December 2018 - Comp-neuro - lists.cnsorg.org

Stanford University Postdoctoral Fellowship

by Christina Atkinson

Stanford University’s Department of Psychiatry & Behavioral Sciences is seeking to hire full time post-doctoral fellows for their Cognitive & Systems Neuroscience Laboratory. This lab is headed by Dr. Vinod Menon who has broad multidisciplinary expertise that spans several scientific disciplines and has published extensively on various aspects of human cognition and brain function. Explore our lab website for more information: http://med.stanford.edu/scsnl.html Please distribute job posting (below) appropriately in your department. We thank you for your support. POSTDOCTORAL FELLOWSHIP IN COMPUTATIONAL MODELING OF BRAIN NETWORKS Currently Available: The Stanford Cognitive and Systems Neuroscience Laboratory invites applications for a postdoctoral fellowship in computational modeling of human brain imaging data using deep neural networks. The successful candidate will be involved in a multidisciplinary project that seeks to develop novel computational frameworks for robust identification of neurobiological signatures of psychiatric and neurological disorders combining deep learning and convolution networks and dynamic brain circuit analyses with task and resting-state fMRI. Clinical disorders currently under investigation include autism, ADHD, anxiety and mood disorders, learning disabilities, schizophrenia, and Parkinson’s disease. We seek talented and highly-motivated individuals with a strong background in at least one of these areas: deep learning algorithms and optimization (theory and practical implementations); computational modeling, statistical inference, and machine learning, especially as applied to fMRI and MRI data. The candidate will have access to multiple large datasets and state-of-the-art computational resources, including HPCs and GPGPUs. Please email a CV, statement of research interests and relevant background, and have three letters of reference sent to Drs. Vinod Menon and Aarthi Padmanabhan at scsnl.stanford+postdoc(a)gmail.com<mailto:scsnl.stanford@gmail.com>

Dec. 12, 2018

EPFL Neuro Faculty Positions - deadline 14th December 2018

by Petersen Carl

Dear Colleague, The Ecole Polytechnique Federale de Lausanne (EPFL) has launched a new neuroscience initiative and as part of this initiative we are in the process of hiring three new professors in the field of neuroscience and engineering. The search is broad and we are interested in all aspects of neuroscience. We are hiring at the Assistant Tenure Track level, as well as the Associate Tenured level. https://professeurs.epfl.ch/page-158407-en.html NeuroSearch(a)epfl.ch If you are interested. then please apply for these faculty positions before 14th December 2018. Woman are particularly encouraged to apply. Thank you for your time and help. Best wishes, Carl. ------------------------------------------ Prof. Carl Petersen, Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Federale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland. email: carl.petersen(a)epfl.ch www: http://lsens.epfl.ch/

Dec. 11, 2018

CFP: TAC | Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data

by Pablo Barros

2nd CALL FOR PAPERS IEEE Transactions on Affective Computing Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data Website: https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/tacSpecialIssue201… I. Aim and Scope Research trends within artificial intelligence and cognitive sciences are still heavily based on computational models that attempt to imitate human perception in various behavior categorization tasks. However, most of the research in the field focuses on instantaneous categorization and interpretation of human affect, such as the inference of six basic emotions from face images, and/or affective dimensions (valence-arousal), stress and engagement from multi-modal (e.g., video, audio, and autonomic physiology) data. This diverges from the developmental aspect of emotional behavior perception and learning, where human behavior and expressions of affect evolve and change over time. Moreover, these changes are present not only in the temporal domain but also within different populations and more importantly, within each individual. This calls for a new perspective when designing computational models for analysis and interpretation of human affective behaviors: the computational models that can timely and efficiently adapt to different contexts and individuals over time, and also incorporate existing neurophysiological and psychological findings (prior knowledge). Thus, the long-term goal is to create life-long personalized learning and inference systems for analysis and perception of human affective behaviors. Such systems would benefit from long-term contextual information (including demographic and social aspects) as well as individual characteristics. This, in turn, would allow building intelligent agents (such as mobile and robot technologies) capable of adapting their behavior in a continuous and on-line manner to the target contexts and individuals. This special issue aims at contributions from computational neuroscience and psychology, artificial intelligence, machine learning, and affective computing, challenging and expanding current research on interpretation and estimation of human affective behavior from longitudinal behavioral data, i.e., single or multiple modalities captured over extended periods of time allowing efficient profiling of target behaviors and their inference in terms of affect and other socio-cognitive dimensions. We invite contributions focusing on both the theoretical and modeling perspective, as well as applications ranging from human-human, human-computer and human-robot interactions. II. Potential Topics Given computational models, the capability to perceive and understand emotion behavior is an important and popular research topic. That is why recent special issues on the IEEE Journal on Transactions on Affective Computing covered topics from emotion behavior analysis “in-the-wild” to personality analysis. However, most of the research published by these specific calls treat emotion behavior as an instantaneous event, relating mostly to emotion recognition, and thus neglect the development of complex emotion behavior models. Our special issue will foster the development of the field by focusing excellent research on emotion models for long-term behavior analysis. The topics of interest for this special issue include, but are not limited to: - New theories and findings on continuous emotion recognition - Multi- and Cross-modal emotion perception and interpretation - Lifelong affect analysis, perception, and interpretation - Novel neural network models for affective processing - New neuroscientific and psychological findings on continuous emotion representation - Embodied artificial agents for empathy and emotion appraisal - Machine learning for affect-driven interventions - Socially intelligent human-robot interaction - Personalized systems for human affect recognition III. Submission Prospective authors are invited to submit their manuscripts electronically, adhering to the IEEE Transactions on Affective Computing guidelines ( https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369) Please submit your papers through the online system ( https://mc.manuscriptcentral.com/taffc-cs) and be sure to select the special issue: Special Issue/Section on Automated Perception of Human Affect from Longitudinal Behavioral Data. IV. IMPORTANT DATES: Submissions Deadline: 15th of January 2019 Deadline for reviews and response to authors: 06th of April 2019 Camera-ready deadline: 05th of August 2019 V. Guest Editors Pablo Barros, University of Hamburg, Germany Stefan Wermter, University of Hamburg, Germany Ognjen (Oggi) Rudovic, Massachusetts Institute of Technology, United States of America Hatice Gunes, University of Cambridge, United Kingdom -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/

Dec. 11, 2018

International Student Fellowship at the PhD level in Computational Neuroscience

by Vinita Samarasinghe

Prof. Sen Cheng, Institute for Neural Computation at the *Ruhr University Bochum* in Germany, invites applicants for an International Student Fellowship to be awarded through the international research training group “Integration and Representation of Sensory Processes” (SFB 874). After successful completion of this 4 month fellowship, the student might be offered a PhD position for a further 3 years. The work will focus on studying the interaction between neocortex and hippocampus using spiking neural network models. The position is part of the project "Theory of the interplay between sensory cortices and hippocampus in memory formation and retrieval", which is funded by the German Research Foundation as part of the collaborative research center SFB 874. The appointment will be initially from 01.03.2019-30.06.2019. Candidates should have an excellent university degree in neuroscience, physics, mathematics, engineering or a related field and be eligible to enroll in a relevant PhD program at the Ruhr University. Competence in mathematical modeling and excellent programming skillsare mandatory. Familiarity with computational neuroscience or computational cognitive modeling would be a further asset. Only candidates who have not previously lived in Germany will be considered. For further information regarding the IRTG fellowship please visit https://www.ruhr-uni-bochum.de/sfb874/integrated_research_training_group/fe… The Ruhr University Bochum is home to a vibrant research community in neuroscience and cognitive science. The Institute for Neural Computation is an independent research unit and combines different areas of expertise ranging from experimental and theoretical neuroscience to machine learning and robotics. For further information see www.rub.de/cns <http://www.rub.de/cns>. To apply please send a statement of your motivation and research interests, academic transcripts, and a complete CV to samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de> in a single PDF file. Please, also request from at least two academic referees that they send letters of reference directly to the same email address. The deadline for applications is 15.01.2019. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Universitätstr. 150 D-44801 Bochum Tel: +49 (0)234 32 27316 Email: samarasinghe(a)ini.rub.de Hours: Mon. - Fri. 8-11

Dec. 11, 2018

Postdoc on resting state analysis in Glasgow

by Robin

Postdoc developing information theoretic methods for resting state analysis A 2-year postdoc position is available working with Dr. Robin Ince at the University of Glasgow. The project is funded by the Wellcome Trust and will involve developing and applying multivariate information theoretic methods to resting state fMRI data from the Human Connectome Project. The position will also involve collection of simultaneous EEG-fMRI resting state data in Glasgow. The ideal candidate will have strong expertise with numerical programming (MATLAB or Python) and be familiar with neuroimaging data and analysis. Glasgow is a friendly, lively and welcoming city with a reasonable cost of living and close proximity to the beautiful Highlands and a wide range of outdoor activities. International applicants should note that Glasgow voted 67% in favour of remaining in the EU and is the second most welcoming city to foreigners in the mainland UK (after London) [1], as well as being one of the safest cities in the UK [2]. The Centre for Cognitive Neuroimaging (CCNi) at the Institute of Neuroscience and Psychology (INP) is a collaborative and stimulating environment with a full suite of world-class facilities, including EEG, MEG, 3T fMRI, 7T fMRI, EEG-fMRI, TMS, and extensive computational resources (~2500 cores, ~15TB RAM). The position is a Research Assistant on Grade 6 of the University of Glasgow salary scale: £28,660 - £32,236 (plus ~18% employer contributions to USS defined benefit pension). Apply online at https://www.gla.ac.uk/it/iframe/jobs/ Search for ref: 023869 Closing date for applications Jan 13th 2019. Flexible start date. Any questions about the project, position or application process please contact robin.ince(a)glasgow.ac.uk Institute of Neuroscience & Psychology College of Medical Veterinary & Life Sciences University of Glasgow [1] Eurostat Urban Europe Report 2016. [2] Mercer Quality of Living Ranking 2016.

Dec. 10, 2018

SMARTSTART Program accepts the next round of applications

by SMARTStart

Dear colleagues, please be invited to share the information on the training program SMARTSTART Computational Neuroscience with your students: **** On January 1, 2019, the SMARTSTART Program accepts the next round of applications. The program offers students and prospective doctoral students the opportunity to complement their previous studies with concepts, theories and techniques of computational neuroscience. Target groups are: 1. students who are enrolled in a relevant Master's program in Germany during the funding period Sep 19 - Sep 20 (SMARTSTART 1) and 2. students who have successfully completed a relevant Master's program at the start of their funding period without having started a doctoral project (SMARTSTART 2). Applications can be submitted from January 1 until February 28, 2019 at the application platform on https://www.smartstart-compneuro.de/ SMARTSTART is the Joint Training Program in Computational Neuroscience of the Bernstein Network; the program is funded by the Volkswagen Foundation. The program was launched in 2016 with the support of the Volkswagen Foundation. Since then, more than 60 students have successfully completed the program. Many of them are currently continuing their research projects as doctoral projects. **** Kind regards, Janina Radny - SMARTSTART coordinator -- Smart Start - Joint Training Program in Computational Neuroscience Bernstein Network Computational Neuroscience Smart Start Coordination Office at the Bernstein Coordination Site (BCOS) Branch Office of the Forschungszentrum Jülich at the University of Freiburg postal address: Hansastr. 9A | 79104 Freiburg, Germany phone: (+49) 0761 203 9593 mail: smartstart(a)fz-juelich.de<mailto:smartstart@fz-juelich.de> web: www.smartstart-compneuro.de<http://www.smartstart-compneuro.de> ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

Dec. 10, 2018

PhD Studentships available in Prof K Tsaneva-Atanasova's group at the University of Exeter

by Tsaneva, Krasimira

A number of Open PhD Positions are available at the University of Exeter: * Interactive virtual reality for individuals with complex PTSD (http://www.exeter.ac.uk/codebox/phdprojects/Tsaneva-Atanasova-EPSRC-DTP-Pro…<http://www.exeter.ac.uk/codebox/phdprojects/Tsaneva-Atanasova-EPSRC-DTP-Pro…>). Apply to University of Exeter: http://www.exeter.ac.uk/studying/funding/award/index.php?id=3386 * Noise-cancelling technology for clock neurones (http://www.exeter.ac.uk/codebox/phdprojects/Sieber-EPSRC-DTP-Project.pdf) Apply to University of Exeter: http://www.exeter.ac.uk/studying/funding/award/index.php?id=3386 * Non-linear Dynamics of Human Locomotion (http://www.exeter.ac.uk/codebox/phdprojects/Williams-EPSRC-DTP-Project.pdf)<http://www.exeter.ac.uk/codebox/phdprojects/Williams-EPSRC-DTP-Project.pdf>. Apply to University of Exeter: http://www.exeter.ac.uk/studying/funding/award/index.php?id=3386 Please feel free to contact me on the email address below should you have any further questions. ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Associate Dean (International and Development) College of Engineering, Mathematics and Physical Sciences Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298 ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Associate Dean (International and Development) College of Engineering, Mathematics and Physical Sciences Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298 ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Associate Dean (International and Development) College of Engineering, Mathematics and Physical Sciences Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298

Dec. 7, 2018

Call for Proposals: Local Organizers for CNS*2020

by Sharon Crook

We look forward to seeing all of you next summer at the 2019 Computational Neuroscience meeting in Barcelona! However, it is already time to begin planning for CNS*2020. OCNS requests proposals from candidate local organizers to hold CNS*2020 at a location outside of Europe, preferably in North or South America. Groups or individuals interested in organizing the 2020 meeting should submit a proposal following the extensive on-line instructions and using the on-line templates at: https://www.cnsorg.org/cns-2020-local-organizer. Proposals should be submitted by email to the OCNS President at president(a)cnsorg.org no later than February 1, 2019.The OCNS Board Members will consider the proposals, contact local organizers for more information if necessary, and select a location in a timely agreement between OCNS and the potential local organizers. As usual, the selected location will be officially announced at the CNS Meeting in July. An earlier email to the OCNS President declaring the intent to submit a proposal would be appreciated, but is not required. Thank you! Your Organization for Computational Neuroscience Team

Dec. 7, 2018

CFP: Advances in HCI: SI on Advancing Big Data in Speech Computation

by Friedhelm Schwenker

CALL FOR PAPERS Advances in Human-Computer Interaction Special Issue on Advancing Big Data in Speech Computation Hindawi Submission Deadline: Friday, 31 May 2019 Publication Date: October 2019 Big Data is an emerging topic in a broad variety of research areas, with the promise to allow predictive user behavior analytics for a wide variety of speech patterns like emotions, sentiment, personality, and pathology. With the emerging voice assistants, such as Amazon Alexa or Google Assistant, speech interaction has attracted increasing attention. In addition, further speech-based HCI-systems could benefit from big data computation, such as Speech-to-Speech translation systems, conversational agents, and educational systems. Unfortunately, when dealing with speech computation tasks, oen only comparably small amounts of data are available, or the collection is cumbersome.Thus, advanced methods such as transfer learning, active learning, data synthesis, and (semi-)automatic annotation methods or domain-/topic-adaptation are needed. This special issue welcomes original research papers concerned with the big data exploitation of speech data, particularly in HCI-related contexts. We encourage researchers to submit review articles describing the current state of the art in speech-based big-data analyses. Submissions dealing with data synthesis or recordings and automatic annotation of large sets of speech data are highly encouraged. Potential topics include but are not limited to the following: * Speech data transfer learning and active learning for HCI systems * (Semi-) Automatic speech data analyses for HCI systems * Big data language modeling for HCI systems * Generative adversarial networks for speech-based HCI behavior analytics * Methods review for big data in advancing speech-based HCI * Comparison of big data and small data approaches for speech-based HCI * Application of Big data methods for speech based HCI-systems Authors can submit their manuscripts through the Manuscript Tracking System at https://mts.hindawi.com/submit/journals/ahci/abd/. Papers are published upon acceptance, regardless of the Special Issue publication date. Lead Guest Editor Ingo Siegert, Otto von Guericke University, Magdeburg, Germany ingo.siegert(a)ovgu.de Guest Editors Anna Esposito, Università della Campania "Luigi Vanvitelli", Napoli, Italy anna.esposito(a)unicampania.it Friedhelm Schwenker, University of Ulm, Ulm, Germany friedhelm.schwenker(a)uni-ulm.de Gennaro Cordasco, Anna Esposito, Università della Campania "Luigi Vanvitelli", Napoli, Italy gennaro.cordasco(a)unicampania.it -- PD Dr. Friedhelm Schwenker University of Ulm Institute of Neural Information Processing D-89069 Ulm, Germany phone: +49-731-50-24159 fax: +49-731-50-24156 email: friedhelm.schwenker(a)uni-ulm.de www: http://www.uni-ulm.de/in/neuroinformatik/mitarbeiter/f-schwenker.html

Dec. 7, 2018

PhD in Computational and Mathematical Neuroscience (EPSRC funded, 3.5 yrs, Sept 2019 start)

by James Rankin

*PhD in Computational and Mathematical Neuroscience (EPSRC funded, 3.5 yrs, Sept 2019 start)* General information & apply (funding is primarily targeted at UK students): http://www.exeter.ac.uk/studying/funding/award/index.php?id=3386 Project description: http://www.exeter.ac.uk/codebox/phdprojects/Rankin-EPSRC-DTP-Project.pdf *Closing date 7th Jan 2019* This interdisciplinary project will develop computational and mathematical models of the auditory system to understand how complex stimuli like speech are encoded by spiking neurons in the midbrain. The auditory midbrain is a key hub in the auditory processing pathway, functioning as an important junction that relays and shapes neural signals as they ascend towards auditory cortex. Knowledge of the way in which complex sounds, e.g. speech, are encoded in the midbrain is crucial for understanding how dysfunction in the earlier auditory processing pathway (cochlea, auditory nerve, cochlear nucleus) leads to different types of hearing loss (a problem affecting 1 in 6 people in the UK). Working with neural recordings from the auditory midbrain in gerbils, a commonly-used animal for the study of low-frequency hearing, this project will develop mathematical and computational models of the auditory processing pathway. The aim is to understand the different roles of the patterns of inputs to midbrain neurons and their intrinsic response properties (e.g. their spiking rate) in shaping their responses to complex sounds. The project will use a dynamical systems approach to model the intrinsic properties of individual neurons in the midbrain in a biologically plausible way (working with, e.g. adaptive exponential integrate-and-fire neurons or the Hodgkin-Huxley equations). Inputs to these neurons will be based on established cochlear models and the biological details of the auditory nerve and cochlear nucleus. The resulting model will produce firing patterns directly comparable with neural recordings provided by the experimental supervisor. This data will be used to train and parameter fit the model using e.g. Bayesian optimisation or genetic algorithms. The resultant model will have explanatory power for the extent to which midbrain responses are shaped by its inputs from cochlear nucleus. Further, it will make predictions, testable in new experiments, of how midbrain responses will be affected by different dysfunctions of the early auditory system relating to hearing loss. The successful candidate will receive training dynamical systems theory and in the development and analysis of individual neuron and neural network models. An interdisciplinary approach, incorporating known biological details of the auditory processing pathway, will require the candidate to learn the relevant biology and neuroscience along with mathematical and computational techniques. The project will involve working closely with experimental neuroscientists and experimental data. This project provides a unique opportunity to receive training in mathematical modelling in close collaboration with experimentalists using cutting-edge methods recording spikes simultaneously from hundreds of neurons. Experience working on such interdisciplinary projects is highly sought after. Candidates with quantitative backgrounds (mathematics, physics, engineering) and from neuroscience programmes are encouraged to apply. Programming experience, knowledge of dynamical systems theory and experience in biological modelling are a plus. For further information, please contact me at the email address above. *For further information, please contact Dr James Rankin, email j.a.rankin(a)exeter.ac.uk <j.a.rankin(a)exeter.ac.uk>* http://emps.exeter.ac.uk/mathematics/staff/jar226

Dec. 7, 2018