- Comp-neuro - lists.cnsorg.org

faculty positions at Penn State

by Vladimir Itskov

---------- Forwarded message ---------- Date: Wed, 9 Dec 2015 14:57:49 -0500 From: "Adam Smith (CSE)" <asmith(a)cse.psu.edu> Subject: data science/ML and cognitive science faculty positions at Penn State -- talk to us at NIPS! Penn State will be hiring multiple faculty in "data science" and "brain science", broadly defined. There are open positions in the department of Computer Science & Engineering as well as Statistics, and positions have the potential to be joint with other departments at Penn State. The ad for the CSE department follows. I will be at NIPS on Thursday (11am poster session) and Friday (at the workshop on adaptive data analysis). Send me an email if you'd like to talk! Adam Smith -- Penn State Computer Science & Engineering http://www.cse.psu.edu/~asmith Links: https://psu.jobs/job/60027 http://eecs.psu.edu/departments/EECS-Departments-Employment-Opportunities.a… http://cra.org/job/pennsylvania-state-university-faculty-position-vacancies/ =========================== Applications are invited for several tenure-track faculty positions at all ranks. Outstanding candidates in all areas of Computer Science and Engineering will be considered. Areas of particular interest are: hardware systems, computer architecture/embedded systems, software systems, brain science, data science, and security with applications to networking, systems and data analytics. Faculty lines in the areas of architecture/embedded systems, data science, and networking will be hired jointly with the Department of Electrical Engineering in the School of Electrical Engineering and Computer Science. Hiring in the brain science (especially around the analyses of imaging data) and the security of large-scale cyberphysical systems (including smart grids and food-water-energy systems), will be jointly hired with the Institute for CyberScience. These positions are part of a university-wide initiative to appoint exceptional candidates who can advance algorithms, software and hardware systems with a demonstrated commitment to participating in interdisciplinary research (see www.ics.psu.edu/hire.html) The department has 30 tenure-track faculty in the major areas of computer science and engineering. Fourteen members of our faculty are NSF Career Award recipients. Three faculty members from the department have received the prestigious NSF PECASE Award. In recent years, faculty in the department were awarded several large-scale research grants, including the Collaborative Research Alliance for the Science of Security, a Collaborative Technology Alliance for Network Science and an NSF Expeditions in Computing award. Further, the faculty have received awards in computing and research infrastructure and instrumentation grants from NSF, and are part of DARPA/STARNET Center, an NSF ERC and NSF IGERT team. The faculty are highly successful in obtaining funding from NSF, DARPA, ARL, DOE, DTRA, AFOSR and AOR. There are state-of-the-art research labs for computer systems, computer vision and robotics, microsystems design and VLSI, networking and security, high performance computing, bioinformatics and virtual environments. The department offers a graduate program with 30 Masters students and 132 Ph.D. students, and undergraduate programs in computer science and computer engineering. The university is committed to growing the faculty ranks and promoting interdisciplinary research toward cyber-enabled discovery and design. Penn State is a major research university and is ranked 3rd in the nation in industry-sponsored research and 8th in the nation in research expenditures. U.S. News and World Report consistently ranks Penn State?s College of Engineering undergraduate and graduate programs among the top in nation. Penn State is ranked 5th world wide in Computer Science Citations according to Thomson-Reuters. The university is located in the beautiful college town of State College in the center of Pennsylvania. The State College area has 130,000 inhabitants and offers a wide variety of cultural and outdoor recreational activities. The university offers outstanding events from collegiate sporting events to fine arts productions. Many major population centers on the east coast (New York, Philadelphia, Pittsburgh, Washington D.C., Baltimore) are only a few hours drive away and convenient air services to several major hubs are operated by three major airlines out of State College. Applicants should hold a Ph.D. in computer science, computer engineering, or a closely related field and should be committed to excellence in both research and teaching. Support will be provided to the successful applicants for establishing their research programs. We strongly encourage dual career couples and candidates from underrepresented groups to apply. Applicants should submit a statement of professional interests, curriculum vitae, and the names and addresses of four references. Please submit these items in a single PDF file electronically at http://apptrkr.com/681413. Nominations and applications will be considered until the positions are filled. If you have questions regarding the application process, please email recruiting(a)cse.psu.edu. Penn State is an equal opportunity, affirmative action employer, and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

Dec. 12, 2015

MICCAI 2016 - Call for Papers and Workshop/Tutorial/Challenge Proposals

by Devrim Unay

[Apologies for cross posting] We are writing to invite you to participate in *MICCAI 2016*, the 19th International Conference on Medical Image Computing and Computer Assisted Intervention, which will be held from *October 17th to 21st, 2016 in Istanbul, Turkey*. Call for papers can be found here: http://miccai2016.org/en/CALL-FOR-PAPERS.html. The paper submission deadline is *March 10, 2016*. Call for workshop/tutorial/challenge proposals can be found here: http://miccai2016.org/en/SATELLITE-EVENTS.html. The proposal submission deadline is *January 19, 2016*. For the latest information, please refer to our website: http://miccai2016.org. Also, please follow us on Facebook <https://www.facebook.com/groups/1050034681703084/> and Twitter <https://twitter.com/MICCAI2016>. We look forward to welcoming you to Istanbul in October 2016! On Behalf of the MICCAI 2016 Organizing Committee Sebastien Ourselin General Chair

Dec. 12, 2015

1st call for papers: PRNI 2016

by Jo Etzel

******* please accept our apologies for cross-posting ******* ------------------------------------------------------------------------------ FIRST CALL FOR PAPERS PRNI 2016 6th International Workshop on Pattern Recognition in Neuroimaging 22-24 June 2016 Fondazione Bruno Kessler (FBK), Trento, Italy www.prni.org - @PRNI2016 - www.facebook.com/PRNI2016/ ------------------------------------------------------------------------------ Paper submission deadline: 18 March 2016, 11:59 pm PST Acceptance notification: 22 April 2016 Camera-ready paper deadline: 7 May 2016 Oral and poster sessions: 22-24 June 2016 Pattern recognition techniques have become an important tool for neuroimaging data analysis. These techniques are helping to elucidate normal and abnormal brain function, cognition and perception, anatomical and functional brain architecture, biomarkers for diagnosis and personalized medicine, and as a scientific tool to decipher neural mechanisms underlying human cognition. The International Workshop on Pattern Recognition in Neuroimaging (PRNI) aims to: (1) foster dialogue between developers and users of cutting-edge analysis techniques in order to find matches between analysis techniques and neuroscientific questions; (2) showcase recent methodological advances in pattern recognition algorithms for neuroimaging analysis; and (3) identify challenging neuroscientific questions in need of new analysis approaches. PRNI welcomes submissions on topics including, but not limited to: * Learning from neuroimaging data - Algorithms for brain-state decoding or encoding - Optimization and regularization - Bayesian analysis of neuroimaging data - Causal inference and time delay techniques - Network and connectivity models (the connectome) - Dynamic and time-varying models - Dynamical systems and simulations - Empirical mode decomposition, multiscale decompositions - Combination of different data modalities - Efficient algorithms for large-scale data analysis * Interpretability of models and results - High-dimensional data visualization - Multivariate and multiple hypothesis testing - Summarization and presentation of inference results * Applications - Disease diagnosis and prognosis - Real-time decoding of brain states - Analysis of resting-state and task-based data - MEG, EEG, structural MRI, fMRI, diffusion MRI, ECoG, NIRS Authors should prepare full papers with a maximum length of 4 pages (two column IEEE style) for double-blind review. The manuscript submission deadline is 18 March 2016. Accepted manuscripts will be assigned either to an oral or poster sessions; all accepted manuscripts will be included in the workshop proceedings. -- Joset A. Etzel, Ph.D. Research Analyst Cognitive Control & Psychopathology Lab Washington University in St. Louis http://mvpa.blogspot.com/

Dec. 11, 2015

Postdoc in mathematical neuroscience at the University of Houston/UC, Boulder

by Kresimir Josic

We are looking for a postdoctoral associate with a background in applied mathematics and/or computational neuroscience. The successful applicant will work with Krešimir Josić at the University of Houston and Zack Kilpatrick at the University of Colorado at Boulder. The goal of the project is to use linear response theory and its extensions to predict how patterns of activity and structure of neuronal networks co-evolve. This is a collaborative project with Brent Doiron (Pitt) and Eric Shea-Brown (UW, Seattle). The deadline for applications is January 15, 2016. This position is expected to run September 1, 2016 through August 31, 2018. Interested applicants can apply online at at the University of Houston jobs website: https://jobs.uh.edu/postings/28856 <https://jobs.uh.edu/postings/28856> Please contact Krešimir Josić (josic(a)math.uh.edu <mailto:josic@math.uh.edu>) or Zack Kilpatrick (zpkilpat(a)math.uh.edu <mailto:zpkilpat@math.uh.edu>) if you have any questions. The University of Houston is an Equal Opportunity/Affirmative Action institution. Minorities, women, veterans and persons with disabilities are encouraged to apply. Additionally, the University prohibits discrimination in employment on the basis of sexual orientation, gender identity or gender expression. -- ** Krešimir Josić ** Department of Mathematics ** University of Houston ** http://math.uh.edu/~josic ** Tel: (713) 743-3485

Dec. 11, 2015

PhD at Edinburgh on data analysis

by Matthias Hennig

A funded PhD position is available at the University of Edinburgh to develop and implement efficient paralellised methods for analysis of large scale, high density multielectrode array recordings. The project will focus on analysis of primary raw data from a 4,096 channel array, and aims at improving spike detection and sorting, and statistical analysis of multi-neuron activity. Data will come from the labs of Evelyne Sernagor (Newcastle, retina) and Luca Berdondini (IIT Genova, cultured networks). Applicants should have a strong quantitative background and interest in interdisciplinary research. Background in neuroscience and/or parallel programming is desirable, but not essential. This position is available to UK/EU applicants, and eligible for funding by the EPSRC CDT in Pervasive Parallelism. Interested individuals should send a c.v., statement of interest and the names of three references to Matthias Hennig (h.hennig(a)ed.ac.uk) Apply by 1 February 2016. PPar http://pervasiveparallelism.inf.ed.ac.uk/ J.-O. Muthmann, H. Amin, E. Sernagor, A. Maccione, D. Panas, L. Berdondini, U.S. Bhalla, M.H. Hennig (2015). Spike detection for large neural populations using high density multielectrode arrays. Front Neuroinform, 9:28. http://journal.frontiersin.org/article/10.3389/fninf.2015.00028/abstract D. Panas, H. Amin, A. Maccione, O. Muthmann, M. van Rossum, L. Berdondini, M.H. Hennig (2015). Sloppiness in spontaneously active neuronal networks. J Neurosci, 35(22): 8480-8492. http://www.jneurosci.org/content/35/22/8480.full -- Matthias H Hennig http://homepages.inf.ed.ac.uk/mhennig/ -- Matthias H Hennig http://homepages.inf.ed.ac.uk/mhennig/ The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

Dec. 10, 2015

PhD student position in Computational Vision - Video Analysis at KTH in Stockholm

by Tony Lindeberg

PhD student position in Computational Vision - Video Analysis at KTH in Stockholm Job description The position is in the area of Computational Vision — the science of understanding the computational mechanisms underlying visual perception and of equipping computers with visual perceptual abilities to make them see. The goal of this specific project is to develop new approaches for computing image features in terms of receptive fields for analyzing spatio-temporal image data (video or real-time image streams) in a theoretically well-founded manner for purposes in computer vision and computational modelling of biological vision. The main focus is specifically on developing computational vision methods for video analysis that are based on image operations in terms of time-causal and time-recursive spatio-temporal receptive fields, which only make use of information from the present moment and a compact buffer of what has occurred in the past, for which we have recently developed a novel theoretical scale-space framework at KTH. The main work to be done concerns: (i) extending this framework to different types of spatio-temporal feature detection tasks, (ii) integrating the framework into higher-order visual tasks and (iii) evaluating the performance on benchmark problems as a guide to further developments. There are possibilities of working theoretically (mathematically), algorithmically and experimentally in close collaboration with the supervisor. An overview of the research environment can be found at https://www.kth.se/profile/76171/page/computational-vision-at-csc-kth. Qualifications The candidate should have a strong computationally oriented background. The preference is for a candidate with a Master's degree in Engineering Physics or Computer Science with focus towards applied mathematics, computer science and numerical computations or a MSc/MEng education leading to similar skills. Good knowledge about computer vision and machine learning is a strong merit. The candidate should have good analytical abilities to work individually on problem solving and in good collaboration with the supervisor, specifically of working systematically and with good communication skills being able to present the results in writing and at scientific meetings. Good programming skills are necessary with the ability of working both with algorithm development in Matlab and if necessary complementing by more efficient implementations in C or C++. Applicants must be strongly motivated for doctoral studies, possess the ability to work independently and perform critical analysis and also possess good levels of cooperative and communicative abilities. Department information The position belongs to the Computational Brain Science group in the recently merged departments of Computational Biology and High Performance Computing and Visualization at the School of Computer Science and Communication. For more information visit https://www.kth.se/en/csc/forskning/cb. Additional information For further information and details about how to apply, please see https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:82576/ The deadline for applications is on January 17, 2016. [cid:FD2B374F-C472-4895-ADA7-B3CD5419FD22@csc.kth.se] Tony Lindeberg Professor of Computer Science — Computational Vision KTH Royal Institute of Technology School of Computer Science and Communication Department of Computational Biology SE-100 44 Stockholm, Sweden Phone: +46 8 790 6205 http://www.csc.kth.se/~tony

Dec. 10, 2015

ACAN 2016 - Call for Applications

by Geoff Goodhill

Graduate students and postdoctoral fellows interested in using electrophysiological and optical techniques in their research are encouraged to apply for the Australian Course in Advanced Neuroscience (ACAN) 2016, which will be held from 10th to 30th of April 2016 at the Moreton Bay Research Station, North Stradbroke Island, Queensland, Australia. ACAN is an intensive three-week course that guides participants through the theory and practice of electrophysiological recording and optical imaging techniques using a unique balance of small group lectures and hands-on laboratory work. Lectures from leading faculty will outline in an informal atmosphere the theoretical basis of cellular and systems neuroscience, and the principles of electrophysiological and optical recording techniques. During the course each participant will become proficient in patch-clamp recording, both in vitro and in vivo, calcium imaging, optogenetics, and many other techniques through unbridled access to state-of-the-art equipment, guided by the faculty. The course is also a lot of fun, with many ACAN students developing close friendships and collaborations during and after the course. In 2016 ACAN faculty will include: Cliff Abraham Ehsan Arabzadeh George Augustine Brad Baker John Bekkers Yossi Buskila Vincent Daria Alan Finkel Andreas Frick Yukiko Goda Geoff Goodhill Brett Graham Maarten Kole Matthew Larkum Joe Lynch Peregrine Osborne Lucy Palmer Steve Petrou Chris Reid Mala Shah Stephen Williams Twelve students will be selected to attend ACAN 2016. The application deadline is Monday 11th Jan 2016. For full details about the course, including the program, please visit: http://acan.qbi.uq.edu.au <http://acan.qbi.uq.edu.au/> In order to apply for ACAN 2016, you must: be a currently-enrolled PhD student, a postdoctoral fellow, or junior faculty (preferably with no more than 5 years after completing your PhD). Preference will be given, but is not exclusive, to those who are full-time residents of Australia or NZ (but you do not need to be a citizen or permanent resident of those countries). In your application you should include: - a completed application form (obtained from http://acan.qbi.uq.edu.au <http://acan.qbi.uq.edu.au/>) - your CV. - a covering letter that clearly states how you will apply the skills taught at ACAN to your research. - a reference from your supervisor, including a confirmation that funds are available to allow you to attend the course. - The fee for ACAN 2016 is A$4500, which covers all meals, accommodation, laboratory supplies and teaching materials. Scholarships from the Neurological Foundation of New Zealand are available for NZ citizens/permanent residents. Please send applications to: Prof Stephen Williams Queensland Brain Institute Email: srw(a)uq.edu.au <mailto:srw@uq.edu.au> http://www.qbi.uq.edu.au/group-leader-williams <http://www.qbi.uq.edu.au/group-leader-williams>

Dec. 10, 2015

IWSP7/ME@MBC talks now online

by Levin Kuhlmann

A selection of the talks from "IWSP7: Epilepsy Mechanisms, Models, Prediction & Control" and the overlapping "Melbourne Epilepsy" (ME@MBC) meeting held at the University of Melbourne, Australia, during 3-7 August 2015 are now online on the IWSP7 YouTube Channel at the following link: https://www.youtube.com/channel/UCy_d33ZB6xL7Cx8-eN7Fwxg/playlists Re-live the action, or share it with your friends or colleagues. On behalf of the local organizing committee Levin Kuhlmann, PhD David B. Grayden, PhD Mark J. Cook, MD Anthony N. Burkitt, PhD Dean R. Freestone, PhD Tatiana Kameneva, PhD Alan Lai, PhD Elma O'Sullivan-Greene, PhD Andre Peterson, PhD Email: organizingcommittee(a)iwsp7.org<mailto:organizingcommittee@iwsp7.org>

Dec. 10, 2015

post-doc position at the center for sleep and consciousness in the integrated information theory (IIT) group (Prof. Giulio Tononi)

by Larissa Albantakis

*Post-doc position(s) at the Center for Sleep and Consciousness * Prof. Giulio Tononi, University of Wisconsin, Madison Several postdoctoral positions are available at the center for sleep and consciousness science in the laboratory of Prof. Giulio Tononi (University of Wisconsin, Madison, http://integratedinformationtheory.org/) to study information and causation within the framework of the integrated information theory. Immediate funding is available for a range of projects on foundational questions regarding information, causation, emergence, adaptation, evolution and complexity, especially in the context of neural networks. Candidates are expected to have strong training in an analytically rigorous discipline such as theoretical biology/neuroscience, physics, mathematics, computer science, or engineering. We explicitly encourage mathematicians to apply. Experience in information theory, complex systems, and an interest in the philosophy of causation are a plus. Programming experience is required (knowledge of MATLAB, Python, and/or C++ is of advantage). Appointments are renewable from year to year for up to 3 years, starting as soon as possible or until the positions are filled. Post-doc salaries correspond to the National Institutes of Health National Research Service Award (NRSA) stipend schedule for postdoc trainees, based on number of years of postdoctoral experience. Candidates should send a CV, brief statement of previous research and future research interests, and email addresses and phone numbers of three references to: Giulio Tononi, gtononi(a)wisc.edu. For more information contact Larissa Albantakis (albantakis(a)wisc.edu) or William Marshall (wmarshall3(a)wisc.edu) Albantakis L, Hintze A, Koch C, Adami C, Tononi G (2014) Evoluation of Integrated Causal Structures in Animats Exposed to Environments of Increasing Complexity. PLoS Comput Biol 10(12):e1003966 Oizumi M, Albantakis L, Tononi G (2014) From the Phenomenology to the Mechanisms of Consciousness: Integrated Information Theory 3.0. PLoS Comput Biol 10(5):e1003588 Hoel EP, Albantakis L, Tononi G (2013) Quantifying causal emergence shows that macro can beat micro. PNAS, 110(49), 19790–19795. Albantakis L, Tononi G (2015) The Intrinsic Cause-Effect Power of Discrete Dynamical Systems—From Elementary Cellular Automata to Adapting Animats. Entropy 17.8 (2015): 5472-5502. -- Larissa Albantakis, PhD Department of Psychiatry University of Wisconsin 6001 Research Park Blvd Madison, WI 53719

Dec. 9, 2015

Announcement: Groningen Spring School on Cognitive Modeling

by Jelmer Borst

Groningen Spring School on Cognitive Modeling – ACT-R, Nengo, PRIMs, & Accumulator Models – Date: April 4-8, 2016 Location: Groningen, the Netherlands Fee: € 200 (late fee €50 after January 31) Registration: www.ai.rug.nl/springschool <http://www.ai.rug.nl/springschool> The Groningen Spring School on Cognitive Modeling will cover four different modeling paradigms: ACT-R, Nengo, PRIMs, and Accumulator models. It thereby offers a unique opportunity to learn the relative strengths and weaknesses of these approaches. Each day will consist of four theory lectures, one on each paradigm. Each modeling paradigm also includes hands-on assignments. Although students are free to chose the number of lectures they attend, we recommend students to sign up for lectures on two of the modeling paradigms, and complete the tutorial units for one of the paradigms. At the end of each day there will be a plenary research talk, to show how these different approaches to modeling are applied. Admission is limited, so register soon! ACT-R Teachers: Jelmer Borst, Hedderik van Rijn, Niels Taatgen (University of Groningen) Website: http://act-r.psy.cmu.edu <http://act-r.psy.cmu.edu/>. ACT-R is a high-level cognitive theory and simulation system for developing cognitive models for tasks that vary from simple reaction time experiments to driving a car, learning algebra, and air traffic control. ACT-R can be used to develop process models of a task at a symbolic level. Participants will follow a compressed five-day version of the traditional summer school curriculum. We will also cover the connection between ACT-R and fMRI, and the timing extension to ACT-R. Nengo Teacher: Terry Stewart (University of Waterloo) Website: http://www.nengo.ca <http://www.nengo.ca/> Nengo is a toolkit for converting high-level cognitive theories into low-level spiking neuron implementations. In this way, aspects of model performance such as response accuracy and reaction times emerge as a consequence of neural parameters such as the neurotransmitter time constants. It has been used to model adaptive motor control, visual attention, serial list memory, reinforcement learning, Tower of Hanoi, and fluid intelligence. Participants will learn to construct these kinds of models, starting with generic tasks like representing values and positions, and ending with full production-like systems. There will also be special emphasis on extracting various forms of data out of a model, such that it can be compared to experimental data. PRIMs Teacher: Niels Taatgen (University of Groningen) Website: http://www.ai.rug.nl/~niels/actransfer.html <http://www.ai.rug.nl/~niels/actransfer.html> How do people handle and prioritize multiple tasks? How can we learn something in the context of one task, and partially benefit from it in another task? The goal of PRIMs is to cross the artificial boundary that most cognitive architectures have imposed on themselves by studying single tasks. It has mechanisms to model transfer of cognitive skills, and the competition between multiple goals. In the tutorial we will look at how PRIMs can model phenomena of cognitive transfer and cognitive training, and how multiple goals compete for priority in models of distraction. Accumulator Models Teacher: Marieke van Vugt (University of Groningen) Decisions can be described in terms of a process of evidence accumulation, modeled with a drift diffusion mechanism. The advantage of redescribing the behavioral data with an accumulator model is that those can be decomposed into more easily-interpretable cognitive mechanisms such as speed-accuracy trade-off or quality of attention. In this course, you will learn about the basic mechanisms of drift diffusion models and apply it to your own dataset (if you bring one). You will also see some applications of accumulator models in the context of neuroscience and individual differences.

Dec. 9, 2015