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Call for Applications: Bernstein Award for Computational Neuroscience 2015
by Kerstin Schwarzwälder Nov. 11, 2014

Nov. 11, 2014

Dear colleagues, I would like to bring to your attention that for the tenth time, the German Federal Ministry of Education and Research (BMBF) has announced an open call for applications for the "Bernstein Award". The "Bernstein Award for Computational Neuroscience" is endowed with up to 1.25 Mio € for a period of five years and allows young scientists of all nationalities to establish an independent research group at a German university or research institution. The BMBF announcement can be found under the following links: German version <http://www.gesundheitsforschung-bmbf.de/de/2476.php> English version <http://www.gesundheitsforschung-bmbf.de/_media/Bernstein_Award_2015_Call_fo…> Posters to announce the Bernstein Award locally can be downloaded from here: German version <http://www.nncn.de/pdfs/poster_ausschreibung_bernsteinpreis2015_de> English version <http://www.nncn.de/pdfs/poster_ausschreibung_bernsteinpreis2015_en> Application deadline is April 15, 2015. Kind regards, Kerstin Schwarzwälder -- Dr. Kerstin Schwarzwälder Bernstein Coordination Site of the National Bernstein Network Computational Neuroscience Albert Ludwigs University Freiburg Hansastr. 9A 79104 Freiburg Germany phone: +49 761 203 9594 fax: +49 761 203 9585 schwarzwaelder(a)bcos.uni-freiburg.de www.nncn.de Twitter: NNCN_Germany <http://twitter.com/NNCN_Germany> YouTube: Bernstein TV <http://www.youtube.com/user/BernsteinNetwork> Facebook: Bernstein Network Computational Neuroscience, Germany <https://www.facebook.com/BernsteinNetwork> LinkedIn: Bernstein Network Computational Neuroscience, Germany <http://www.linkedin.com/company/bernstein-network-computational-neuroscienc…>

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G-Node Winter Course on Neural Data Analysis 2015
by Thomas Wachtler Nov. 11, 2014

Nov. 11, 2014

7th G-Node Winter Course on Neural Data Analysis February 23 - 27, 2015 in Munich, Germany The German Neuroinformatics Node (G-Node) organizes its seventh international training course to promote state-of-the-art methods of neural data analysis among PhD students and postdocs. The course offers hands-on experience with model-driven analysis of data from intra- and extracellular electrophysiology. We encourage applications from students/postdocs with an experimental background that want to widen their repertoire of analysis methods, as well as from students with a theoretical background that have an interest in analyzing physiological data. Participants must have ample programming skills in Matlab or Python. Faculty: Jan Grewe · Eberhard Karls Universität Tübingen Alex Loebel · Ludwig-Maximillians-Universität München and BCCN München Moritz Grosse-Wentrup · Max Planck Institute for Intelligent Systems Tübingen Thomas Wachtler · Ludwig-Maximillians-Universität München and BCCN München Topics: · Short-term plasticity · Spectral analysis · Mutual information · Machine learning · Neural tuning and decoding · Deadline for application: December 19, 2014 For more information visit http://www.g-node.org/dataanalysis-course-2015 With best regards, Jan Grewe (Organizer, Tübingen) and Thomas Wachtler (Local Organizer, Munich)

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Doctoral studies at the Princeton Neuroscience Institute
by Yael Niv Nov. 11, 2014

Nov. 11, 2014

The Graduate Program in Neuroscience at Princeton University offers a unique and intensive program of study spanning molecular, cellular, systems and cognitive neuroscience, followed by advanced research in a world-class Princeton laboratory. We seek highly motivated and creative students in our efforts to understand the brain. A listing of faculty affiliated with the program can be found online at www.princeton.edu/neuroscience, and below. Our doctoral program is flexible and individually-tailored, and we encourage students to pursue research with more than one faculty and across departmental boundaries. Applications for entry in the Fall of 2014 are now being accepted, with a deadline of December 1. For details, including contact information, please visit www.princeton.edu/neuroscience. Michael Berry - Neural computation in the retina William Bialek - Interface between physics and biology Matthew Botvinick - Neural foundations of human behavior Lisa Boulanger - Neuronal functions of immune molecules Carlos Brody - Quantitative and behavioral neurophysiology Tim Buschman - Neural dynamics of cognitive control Jonathan Cohen - Neural bases of cognitive control Lynn Enquist - Neurovirology Liz Gavis - Neural development and mRNA localization in Drosophila Alan Gelperin - Learning, memory and olfaction Asif Ghazanfar - Neurobiology of primate social agents Elizabeth Gould - Neurogenesis and hippocampal function Michael Graziano - Sensorimotor integration Charles Gross - Functions of the cerebral cortex in behavior Uri Hasson - Temporal scales of neural processing Philip Holmes - Mathematical modeling John Hopfield - Computational neurobiology/biophysics Barry Jacobs - Brain monoamine neurotransmitters Sabine Kastner - Neural mechanisms for visual perception Carolyn McBride - Molecular and neural basis of behavioral evolution Mala Murthy - Neurophysiology of olfactory and auditory perception in Drosophila Coleen Murphy - Molecular mechanisms of aging Yael Niv - Reinforcement learning and decision making Ken Norman - Neural bases of episodic memory Jonathan Pillow - Neural information processing, machine learning, and statistical modeling of neural data Sebastian Seung - Structure and function of neural circuits Joshua Shaevits - Neural and behavioral dynamics in simple organisms David Tank - Neural circuit dynamics Jordan Taylor - Motor control and learning Alexander Todorov - Cognitive neuroscience of social cognition and behavior Nicholas Turk-Browne - Cognitive neuroscience of attention, perception and memory Samuel Wang - Dynamics and learning in neural circuits Ilana Witten - Neural circuits underlying reward and motivation

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Faculty positions in applied statistics
by Robert Rosenbaum Nov. 11, 2014

Nov. 11, 2014

Dear colleagues, The ACMS department at Notre Dame is hiring two statistics professors, one tenured and one tenure-track. The department strongly supports interdisciplinary and collaborative research, so researchers who focus on statistical applications in neuroscience are encouraged to apply. Applications should be received by Dec 1. See the full advertisement below. The University of Notre Dame has committed four new faculty positions to the Department of Applied and Computational Mathematics and Statistics (ACMS) to be filled over the next two years. Positions at both the junior and senior level are available. This year we seek to hire a statistician at the tenured level, and a statistician at the tenure-track level, in any areas of research that build on our existing activities. Preference will be given to applicants whose statistical research includes multi-disciplinary collaborations. ACMS includes research groups in applied mathematics, statistics and computational science. The current fourteen faculty members have research interests in Bayesian statistics, statistical bioinformatics and high-dimensional data, finance, statistics in networks and Big Data, multiscale modeling of blood clotting and biofilms, mathematical modeling in cell biology and tumor growth, MEMS, and numerical and computational algorithms and computational neuroscience. ACMS offers a Bachelor of Science, a doctoral degree, a research masters degree and a professional masters degree. ACMS is a member of the College of Science. The successful applicant must have a doctorate in statistics, biostatistics or a closely related field, and a record of success in both research and teaching. The teaching load in ACMS is 3 courses per year, and the position begins in August 2015. Applications received by December 1, 2014 will be given full consideration. Applications, including a cover letter, curriculum vitae and research and teaching statements, should be filed through MathJobs (www.MathJobs.org) Applicants should also arrange for at least three letters of recommendation to be submitted through the MathJobs system. These letters should address the applicant's research accomplishments and supply evidence that the applicant has the ability to communicate articulately and teach effectively. Senior faculty are invited to contact the Department Chair, Steven Buechler, at buechler.1(a)nd.edu, at any time. Notre Dame is an equal opportunity employer, and we particularly welcome applications from women and minority candidates. — Robert Rosenbaum Assistant Professor Department of Applied and Computational Mathematics and Statistics University of Notre Dame

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Physics of Neural Systems focus topic at the 2015 American Physical Society March Meeting, March 2-6, San Antonio, TX
by Ilya Nemenman Nov. 10, 2014

Nov. 10, 2014

Dear Colleagues: This is the final reminder that the 2015 American Physical Society (APS) March meeting (March 2-6, 2015; San Antonio, TX) will emphasize “Physics of Neural Systems” as one of the focus topics supported by the Division of Biological Physics. We expect multiple sessions resulting from this focus topic, addressing recent advances in understanding of the structure and the dynamics of neural circuits responsible for sensing, memory, and motor output. Arguably, in the last few years, we have found out more about the dynamics of neural circuits than we have in all of the previous decades combined. Thus we solicit submissions of contributed presentations to the March meeting, focusing on a broad range of topics on the intersection of physics and neuroscience, such as quantitative experimental protocols, modeling of neural dynamics, analysis of collective computation in neural circuits, and others. The neural focus at the meeting will be anchored by talks by Tatyana Sharpee (Salk Institute) and Christopher Fang-Yen (University of Pennsylvania), among others. March meeting abstract submission website: http://www.aps.org/meetings/march/scientific/index.cfm <http://www.aps.org/meetings/march/scientific/index.cfm> Abstract submission deadline: November 14, 2014, 5:00pm EST While the actual timing of the neuro sessions at the meeting will not be known until December and will depend on the number of qualified submissions, the sessions will be scheduled not to conflict with other computational neuroscience meetings, such as COSYNE. APS March meeting is the largest physics meeting in the world, attracting about 10,000 physicists. At the meeting, the APS Division of Biological Physics supports one of the largest and scientifically diverse programs on the interface of physics and biology, from molecular and cellular biophysics, to computational neuroscience and population dynamics, featuring typically more than 500 talks every year. We are looking forward to receiving your abstracts. If you have any questions about neuroscience at the March Meeting, please don’t hesitate to contact Ilya Nemenman (ilya.nemenman(a)emory.edu <mailto:ilya.nemenman@emory.edu>). Sincerely, Ilya Nemenman Associate Professor of Physics and Biology Emory University, Atlanta, GA and Vice-Chair, Division of Biological Physics (DBIO) American Physical Society (APS) http://nemenmanlab.org <http://nemenmanlab.org/> Biophysicist? Join APS/DBIO and come to the March Meeting!

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Can local inhibition lead to long-range competition?
by Dylan Richard Muir Nov. 10, 2014

Nov. 10, 2014

Dear colleagues, We would like to draw your attention to a recent publication, where we examine the spatial range of competition expected for columnar visual cortex, given known features of cortical anatomy. Reprints are freely available from the author’s homepage (see link below). Models of cortex that assume long-range competition are widespread, although it has long been known through anatomical studies that the spatial extent of inhibition is in fact more restricted than that of excitation. We analyzed straightforward models of interacting cortical columns, and performed simulations of larger models, to show how the spatial scales of excitation and inhibition interact to produce competition through disynaptic inhibition. We found that although disynaptic inhibition is widespread, the presence of competition across the cortical surface is predicted well by the anatomy of direct excitatory and inhibitory coupling. In comparison, the effect of multisynaptic network interactions was very small. This implies that for realistic models of cortex, which should include short-range inhibition and longer-range excitation, the spatial extent of competition is likely to be even narrower than the range of inhibitory connections. Muir and Cook, "Anatomical Constraints on Lateral Competition in Columnar Cortical Architectures", Neural Computation 26 8:1624–1666. Reprints: http://dylan-muir.com/resources/docs/neco_a_00613.pdf Journal: http://dx.doi.org/10.1162/NECO_a_00613 Summary: http://dylan-muir.com/projects/lateral_competition_cortex/ Best regards, Dylan Muir. Dylan Muir | Post-doctoral researcher Biozentrum, University of Basel | Klingelbergstrasse 50/70 | CH-4056 Basel Phone: +41 61 267 17 75 | Email: dylan.muir(a)unibas.ch www.biozentrum.unibas.ch | www.dylan-muir.com

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Postdoctoral position in computational systems neuroscience (sensory processing & decision-making)
by Ralf Haefner Nov. 10, 2014

Nov. 10, 2014

Postdoctoral position in computational systems neuroscience (sensory processing & decision-making) We are looking for a postdoctoral researcher to join the group of Ralf Haefner in the department for Brain & Cognitive Sciences at the University of Rochester (NY). The focus of our group is on understanding the neural basis of perceptual inference. Based on the assumption that the brain performs probabilistic inference using an internal model of the world, we ask questions such as: What is the nature of the internal model? How is it learnt? How are posterior beliefs represented by spiking responses of populations of neurons and what algorithm does the brain use to compute its beliefs? The position requires strong mathematical and good programming skills. The ideal candidate would also be familiar with machine learning techniques, especially regarding generative models and MCMC-sampling-based probabilistic inference. Possible research projects range from purely theoretical to data-driven. Our collaborations with electrophysiology labs allow for testing of theoretical models using state-of-the-art cortical population recordings in vivo and, if desired, the opportunity to record your own data. More information about past work is available here: http://tinyurl.com/rmhaefner and a preprint of a manuscript representative of future work here: http://arxiv.org/abs/1409.0257 For details on current and possible future projects, and general information, please contact us directly. The successful candidate with join a world-class department with a wide range of research interests ( https://www.bcs.rochester.edu/research/index.html ) and a strong tradition in probabilistic modeling. Start date and duration are flexible. Please send applications including a CV and names of 2-3 references by email. Please contact us as soon as possible if you'd like to meet at the upcoming SfN or NIPS conferences. Ralf Haefner Assistant Professor Brain & Cognitive Sciences University of Rochester (NY) rhaefner(a)bcs.rochester.edu

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Postdoctoral research position: modelling musical preference decisions
by Marcus Pearce Nov. 10, 2014

Nov. 10, 2014

Dear All (with apologies for cross-posting), A postdoc position is available at Queen Mary, University of London as part of an EPSRC-funded project <http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/M000702/1>on predicting musical choices using computational models of cognitive and neural processing. The goal of the project is to understand the cognitive and neural processes involved in musical preference decisions using computational modelling that incorporates the structure of the music, the listener and the listening context. The project also involves behavioural and EEG data collection and analysis using machine learning. Salary: £31,735 - £35,319 per annum Closing date: 14th November 2014 Start date: January 2014 or soon thereafter Duration of post: 14 Months For further information and to apply see: http://music-cognition.eecs.qmul.ac.uk/postdoc.html Marcus -- Lecturer in Sound and Music Processing Queen Mary, University of London Mile End Road, London E1 4NS, UK Tel: +44 (0)20 7882 6207 Web:http://webprojects.eecs.qmul.ac.uk/marcusp Lab:http://music-cognition.eecs.qmul.ac.uk/

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Postdoctoral position in Houston--Multisensory Integration and Visual Perception
by Beauchamp, Michael S Nov. 8, 2014

Nov. 8, 2014

The Beauchamp Lab at the University of Texas Medical School at Houston (http://openwetware.org/wiki/Beauchamp) seeks a postdoctoral fellow for a federally-funded research program. The main focus of the lab is to understand the neural substrates of multisensory integration and visual perception. The laboratory uses multiple techniques, including fMRI and electrocorticography: experience with one of these techniques (or related) is a requirement. Data analysis is carried out with specialized software, including AFNI, EEGlab and Fieldtrip, requiring that applicants be comfortable with writing and modifying C-shell scripts. An interest in computational and quantitative modeling of behavioral and neuroimaging data is an asset. Houston has a rich neuroimaging and neuroscience community, with Rice University, Baylor College of Medicine, and the University of Texas Health Science Center at Houston as partners in the Gulf Coast Consortia for quantitative biomedical sciences. Facilities include multiple research‑dedicated 3 T scanners, a Blackrock Microsystems 128‑channel recording system, infrared eye trackers, and MR-compatible transcranial magnetic stimulation (TMS). The position is available immediately and the review of applications will continue until the position is filled. Please send your CV to beauchamplab(a)gmail.com<mailto:beauchamplab@gmail.com> for an immediate reply.

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Tenure Track Assistant Professor in Theoretical and Computational Neuroscience
by Liu, Robert C Nov. 7, 2014

Nov. 7, 2014

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

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Faculty position in Information Engineering and Medical Neuroscience, Cambridge
by Máté Lengyel Nov. 7, 2014

Nov. 7, 2014

Faculty position in Information Engineering and Medical Neuroscience Department of Engineering, University of Cambridge, UK Applications are invited for a University Lectureship (~ US Assistant /Professor equivalent) in the Control Group in the Department of Engineering. Exceptional candidates are sought with the potential to develop a record of world-class research commensurate with the Department’s international reputation. The current faculty members in the Cambridge Control Group are: Emeritus Professor Keith Glover, Professor Jan Maciejowski, Professor Rodolphe Sepulchre (Professor of Engineering), Professor Malcolm Smith (Head of Group) and Dr Glenn Vinnicombe (Reader). Candidates will be expected to contribute to undergraduate and graduate teaching in the general area of Control Engineering and possibly other related areas of Information Engineering. The closing date for applications is 9 January, 2015. The interviewing panel will meet soon after the closing date. Short-listed candidates will be invited to visit the Department, give a short seminar/lecture and attend a formal interview. The field of this University Lectureship is at the interface between Information Engineering and Medical Neuroscience. Unprecedented challenges and opportunities exist in this area as a consequence of a fast-developing technology of actuating and sensing devices at the neuronal scale (e.g. neural implants, multi-electrode recordings, and optogenetic techniques). The successful candidate will preferably be working in the field of Control Engineering with a research record in problems of medical neuroscience, and with appropriate theoretical expertise (nonlinear systems). It could be filled by someone whose primary expertise is in a different branch of Information Engineering, but the ability to contribute to teaching in one or more of the ‘core’ areas of Information Engineering (Control, Signal processing, Information theory, etc) will be expected. Medical neuroscience and brain science is a current focus of most national and international funding agencies. Funding opportunities will exist in conjunction with Cambridge Neuroscience. The lectureship will strengthen the Department’s Bioengineering strategic theme. Informal enquiries can be made to Professor Rodolphe Sepulchre (r.sepulchre(a)eng.cam.ac.uk) or Professor Malcolm Smith (mcs(a)eng.cam.ac.uk)

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PhD studies in Comp Neuro and Neural Engineering at the University of Washington
by Adrienne Fairhall Nov. 6, 2014

Nov. 6, 2014

PhD studies in Computational Neuroscience and Neural Engineering at the University of Washington The University of Washington has a rich, active and highly collaborative community of researchers in the field of computational neuroscience (http://compneuro.washington.edu/) and neural engineering. The University of Washington is a vibrant research university with a beautiful campus in a spectacular urban setting, with an ERC Center in Sensorimotor Neural Engineering (http://www.csne-erc.org/) the UW Institute for Neuroengineering (uwin.washington.edu) close connections to the local tech industry and the Allen Institute for Brain Science. UW is also a major data sciences center with interdisciplinary interactions coordinated through the eSciences Institute (http://escience.washington.edu) The city is a short distance from wilderness and outstanding summer and winter outdoor adventure. While faculty advisors belong to a wide range of different departments, researchers come together regularly for seminars, journal clubs and a yearly retreat. Many student funding opportunities exist through multiple training grants, UWIN and the CSNE. Doctoral programs encourage collaborative research projects across departmental boundaries, but admissions and first-year course work and formal requirements are handled by graduate programs individually. Students interested in this area should apply to the program that best fits their background, interests and career goals. Relevant programs, websites and application deadlines include: Neuroscience, http://depts.washington.edu/behneuro/ , Dec 1 Bioengineering, http://depts.washington.edu/bioe/, Dec 1 Computer Science and Engineering, www.cs.washington.edu/, Dec 15 Applied Mathematics, www.amath.washington.edu/, Jan 15 Speech and Hearing, http://depts.washington.edu/sphsc/, Feb 15 Biological Physics, Structure and Design, http://depts.washington.edu/bpsd/, Dec 1 Biology, www.biology.washington.edu/, Dec 1 Faculty include: Wyeth Bair (Neurobiology and Behavior, CSE): Computer modeling of visual cortical circuits Geoff Boynton (Neuro, Psychology): Functional imaging of vision Beth Buffalo (Neuro): Navigation and memory in primates Bing Brunton (Biology and Data Sciences): High dimensional neural data Howard Chizeck (CSE): Performance metrics for neural interfaces Tom Daniel (Neuro, Biology): Sensorimotor integration and flight control Horacio de la Iglesia (Neuro, Biology): Circadian rhythms Marcel den Nijs (Physics): Statistical mechanics of brain function Adrienne Fairhall (Neuro, BPSD, Physics): Adaptive neural coding and sensorimotor integration Eb Fetz (Neuro): Motor control and brain-computer interfaces Ione Fine (Neuro, Psychology): Human visual psychophysics and imaging David Gire (Neuro, Psychology): Mammalian olfaction Bertil Hille (Neuro, BPSD): Biophysics of neuronal signal transduction Greg Horwitz (Neuro): Cortical color processing Nathan Kutz (A Math): Nonlinear dynamics and dimensionality reduction Adrian KC Lee (Neuro, Speech and Hearing): Auditory scene analysis with imaging Chet Moritz (Neuro, Rehabilitation Medicine): Neural prosthetics Sheri Mizumori (Neuro, Psychology): Neurobiology of decisions, learning, and memory Bill Moody (Neuro, Biology): Cortical development Scott Murray (Neuro, Psychology): Visual neuroimaging Jay Neitz (Neuro): Color vision Jeff Ojemann (Neuro, Neurology): Human neural function and neuroprosthetics Anitha Pasupathy (Neuro): Neurobiology of visual shape processing David Perkel (Neuro): Neural mechanisms of vocal learning Steve Perlmutter (Neuro): Motor control Chantal Prat (Neuro, Speech and hearing): Auditory processing Nino Ramirez (Neuro): Neural control of rhythmic activity Rajesh Rao (Neuro, CSE): Computational modeling and brain-computer interfaces Fred Rieke (Neuro, Physics, BPSD): Sensory signal processing in the retina Jeff Riffell (Neuro, Biology): Neuroecology and chemosensation Ed Rubel (Neuro): Development of the auditory system Jay Rubinstein (Neuro, Bioengineering): Biophysics and engineering of cochlear implants Eric Shea-Brown (Neuro, A Math): Nonlinear dynamics in neural computation and coding Bill Spain (Neuro): Biophysics of neuronal computation Kat Steele (Mec Eng): Human movement Emo Todorov (Neuro, A Math, CSE): Optimal motor control

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PhD in Cogn Neuro, Univ of Wisc-Milwaukee
by Adam S Greenberg Nov. 6, 2014

Nov. 6, 2014

Dear Colleagues, Please pass the following information along to your undergraduates who plan to pursue a PhD in Cognitive Neuroscience beginning in the Fall of 2015. Faculty at the University of Wisconsin-Milwaukee (UWM) are actively recruiting graduate students who intend to earn a PhD conducting cognitive neuroscience research. UWM has an extremely energetic & cohesive group of faculty using cognitive neuroscience techniques to study the neural bases of learning & memory, attention, perception, dementia, addiction, anxiety, depression, and motor control. Collectively, our labs form a group of more than 50 faculty, postdocs, graduate students, research scientists, and research assistants all working on cognitive neuroscience at UWM. A major strength of our program is our depth - cognitive neuroscientists at UWM are part of a much broader community of researchers whose interests range from cellular to systems-level neuroscience (see http://www4.uwm.edu/neuroscience for more information about UWM's Neuroscience Program). Labs of the following cognitive neuroscience faculty are currently interested in accepting graduate students: Ira Driscoll, PhD --> Cognitive Neuroscience of Aging Lab (http://www.uwmdriscolllab.com) Adam S. Greenberg, PhD --> Sensory Neuroscience, Attention, & Perception Lab (http://SNAPlaboratory.com<http://snaplaboratory.com/>) Anthony J. Greene, PhD --> Greene Cognitive Neuroscience Lab (http://www4.uwm.edu/people/ag) Deborah Hannula, PhD --> Memory & Brain Lab (https://pantherfile.uwm.edu/hannula/brainlab) Fred Helmstetter, PhD --> Helmstetter Lab (http://pantherfile.uwm.edu/fjh/www/helmlab) Wendy Huddleston, PhD --> Visuomotor Lab (http://www4.uwm.edu/visuomotor) Christine Larson, PhD --> Affective Neuroscience Lab (http://<http://uwmlarsonlab.org/>uwmlarsonlab.org<http://uwmlarsonlab.org/>) Krista M. Lisdahl, PhD --> Brain Imaging & Neuropsychology Lab (http://uwmBraINlab.com<http://uwmbrainlab.com/>) Ali Borji, PhD --> Vision & Learning Lab (http://pantherfile.uwm.edu/borji/www) These labs make use of a large array of tools including fMRI, TMS, eye-tracking, MEG, EEG, DTI, psychophysical methods, and computational modeling. In addition to two existing 3 Tesla MRI scanners, we are also excited about the recent arrival of a research-dedicated 7 Tesla MRI scanner at our partner institution, the Medical College of Wisconsin. Students in our program interact with biophysicists, neurologists, and radiologists through the world-renown Center for Imaging Research: http://www.mcw.edu/CIR/AboutUs/About-the-Center.htm Milwaukee is a vibrant, inexpensive city on the shores of Lake Michigan (90 miles from Chicago) with a thriving urban culture, food, arts & music scene. An award-winning network of parks and biking/hiking trails allow for plentiful outdoor activities during all seasons. Research experience is strongly desirable. Students in good standing typically receive financial support for five years, in the form of research, teaching or fellowship positions. Students are encouraged to contact the above faculty directly by email, and can apply through the graduate programs listed below (depending on the lab they're interested in). NOTE: Please come visit our booth (#41) at SfN 2014 during the Graduate School Fair on 11/15 & 11/16 to talk to one of us about our program and answer any questions you may have. PhD in Experimental Psychology/Neuroscience (applications due December 1, 2014): http://www4.uwm.edu/letsci/psychology/graduate/phdprograms/experimental/ind… PhD in Clinical Psychology (applications due December 1, 2014): http://www4.uwm.edu/letsci/psychology/graduate/phdprograms/clinical/ PhD in Health Sciences/Kinesiology (rolling admissions): http://www4.uwm.edu/chs/academics/phd_health_sciences/ PhD in Computer Science/Engineering (rolling admissions); http://uwm.edu/engineering/academics-2/graduate/doctoral-programs-in-engine… ___________________________ Adam Greenberg, Ph.D. Assistant Professor University of Wisconsin-Milwaukee Department of Psychology P.O. Box 413 Milwaukee, WI 53201 email: agreenb(a)uwm.edu<mailto:agreenb@uwm.edu> Tel. (414) 229-1106 Fax (414) 229-5219 http://www.snaplaboratory.com/ ___________________________

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Postdoctoral Position at the Bernstein Center Freiburg, University of Freiburg, Germany
by Birgit Ahrens Nov. 6, 2014

Nov. 6, 2014

*PostDoc Position in Non-Clinical Epilepsy Research in the Biomicrotechnology lab of Prof. Ulrich Egert* We are currently offering a PostDoc position (2 years) in the Laboratory for Biomicrotechnology (http://www.bcf.uni-freiburg.de/people/details/egert) at the University of Freiburg. The project investigates mechanisms underlying mesiotemporal lobe epilepsy from the perspective of the dysfunction of interaction between subnetworks in the hippocampal formation (Froriep et al. 2012, Epilepsia). We aim to use targeted stimulation to reduce the circuit's susceptibility for seizures. For this project, we are searching for a neurophysiologist to implement a new paradigm for stimulation in a mouse model of epilepsy. It is essential that you have a background in neuroscience, ideally in experimental neurophysiology in vivo as well as a PhD degree. You should further be competent in data analysis and have an affinity for the network perspective. The project is part of the Cluster of Excellence "BrainLinks-BrainTools'' (www.brainlinks.uni-freiburg.de) together with the Bernstein Center Freiburg (www.bcf.uni-freiburg.de) and will combine neurophysiology, computational neuroscience and neurotechnology. *Please apply using our online form at https://yoda.bcf.uni-freiburg.de/* Further details on: www.bcf.uni-freiburg.de/jobs Contact: Dr. Birgit Ahrens Teaching & Training Coordinator Bernstein Center Freiburg Hansastr. 9a 79104 Freiburg, Germany birgit.ahrens(a)bcf.uni-freiburg.de

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[jobs] Post Doctoral Position in Embodied Neural Computation at the University of Southern Denmark in Odense
by poramate＠manoonpong.com Nov. 5, 2014

Nov. 5, 2014

The Embodied AI and Neurorobotics Lab, part of Centre for BioRobotics at the Maersk Mc-Kinney Moller Institute at the University of Southern Denmark, invites applications for a position as postdoc in embodied neural computation. The position is available starting fromMarch2015, or as soon as possible thereafter, for up to two years. Description The recently established Embodied AI and Neurobotics lab aims to 1) develop modular bio-inspired robots and their modular neural mechanisms towards embodied autonomous locomotion systems with adaptivity, energy efficiency, and versatility; 2) understand complex dynamical interactions between physical and computational components in embodied neural closed-loop systems. Recent developments of our embodied (neuro) robotic systems include Locokit robots (<http://locokit.sdu.dk/>) and AMOS hexapod walking robots (<http://manoonpong.com/AMOSII.html>). To further this vision, we are recruiting one highly motivated postdoctoral scientist in the fields of Machine learning, Computational Neuroscience, Embodied AI, and Robotics, to work on neural predictive control for goal-directed learning and multi- scale adaptation. The predictive control will be used for autonomous acoustic navigation and communication of walking robots in complex environments. The successful candidate will be expected to have 1) a PhD degree in electrical engineering and computer science, computational neuroscience, artificial intelligence, physics of complex systems, or a quantitative field, 2) articles published in international peer-reviewed journals documenting experience with embodied neural computation, and 3) strong background on reinforcement learning (such as continuous time actor-critic), artificial neural networks (in particular reservoir computing), nonlinear dynamic systems and robotics (e.g., walking robots), and 4) good programming skills (e.g., C, C++). Additionally, the candidate should have excellent writing skills and be able to work independently. The successful candidate for the position will be affiliated to Centre for BioRobotics at the Maersk Mc-Kinney Moller Institute, the University of Southern Denmark. Applicants should provide a covering letter explaining their approach to the problem of predictive control alluded to above, and at most three articles illustrating their publication record and research interests, in addition to standard items such as CV, full publication list, etc. (see below). Applications will be considered continuously until the position is filled.Contact Information: Further information is available from Assoc. Prof. Poramate Manoonpong, The Maersk Mc-Kinney Moller Institute, Tel: +4565508698, Email: <poma(a)mmmi.sdu.dk>, Website: <http://www.sdu.dk/staff/poma> , <http://www.manoonpong.com> An application must include: * Application * Curriculum Vitae * Certificates/Diplomas (Master's degree certificate and the latest certificate) * Information on previous teaching experience, please attach as Teaching portfolio * List of publications indicating the publications attached * Examples of the most relevant publications. Please attach one pdf-file for each publication, a possible co-author statement must be a part of this pdf-file The University encourages all interested persons to apply, regardless of age, gender, religious affiliation or ethnic background. The full posting can be accessed at <https://ssl1.peoplexs.com/Peoplexs22/CandidatesPortalNoLogin/Vacancy.cfm?Po…> Please apply online at: <https://ssl1.peoplexs.com/Peoplexs22/CandidatesPortalNoLogin/ApplicationFor…>

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computational neuroscience positions at Sandia National Laboratories
by Chance, Frances S. Nov. 5, 2014

Nov. 5, 2014

Colleagues, We are seeking computational neuroscientists to join our interdisciplinary research program in understanding cognitive function at the neural circuit level. Example research topics of interest include understanding neural circuit function, neural basis of perception, decision-making, learning and memory, and the development and validation of large-scale high-fidelity neural simulations. Multiple positions for varying levels of experience are available. To apply, visit http://www.sandia.gov/careers/ and click "View All Jobs". Type the indicated Job ID into the Keywords box to find the appropriate posting. For questions please contact Frances Chance (fschanc(a)sandia.gov<mailto:fschanc@sandia.gov>), Brad Aimone (jbaimon(a)sandia.gov<mailto:jbaimon@sandia.gov>), or Glory Emmanuel (gremman(a)sandia.gov<mailto:gremman@sandia.gov>). Applications received by December 19, 2014 will receive full consideration. -- Technical Staff (Job ID 647552): The successful applicant for our technical staff position should have a strong background in neuroscience (as evidenced by a Ph. D. in neuroscience, cognitive science, machine learning, or a related field), and experience with current neuroscience research methods and data analysis. The successful applicant will be expected to contribute to ongoing projects as well as to develop new lines of research and pursue new funding opportunities. Experience should be commensurate with a beginning assistant professor or higher. Postdoctoral Position in Computational Neuroscience (Job ID 647564): An advanced degree (Ph. D. or equivalent) in computational neuroscience or a related area is required for this position, as is a strong record of academic performance and publications. Other required qualifications include competence in C, C++, Matlab, Python, or a related programming language, and excellent written- and oral-communication skills. Postdoctoral Position in Machine Learning/Computer Science (Job ID 647563): An advanced degree (Ph. D. or equivalent) in mathematics or computer science or related area is required for this position; with a preference for those with experience in examining neural computation or developing machine learning approaches based on neural inspiration. Those with focus on mathematics research areas pertinent to neural systems, such as studies of large dynamical systems, high-dimensional statistics, and dimensionality reduction, are particularly encouraged to apply. A strong record of academic performance and publications is required. Other required qualifications include competence in C, C++, Matlab, Python, or a related programming language, and excellent written- and oral-communication skills.

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Last Mile: ADAPTIVE 2015 || March 22 - 27, 2015 - Nice, France
by Cristina Pascual Nov. 4, 2014

Nov. 4, 2014

INVITATION: ================= Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and publish original scientific results to ADAPTIVE 2015. The submission deadline is November 18, 2014. Authors of selected papers will be invited to submit extended article versions to one of the IARIA Journals: http://www.iariajournals.org ================= ============== ADAPTIVE 2015 | Call for Papers =============== CALL FOR PAPERS, TUTORIALS, PANELS ADAPTIVE 2015, The Seventh International Conference on Adaptive and Self-Adaptive Systems and Applications March 22 - 27, 2015 - Nice, France General page: http://www.iaria.org/conferences2015/ADAPTIVE15.html Call for Papers: http://www.iaria.org/conferences2015/CfPADAPTIVE15.html Submission page: http://www.iaria.org/conferences2015/SubmitADAPTIVE15.html Contributions: - regular papers [in the proceedings, digital library] - short papers (work in progress) [in the proceedings, digital library] - ideas: two pages [in the proceedings, digital library] - extended abstracts: two pages [in the proceedings, digital library] - posters: two pages [in the proceedings, digital library] - posters: slide only [slide-deck posted at www.iaria.org] - presentations: slide only [slide-deck posted at www.iaria.org] - demos: two pages [posted at www.iaria.org] - doctoral forum submissions: [in the proceedings, digital library] Proposals for: - mini-symposia: see http://www.iaria.org/symposium.html - workshops: see http://www.iaria.org/workshop.html - tutorials: [slide-deck posted on www.iaria.org] - panels: [slide-deck posted on www.iaria.org] Submission deadline: November 18, 2014 Sponsored by IARIA, www.iaria.org Extended versions of selected papers will be published in IARIA Journals: http://www.iariajournals.org Print proceedings will be available via Curran Associates, Inc.: http://www.proceedings.com/9769.html Articles will be archived in the free access ThinkMind Digital Library: http://www.thinkmind.org The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas. All tracks are open to both research and industry contributions, in terms of Regular papers, Posters, Work in progress, Technical/marketing/business presentations, Demos, Tutorials, and Panels. Before submission, please check and comply with the editorial rules: http://www.iaria.org/editorialrules.html ADAPTIVE 2015 Topics (topics and submission details: see CfP on the site) Fundamentals and design of adaptive systems Fundamentals on adaptive and self-adapting systems; Frameworks and architectures for adaptive supporting platforms; Architectures for adaptive applications; Specification of adaptive behavior; Specification of adaptive structures and topologies; Design and implementation of adaptive components; Composition of adaptive behaviors and structures; Adaptive individual and collective behavior and structures; Adaptive deterministic and non-deterministic behavior; Semantic modeling Adaptive entities Adaptive environments; Adaptive hardware configurations; Adaptive software applications; Adaptive protocols; Adaptive algorithms; Adaptive and interactive interfaces; Adaptive filters; Adaptive clock speeds; Adaptive schedulers; Adaptive load balancers Adaptive mechanisms Adaptive real-time strategies; Learning-based adaptive strategies; Adaptive mechanisms (trees, ant algorithms, fuzzy-logic, etc. ); Agent based-adaptive mechanisms; Policy- based adaptation; Feedback-based adaptive systems; Context-aware adaptation; User-aware adaptation Adaptive applications Adaptive artificial intelligence in computer wargames; Intelligent complex adaptive systems; Adaptive virtualization; Adaptive social networks; Adaptive entertainment applications; Adaptive disaster recovery systems; Anticipative adaptive systems; Fault-tolerant adaptive systems; Adaptive ad hoc networks; Application domains, e,g., building (AEC projects, simulation models, facility management), tourism, etc.; Adaptive economic applications (finance, stock exchange, regulatory decisions, etc.); Adaptive vehicular traffic Adaptivity in robot systems Adaptive robot behavior; self-organization and emergence; flexible and reconfigurable robot structures; adaptation in collective and swarm robotics Self-adaptation Theory of self-adaptation and control; Self-adaptive networks, systems, and applications; Self-adaptive services; Self-adaptive behavior and topology/structure; Specification of self-adaptive behavioral control Self-adaptation applications Self-monitoring and self-management; Self-configuration, self-healing, self-management; Self-defense, self-protection, self-diagnosis; Self-adaptation of overlay networks; Self-adaptation in ad hoc sensor networks; Context-aware self-adaptation of networks and services Computational Trust for Self-Adaptive Systems Trust models for adaptive systems; Trust models for self-organizing and autonomics systems; Agent-based trust models for cooperation; Privacy and Security in self-organizing and adaptive systems; Human and social factors involved in trust and adaptation; Applications of trust and security on adaptive systems, with a focus on web-based applications, social networks, social search; Trust models for self-organizing systems of information (wikis, forums, blogs.); Trust and personalisation for enabling adaptation; Models for learning trust and the evolution of trust; Decentralised trust models; Case studies; Theoretical trust models for self-adaptation Metrics for adaptive and self-adaptive systems Stability and convergence; Optimal (self-) adaptation; Accuracy validation of (self-) adaptation; Real-time (self-) adaptive performance Committee: http://www.iaria.org/conferences2015/ComADAPTIVE15.html ================================================

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CFP: Special Issue on Neurobiologically Inspired Robotics: Enhanced Autonomy Through Neuromorphic Cognition
by Jeff Krichmar Nov. 4, 2014

Nov. 4, 2014

Dear Comp-Neuro, I hope some of you will consider submitting to this special issue of Neural Networks. Neurobiologically inspired robotics goes by many names: brain-based devices, cognitive robots, neurorobots, and neuromorphic robots, to name a few. The field has grown into an exciting area of research and engineering. The common goal is twofold: Firstly, developing a system that demonstrates some level of cognitive ability can lead to a better understanding of the neural machinery that realizes cognitive function. The often used phrase, “understanding through building”, implies that one can get a deep understanding of a system by constructing physical artifacts that can operate in the real-world. In building and studying neurobiologically inspired robots, scientists must address theories of neuroscience that couple brain, body, and behavior. Secondly, the deep theoretical understanding of cognition, neurobiology and behavior obtained by constructing physical systems, could lead to a system that demonstrates capabilities commonly found in the animal kingdom, but rarely found in artificial systems, most notably their adaptive and flexible autonomous behavior. There have already been some successes that meet these goals. For example, navigation models based on the hippocampus are now deployed on robots that autonomously explore their environment. Machine image processing systems based on visual cortex have been used in a number of unsupervised recognition and perception applications. Robots designed to address impairments due to disorders such as Alzheimer’s disease, autism spectrum disorder, and attentional deficit disorders, are being used as therapeutic and diagnostic tools without the need for constant caretaker supervision. Despite these successes, the field is still in its infancy and basic research is needed. In particular, we are interested in papers that describe: 1) How models of cognitive functions, such as attention, decision-making, learning and memory, perception, and social cognition can be constructed on physical robots. 2) How the neuromorphic devices, which are designed to run neural algorithms with low-power, can advance the construction of autonomous robotics. 3) How the theoretical and engineering lessons learned from constructing neurobiologically inspired robots can transfer to autonomous robots carrying out practical applications. This Special Issue invites papers that address the three broad topics described above. Topics of interest • Adaptive behavior • Active sensing • Artificial empathy • Cortical computing • Developmental robotics • Embodied Cognition • Neuromorphic Engineering • On-line learning and memory systems • Prediction and planning • Socially assistive robotics Guest Editors Jeffrey Krichmar, University of California, Irvine Minoru Asada, Osaka University Jorg Conradt, Technische Universitat München Important Dates Submission due: 1 Feb 2015 Acceptance notification: 1 Aug 2015 Expected publication: 1 Nov 2015 Submission instructions Each paper for submission should be formatted according to the style and length limit of Neural Networks. Please refer complete Author Guidelines at http://www.elsevier.com/journals/neural-networks/0893-6080/guide-for-authors. Note that published papers and those currently under review by other journals or conferences are prohibited. A separate cover letter should be submitted that includes the paper title, the list of all authors and their affiliations, and information of the contact author. Each paper will be reviewed rigorously, and possibly in two rounds, i.e., minor/major revisions will undergo another round of review. Prospective authors are invited to submit their papers directly via the online submission system at http://ees.elsevier.com/neunet/. To ensure that all manuscripts are correctly included into the special issue described, it is important that all authors select “SI: Neurobiological Robotics” when they reach the "Article Type" step in the submission process. Jeff Krichmar Department of Cognitive Sciences 2328 Social & Behavioral Sciences Gateway University of California, Irvine Irvine, CA 92697-5100 jkrichma(a)uci.edu http://www.socsci.uci.edu/~jkrichma

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**Abstract submission deadline THIS FRIDAY 11/07** MURI Winter School Jan. 2015
by Santamaria, Cookie Nov. 4, 2014

Nov. 4, 2014

UCSD and the University of Chicago present: MURI WINTER SCHOOL 2015<http://biocircuits.ucsd.edu/special/winterschool2015> Dynamics of Multifunction Brain Networks Organizers: Henry Abarbanel (UCSD), Timothy Gentner (UCSD), and Daniel Margoliash (Univ. of Chicago) 15th Floor, Building 1, Village West<http://maps.ucsd.edu/mapping/viewer/default.htm?mkey=1&lc=open&km=open&rc=c…>, UC San Diego January 7-9, 2015 Registration deadline: Friday, December 5, 2014 Abstract submission deadline: Friday, November 7, 2014 Lecturers: Tim Gardner<http://people.bu.edu/timothyg/Home.html> (Boston University) – “High density neural recordings in singing birds: methods and observations” Michael Long<http://longlab.med.nyu.edu/> (New York University) – “How does the brain generate behavioral sequences?” Gabriel Mindlin<http://www.lsd.df.uba.ar/> (University of Buenos Aires) – “The biomechanics of birdsong production” and “Low dimensional dynamics systems behind birdsong production” Richard Mooney<http://www.mooneylab.com/> (Duke University) – “Neurobiology of vocal learning” and “Forward mechanisms for hearing and learning” Marc Schmidt<http://www.bio.upenn.edu/people/marc-schmidt> (University of Pennsylvania) – “Brainstem and forebrain contributions to the generation of learned motor” Ofer Tchernichovski<http://ofer.sci.ccny.cuny.edu/> (Hunter College) – “Vocal learning beyond imitation: from cultural evolution to brain dopamine” and “How a song is learned: mechanisms of template matching” ________________________________________________________________________________ This is the third annual Winter School sponsored by the U.S. Office of Naval Research as part of its UCSD/Chicago MURI program in Dynamics of Multifunction Brain Networks. This year’s School presents a series of pedagogical and research oriented talks on the use of birdsong as a model system where theory and experiment can meet productively. It includes a series of pedagogical presentations and a poster session. The School is intended for all researchers, including advanced graduate students, interested in the general area of understanding functional nervous systems. Active participation during the School's lectures is strongly encouraged. All attendees are invited to submit abstracts for poster presentations. Selected contributed posters will be highlighted in an oral session. Registration is required for attendance, but there is no fee for attending. A limited number of travel awards are available for exceptionally qualified graduate students and postdocs, who should apply and have their supervisor send a letter of reference, via email, to muri.winter.school(a)gmail.com<mailto:muri.winter.school@gmail.com>. Please visit us online to register and for details regarding the schedule and poster abstract submission: http://biocircuits.ucsd.edu/special/winterschool2015

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PhD student position in theoretical/ computational neuroscience available in Mannheim, Germany
by Seeger, Simone Nov. 4, 2014

Nov. 4, 2014

A PhD student position in theoretical/ computational neuroscience (German payscale 0.67x E13 TV-L) is available for 3 years initially, starting January 2015 or later, at the Dept. of Theoretical Neuroscience (Head: Prof. Daniel Durstewitz), Bernstein Center for Computational Neuroscience Heidelberg-Mannheim, Central Institute of Mental Health Mannheim, Heidelberg University. The lab focuses on highly data-driven computational models of prefrontal cortical and hippocampal network dynamics underlying higher cognitive function in health and psychiatric disease. Our approach is to estimate (in statistically principled ways) single cell and network models from slice and in-vivo electrophysiological recordings generated in the lab, and then apply these for understanding network function and dysfunction in experimental data (multiple single-unit, behavior) in psychiatrically relevant genetic animal models. Applicants should have a strong mathematical background (dynamical systems and/or statistics / stochastic processes), good programming skills (Matlab, C++), and a keen interest in biological and neural systems. Please send informal inquiries and application documents (cover letter including a brief description of research interests, CV and contact details of two personal references) to Dr. loreen.hertaeg(a)zi-mannheim.de<mailto:loreen.hertaeg@zi-mannheim.de>. *** Simone Seeger, M.A. Administration Bernstein Center for Computational Neuroscience Zentralinstitut für Seelische Gesundheit Postfach 12 21 20, 68072 Mannheim J5, 68159 Mannheim Telefon: 0621/1703-1326 oder 06221/54-8310 Fax: 0621/1703-2915 E-Mail: Simone.Seeger(a)zi-mannheim.de<mailto:Simone.Seeger@zi-mannheim.de> Internet: http://www.bccn-heidelberg-mannheim.de<http://www.bccn-heidelberg-mannheim.de/>

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CfP : TWELFTH INTERNATIONAL CONFERENCE ON MULTIPLE CLASSIFIER SYSTEMS
by Dr. Schwenker Nov. 3, 2014

Nov. 3, 2014

---- PLEASE, APOLOGIZE MULTIPLE COPIES ---- ****************************************** ** MCS 2015 Preliminary Call for Papers ** ****************************************** *****Paper Submission: JANUARY 30, 2015***** ********************************************************************** TWELFTH INTERNATIONAL CONFERENCE ON MULTIPLE CLASSIFIER SYSTEMS Reisensburg Castle (Günzburg, Germany), Ulm University, June 29 - July 1, 2015 http://mcs.diee.unica.it ********************************************************************** MCS 2015 is the twelfth edition of the well-established series of meetings providing the leading international forum for the discussion of issues in multiple classifier systems and ensemble methods. The aim of the workshop is to bring together researchers from diverse communities concerned with this topic, including pattern recognition, machine learning, neural networks, data mining and statistics. MCS 2015 will be held on June 29 - July 1, 2015, at Reisensburg Castle (Günzburg, Germany) research center of the Ulm University. Updated information:http://mcs.diee.unica.it Best regards, MCS 2015 Co-Chairs Friedhelm Schwenker Joseph Kittler Fabio Roli

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PhD in “Fragmented neural processing in Parkinson's disease” at University of Manchester, Faculty of Life Sciences
by Mark Humphries Nov. 3, 2014

Nov. 3, 2014

PhD in “Fragmented neural processing in Parkinson's disease”. Applications are invited for this fully-funded PhD position (fees and salary) in the lab of Dr Mark Humphries in the Faculty of Life Science, University of Manchester Deadline: 12th December 2014 Start date: September 2015 Duration: 3 or 4 years, depending on qualifications Eligibility: Candidates must be nationals of the UK or other EU country This project will pursue the hypothesis that chronic loss of dopamine causes the fragmentation of striatal processing of cortical input. The striatum supports neural populations coding for different actions, forming the basis for action selection. Animal model data has suggested that chronic dopamine loss causes the fragmentation of these populations, mixing together previously well-defined populations (Cho et al 2002 J Comp Neurol). To test this hypothesis, the candidate will develop our existing large-scale model of the striatal network (Humphries et al, 2010, PLoS Comput Biol) and combine it with a newly-developed model of dopamine-dependent plasticity at cortical synapses onto striatal neurons (Gurney et al, PLoS Biol, in press). The project will then test aspects of the hypothesis: Does fragmentation occur via changes to network excitability or to plastic change to network inputs? Does fragmentation cause the breakdown of action selection and therefore the observed motor symptoms? And why is 80% loss of dopamine necessary for this to occur? For more details of the project please visit: http://www.ls.manchester.ac.uk/phdprogrammes/projectsavailable/project/?id=… For details of the application and interview process see: http://www.mhs.manchester.ac.uk/postgraduate/mhs-graduate-school/mrcdtp/stu… Informal enquiries: mark.humphries(a)manchester.ac.uk<mailto:mark.humphries@manchester.ac.uk> Dr Mark Humphries MRC Senior non-Clinical Research Fellow AV Hill Building Faculty of Life Sciences University of Manchester http://www.systemsneurophysiologylab.ls.manchester.ac.uk/

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Assistant or Associate Professor, Data Analytics
by Guerra, Erick J. Nov. 1, 2014

Nov. 1, 2014

Assistant or Associate Professor, Health or Biomedical Data Analytics Rowan University is a comprehensive state-designated research institution with approximately 15,000 students. Its main campus is located in Glassboro, N.J., 20-miles southeast of Philadelphia, and it has a branch campus and medical school in Camden and a second medical school in nearby Stratford. Rowan is the second university in the country to offer M.D. and D.O. medical-degree granting programs. The School of Osteopathic Medicine has a faculty practice plan that serves approximately 200,000 patients in Southern New Jersey. The institution is also home to the South Jersey Technology Park, which fosters the translation of applied research into commercial products and processes. Its business incubator also supports that mission. The University boasts seven colleges–Rohrer College of Business and colleges of Communication and Creative Arts, Education, Engineering, Humanities and Social Sciences, Performing Arts, and Science and Mathematics. The Department of Biomedical & Translational Sciences in the School of Biomedical Science & Health Professions invites applications for a tenure-track Associate or Assistant Professor position in the field of Health or Biomedical Data Analytics starting September 1, 2015. A Ph.D. in Data Analytics or related field is required. The successful candidate will assume a leadership role in the newly established Data Analytics programand is expected to develop an externally-funded research program in Health or Biomedical Data Analytics that involves undergraduate and/or graduate (MS) students. Applications are encouraged from candidates with a successful record of research in one of the following areas: medical informatics, genomic or proteomic data mining, systems biology, translational bioinformatics. Candidates with a background in industry settings are also encouraged to apply. The Department of Biomedical & Translational Sciences is the home for new interdisciplinary biomedical initiatives and welcomes its first cohort of students pursuing a BS in Translational Biomedical Sciences in Fall 2014. Many faculty-members in the Department of Biomedical & Translational Sciences have joint appointments with the College of Science and Mathematics, and there are opportunities to collaborate with both the allopathic and osteopathic medical schools at Rowan University. The College of Science & Mathematics currently offers related BS degrees in Biological Sciences, Biochemistry, Biophysics, and Bioinformatics, in addition to MS degrees in Pharmaceutical Science and Bioinformatics. The Master of Science in Data Analytics with a specialization in Health Data Analytics is housed in the College of Science & Mathematics with stakeholders spanning several colleges and schools at Rowan University. The successful candidate will develop and implement new interdisciplinary curricula in both Data Analytics and Translational Biomedical Sciences. Teaching responsibilities will include courses in Translational Biomedical Sciences, graduate courses in Data Analytics, and potentially other discipline specific courses falling under these programs. The application must be submitted through our online application system (http://rowanuniversity.hodesiq.com/jobs/assistant-associate-professor-healt…) as a single file (PDF format) containing a curriculum vitae, a detailed description of research interests and plans, a statement of teaching philosophy, and graduate transcripts (copies acceptable). Three letters of recommendation should be sent via email directly to Ms. Shelly Klink (klink(a)rowan.edu<mailto:klink@rowan.edu>). The application deadline is November 15, 2014. Rowan University values diversity and is committed to equal opportunity in employment. Candidates must demonstrate authorization to work in the United States. All positions are contingent upon budget appropriations.

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

Nov. 1, 2014

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

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Postdoctoral Position in Neuroscience (BRAIN Initiative project): In vivo imaging of cortical dynamics
by Patrick Kanold Oct. 31, 2014

Oct. 31, 2014

Dear all, A postdoctoral position utilizing in vivo 2-photon imaging is available in the laboratory of Dr. Patrick Kanold at the University of Maryland. The laboratory studies the function, development, and plasticity of the cerebral cortex (http://www.kanold.org) We are seeking highly motivated individuals that want to join exciting collaborative project, together with Dr. Dietmar Plenz (NIMH, http://www.nimh.nih.gov/labs-at-nimh/principal-investigators/dietmar-plenz.…) and Dr. Wolfgang Losert (UMd Physics), funded by the NIH BRAIN initiative. We use in vivo 2-photon imaging and stimulation technology that allows rapid imaging and stimulation in multiple focal planes and aim to develop new analysis techniques based on dynamic systems and graph theoretic measures to extract network dynamics at the single neuron and population level. We aim to identify the influence of single neurons relative to the synergistic influence of specific groups of neurons (the crowd) on network dynamics and ultimately behavior of the animal (see http://www.clfs.umd.edu/biology/kanold/Research.html) The ideal candidate will have a PhD in neuroscience, engineering, or related discipline, a background in systems neuroscience, and an ability to work in a large multidisciplinary team. Special considerations are given to applicants with training in imaging, in vivo physiology, computational approaches, and programming skills (esp. MATLAB). Qualified individuals should send a copy of curriculum vitae and names of three references to pkanold(a)umd.edu.

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