September 2014 - Comp-neuro - lists.cnsorg.org

3 open PhD psoitions at the Neuroinformatics Lab at the Institute of Cognitive Science, University of Osnabrück, Germany [Reminder]

by Gordon Pipa

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

Sept. 1, 2014

Tenure Track Assistant Professot in Theoretical and Computational Neuroscience

by Liu, Robert C

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

Sept. 1, 2014

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

by Giugliano Michele

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

Sept. 1, 2014

Postdoctoral position studying neurovascular coupling

by Patrick Drew

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

Sept. 1, 2014

Call for Papers - Neural Networks special issue on Big Data

by Asim Roy

Apologies for cross posting. Special Issue on Neural Network Learning in Big Data [Special Issue on Neural Network Learning in Big Data] Neural Networks Special Issue: Neural Network Learning in Big Data Big data is much more than storage of and access to data. Analytics plays an important role in making sense of that data and exploiting its value. But learning from big data has become a significant challenge and requires development of new types of algorithms. Most machine learning algorithms encounter theoretical challenges in scaling up to big data. Plus there are challenges of high dimensionality, velocity and variety for all types of machine learning algorithms. The neural network field has historically focused on algorithms that learn in an online, incremental mode without requiring in-memory access to huge amounts of data. The brain is arguably the best and most elegant big data processor and is the inspiration for neural network learning methods. Neural network type of learning is not only ideal for streaming data (as in the Industrial Internet or the Internet of Things), but could also be used for stored big data. For stored big data, neural network algorithms can learn from all of the data instead of from samples of the data. And the same is true for streaming data where not all of the data is actually stored. In general, online, incremental learning algorithms are less vulnerable to size of the data. Neural network algorithms, in particular, can take advantage of massively parallel (brain-like) computations, which use very simple processors, that other machine learning technologies cannot. Specialized neuromorphic hardware, originally meant for large-scale brain simulations, is becoming available to implement these algorithms in a massively parallel fashion. Neural network algorithms, therefore, can deliver very fast and efficient real-time learning through the use of hardware and this could be particularly useful for streaming data in the Industrial Internet. Neural network technologies thus can become significant components of big data analytics platforms and this special issue will begin that journey with big data. For this special issue of Neural Networks, we invite papers that address many of the challenges of learning from big data. In particular, we are interested in papers on efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms), implementations on different computing platforms (e.g. neuromorphic, GPUs, clouds, clusters) and applications of online learning to solve real-world big data problems (e.g. health care, transportation, and electric power and energy management). RECOMMENDED TOPICS: Topics of interest include, but are not limited to: 1. Autonomous, online, incremental learning - theory, algorithms and applications in big data 2. High dimensional data, feature selection, feature transformation - theory, algorithms and applications for big data 3. Scalable neural network algorithms for big data 4. Neural network learning algorithms for high-velocity streaming data 5. Deep neural network learning 6. Neuromorphic hardware for scalable neural network learning 7. Big data analytics using neural networks in healthcare/medical applications 8. Big data analytics using neural networks in electric power and energy systems 9. Big data analytics using neural networks in large sensor networks 10.Big data and neural network learning in computational biology and bioinformatics SUBMISSION PROCEDURE: Prospective authors should visit http://ees.elsevier.com/neunet/ for information on paper submission. During the submission process, there will be steps to designate the submission to this special issue. However, please indicate on the first page of the manuscript that the manuscript is intended for the Special Issue: Neural Network Learning in Big Data. Manuscripts will be peer reviewed according to Neural Networks guidelines. Manuscript submission due: December 15, 2014 First review completed: March 1, 2015 Revised manuscript due: April 1, 2015 Second review completed, final decisions to authors: April 15, 2015 Final manuscript due: April 30, 2015 GUEST EDITORS: Asim Roy, Arizona State University, USA (asim.roy(a)asu.edu<mailto:asim.roy@asu.edu>) (lead guest editor) Kumar Venayagamoorthy, Clemson University, USA (gkumar(a)ieee.org<mailto:gvenaya@clemson.edu>) Nikola Kasabov, Auckland University of Technology, New Zealand (nkasabov(a)aut.ac.nz<mailto:nkasabov@aut.ac.nz>) Irwin King, Chinese University of Hong Kong, China (irwinking(a)gmail.com<mailto:irwinking@gmail.com>)

Sept. 1, 2014

PhD top-ups and full scholarships in Computational Neuroscience of Alertness

by Svetlana Postnova

*PhD top-ups and full scholarships in Computational Neuroscience of Alertness* Multiple PhD opportunities are available at the University of Sydney node of the Cooperative Research Centre for Alertness, Safety, and Productivity. *Supervisors: *Dr Svetlana Postnova, Dr Jong Won Kim*, *Prof. Peter Robinson. For the group website see http://sydney.edu.au/science/physics/research/complex-systems/brain-dynamic… *Projects* We focus on understanding the biological system controlling alertness and on developing quantitative models and tools to predict alertness in variety of situations and develop interventions to improve it. All projects involve quantitative modelling on the level of interacting brain nuclei and neurotransmitter systems with the effects manifested on the behavioural level. Project 1: Effects of light wavelength on the circadian system and alertness. Project 2: Individual variability in sleep-wake dynamics and vulnerability to shiftwork. Project 3: Real-time prediction of alertness using data fusion and modelling techniques. These opportunities are affiliated with the Cooperative Research Centre for Alertness Safety and Productivity which involves modellers, experimentalists, and industry partners from universities and industries across Australia and worldwide. Successful candidates will be located at the School of Physics of the University of Sydney and collaborating with sleep and chronobiology experimentalists across the University of Sydney, Monash University, and Harvard. All PhD projects provide an opportunity for up to 6 months placements with industrial partners. *Process and deadlines* For questions and to apply send an e-mail with CV to Dr Svetlana Postnova ( postnova(a)physics.usyd.edu.au) Full stipends ($25,392) from the Alertness CRC Ltd are available. High achieving applicants will be encouraged to apply for the prestigious APA/UPA (Australian) or IPRS/USYDIS (international) postgraduate scholarships. Successful candidates will be provided with additional top-up scholarships of $5000-$10.000 per year depending on merit. Applications for Alertness CRC Ltd stipends will be considered until the positions are filled. Applications for APA/UPA national scholarships close on the *31st of October 2014* to start in January 2015*. * http://sydney.edu.au/scholarships/research/postgraduate_awards.shtml#APAUPA Applications for IPRS/USYDIS international scholarships close on the *15th of December 2014 * to start in July 2015*.* http://sydney.edu.au/scholarships/prospective/international_postgraduate_sc… Best wishes Sveta -- Dr Svetlana Postnova CRC for Alertness Safety and Productivity & Complex Systems Group School of Physics, University of Sydney Physics Annex, A29, NSW 2006, Australia Phone: +61 2 9036 7971

Sept. 1, 2014