cognitive scientists and neuroscientists. Two-year commitment required. Health benefits provided. To apply, see the PDF application at the Dynamic Cognition Laboratory website, http://dcl.wustl.edu. Jeffrey M. Zacks, Ph.D. Washington University Department of Psychology Campus Box 1125 St. Louis, MO 63130-4899 314.935.8454 jzacks(a)wustl.edu

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Fully-funded PhD studentship in "Data-driven null models for big data networks"
by Mark Humphries June 8, 2017

June 8, 2017

We seek PhD candidates for the project "Data-driven null models for big data networks", supervised by Dr Mark Humphries at the University of Manchester. We are developing network theory approaches to analysing data in systems neuroscience (Humphries, 2017, https://doi.org/10.1101/115485 ). The aim of this PhD project is to develop an analysis framework for separating signal from noise in data-driven networks. We will develop new, flexible data-driven null models for network structure - models that will predict noise. Using these models, we will create powerful ways of extracting the signal network from observed data. With these signal networks, we will then explore how they change the conclusions we can draw from our observed data, what large-scale structures they uncover in the networks, and how they can track changes to networks over time. Applications will be assessed on a rolling basis, so please apply as soon as possible. This studentship is MRC-funded, so only open to UK and EU students. More information, and how to apply: https://www.findaphd.com/search/ProjectDetails.aspx?PJID=78216&LID=1020 Questions: mark.humphries(a)manchester.ac.uk<mailto:mark.humphries@manchester.ac.uk> Our lab: http://www.systemsneurophysiologylab.manchester.ac.uk/ _____________________________________________________________________________ Dr Mark Humphries | MRC Senior non-Clinical Research Fellow | Faculty of Biology, Medicine & Health http://www.systemsneurophysiologylab.manchester.ac.uk/ [0da17e2a-9ed5-496a-b161-9fd4491ce5c7]@markdhumphries <https://twitter.com/markdhumphries> Public blog: https://medium.com/the-spike

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Registration Open - EPFL Online Course: Simulation Neuroscience I
by Eilif Muller June 7, 2017

June 7, 2017

Dear Colleagues, I would like to bring to your attention this upcoming new course on Simulation Neuroscience we are offering online, leveraging the HBP Brain Simulation Platform. It is the first of 3 planned courses through which we will teach students to construct and simulate data-driven microcircuits, like the Blue Brain cortical model. More details are below. Many thanks for forwarding to students who may be potentially interested. Best regards, Eilif ===== ANNOUNCEMENT ===== The Center for Digital Education of the École polytechnique fédérale de Lausanne (EPFL), Switzerland in cooperation with the Blue Brian Project is welcoming students to participate in a new online course entitled: Simulation Neuroscience I - Reconstruction of a single neuron Faculty: Prof. Henry Markram, Prof. Idan Segev, Prof. Sean Hill, Prof. Felix Schuermann, Samuel Kerrian, Lida Kanari, Werner Van Geit, Dr. Srikanth Ramaswamy, Dr. Eilif Muller Abstract: Simulation Neuroscience is an emerging approach to integrate the knowledge dispersed throughout the field of neuroscience. The aim is to build a unified empirical picture of the brain, to study the biological mechanisms of brain function, behaviour and disease. This is achieved by integrating diverse data sources across the various scales of experimental neuroscience, from molecular to clinical, into computer simulations. In a series of three courses, you will learn to use the state-of-the-art modelling tools of the Human Brain Project Brain Simulation Platform to simulate neurons, build neural networks, and perform your own simulation experiments. This is the first course of the series that will teach you how to digitally reconstruct a single neuron. We invite you to join us and share in our passion to reconstruct, simulate and understand the brain! The course is targeted at senior bachelor, master or PhD students in science or engineering fields looking for an introduction to Simulation Neuroscience. It is a 6 week course, with an estimated course load of 5-7 hours per week. The registration deadline is June 13, 2017 The start date of the course is June 15, 2017 Registration is limited due to available compute resources, on a first-come, first-served basis. For more information: https://actu.epfl.ch/news/mooc-simulation-neuroscience-reconstruction-of-a-… ------------- Dr. Eilif Muller Section Manager - In Silico Neuroscience - Experimentation EPFL - Blue Brain Project QIJ 3ème étage CH-1015 Lausanne 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

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Permanent academic positions in computational neuroscience/ machine learning at assistant and associate professor level
by Eleni Vasilaki June 6, 2017

June 6, 2017

There are two permanent academic openings in the Department of Computer Science, University of Sheffield, in the area of Computational Neuroscience within the Machine Learning group. Lecturer/Senior Lecturer/Reader in Machine Learning and Computational Neuroscience. Lecturer/Senior Lecturer/Reader in Machine Learning and Robotics. Lecturer is roughly equivalent to Assistant professor and Senior Lecturer/Reader to Associate Professor in the US system. Since it was established in 1982, the Department of Computer Science at the University of Sheffield has attained an international reputation for its research and teaching. In the 2014 Research Excellence Framework (REF) exercise, we were ranked 5th out of 89 departments in the UK for computer science research. For more information please see: https://www.sheffield.ac.uk/dcs/jobs/index Prof. Eleni Vasilaki, DPhil CEng MIET Computer Science, University of Sheffield, www.dcs.shef.ac.uk/~eleni

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