December 2019 - Comp-neuro - lists.cnsorg.org

Reminder: Special Entropy Issue "Information Theory in Computational Neuroscience"
by Dimitrije Markovic Dec. 16, 2019

Dec. 16, 2019

Dear Colleagues, We cordially invite you to submit a manuscript for possible publication in a Special Issue on "Information Theory in Computational Neuroscience" to be published in the journal Entropy (ISSN 1099-4300, IF 2.419, http://www.mdpi.com/journal/entropy) The aim of the Special Issue is to bring together neuronal models and neuronal plasticity mechanisms that are grounded in information theory principles, modern inference, and learning algorithms. We welcome submissions that use information theory as the basis for defining generative principles of neuronal dynamics over multiple spatio-temporal scales, which informs our understanding of information processing in the brain. You can see full details of the scope and submission details at: https://www.mdpi.com/journal/entropy/special_issues/Computational_Neuroscie… The submission deadline is 31 January 2020. You may send your manuscript at any time before the deadline or a bit later. Submitted papers should not be under consideration for publication elsewhere. Entropy is fully open access. Open access (unlimited and free access by readers) increases publicity and promotes more frequent citations, as indicated by several studies. Please kindly note that an Article Processing Charge (APC) of CHF 1600 currently applies to all accepted papers. Fortunately, it is noticed that your institute have already had a central open access fund established in MDPI's Institutional Open Access Program, it means you do not have to pay the publication fees and your institute will cover it for you if you submit your papers to MDPI journals (see details at: <http://www.mdpi.com/about/ioap><http://www.mdpi.com/about/ioap>). You may contact your library and confirm this. Please do not hesitate to come back to us if there is anything further that we can help with. We look forward to hearing from you. Kind regards, Dimitrije Markovic and Claudius Gros ============================= Dr. Dimitrije Markovic Post-Doc at Technische Universität Dresden, Department of Psychology, Dresden, Germany Lab website: https://tu-dresden.de/mn/psychologie/ifap/ni Phone: +49-351-463-43146 Personal website: http://dimarkov.github.io/ =============================

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PhD position in Bern
by Jean-Pascal Pfister Dec. 16, 2019

Dec. 16, 2019

The Department of Physiology at the University of Bern is opening a PhD position in computational neuroscience at the interface with experimental neuroscience. The cerebral cortex endows us with the ability to perform complex cognitive and emotional processes supporting adaptive behavior. The hippocampus is a high-order cortical area instrumental for cognition and emotions. The PhD project will focus on discovering selective computations related to spatial navigation and emotional states using hippocampal neural recordings in behaving rodents. It will further develop predictive models for animal position taking into account uncertainty of hidden states such as emotions. The specificity of the project is the close interactions between theory and experiments. The candidate will have access to experimental data acquired within the research group of Stéphane Ciocchi and the supervision will be shared with Jean-Pascal Pfister of the Theoretical Neuroscience Group. The candidate should hold a Master degree in Physics, Mathematics, Biology, Neuroscience, Computational Neuroscience or a related field. She/he should have keen interests in close interactions between theory and experiments. Interested candidates can send their application and inquiries via email to pfister(a)pyl.unibe.ch <mailto:pfister@pyl.unibe.ch>, ciocchi(a)pyl.unibe.ch <mailto:ciocchi@pyl.unibe.ch> The application should include the following in one pdf document: letter of motivation, CV, contact details of 2 references. The position is funded for a duration of three years. The PhD position shall start early in 2020. Deadline for application is the 31st of January 2020 or until the position is filled. References: Ciocchi, S., Passecker, J., Malagon-Vina, H., Mikus, N., Klausberger, T. Selective information routing by ventral hippocampal CA1 projection neurons. Science (2015). Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception. Kutschireiter A, Surace SC, Sprekeler H, Pfister JP. Sci Rep (2017). --------------------------------- Prof. Jean-Pascal Pfister Theoretical Neuroscience Group Institute of Neuroinformatics University of Zurich and ETH Zurich Winterthurerstrasse 190 8057 Zurich, Switzerland and Department of Physiology University of Bern Bühlplatz 5 3012 Bern, Switzerland www.ini.uzh.ch/~jpfister Tel: ++ 41 31 631 87 78

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Stellenanzeige
by Obermayer, Klaus, Prof. Dr. Dec. 16, 2019

Dec. 16, 2019

Dear moderator, can you post our job announcement (see below) on the neuroinformatics mailing list? Thank you very much! Best regards Klaus Obermayer ---------------------------------------------------------------------------------------------------------------------------------------- Neural Information Processing Group @ Technische Universität Berlin Research Assistant (PhD Position) in Computational Neuroscience Brain network models: Dynamics and Control Salary grade E13 (TV-L Berliner Hochschulen) Duration: 34 months Starting date: March 1st, 2020 Working field: The successful candidate is supposed to work on the analysis and simulation of calibrated whole-brain networks using neuronal mass models and on the design and evaluation of novel control schemes for the stabilization of and the switching between dynamical states. She/he will be part of the Collaborative Research Center "Control of self-organizing nonlinear systems: Theoretical methods and concepts of application" (https://www.itp.tu-berlin.de/sfb910/ sonderforschungsbereich_910/sonderforschungsbereich_910/) as well as the Bernstein Center for Computational Neuroscience Berlin (https://www.bccn-berlin.de/) The candidate is also expected to interact with clinical scientists who are interested in the non-invasive manipulation of the whole-brain dynamics using transcranial current stimulation. Requirements: Successfully completed university degree (Master, Diplom, or equivalent) in Computational Neuroscience, Computer Science, Electrical Engineering, Mathematics, Physics, or related fields; in-depth knowledge in dynamical systems, knowledge in the area of control of non-linear dynamical systems is desirable; very good programming and English language skills. How to apply: Please send your application with the usual documents (CV, motivation letter, transcripts of records, certificates, and the names of two persons who can provide recommendation letters) to Prof. Dr. Obermayer, FG Neuronale Informationsverarbeitung, Sekr. MAR 5-6, Marchstr. 23, 10587 Berlin, Germany, or - preferably - by e-mail to klaus.obermayer(a)tu-berlin.de. For information about the research group see https://www.ni.tu-berlin.de/ Please send copies only. Original documents will not be returned. Aplication deadline for full consideration: 31. 1. 2020 Applications, however, will be accepted until the position is filled.

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2 postdoctoral positions at the Learning and Cognitive Control Lab, Ghent University, Belgium
by Clay Holroyd Dec. 14, 2019

Dec. 14, 2019

The Learning and Cognitive Control Lab at Ghent University (Belgium) is recruiting two postdoctoral fellows. The positions are funded by a European Research Council Advanced Grant, “Cracking the Anterior Cingulate Cortex Code: Toward a Unified Theory of ACC Function” ( https://cordis.europa.eu/project/rcn/216511/factsheet/en ; for an example of our approach, please see doi 10.1073/pnas.1803650115 ). The positions are for two years with an opportunity to renew and are available to start immediately. Applications will be accepted until the positions are filled. Position 1: The successful candidate will work on the development of a hierarchical recurrent neural network model of anterior cingulate cortex. A Ph.D. and a background in computational cognitive neuroscience, broadly defined, are required. The applicant must have experience with neural network modeling. Position 2: The successful candidate will conduct functional magnetic resonance imaging experiments following a model-based cognitive neuroscience approach. A Ph.D. and a background in psychology, cognitive neuroscience, or a closely related discipline are required. Prior fMRI training as well as good programming skills (e.g., Python, Matlab) are required. Interested candidates should email their CV, a statement of research interests, and have three letters of reference forwarded to Clay Holroyd at clay.holroyd(a)ugent.be. Inquiries may be directed to him at that email address.

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Post-doctoral fellowships and faculty positions for Women in the faculty of engineering from Univ. de Sherbrooke, Québec, Canada
by Jean Rouat Dec. 13, 2019

Dec. 13, 2019

Dear all, Please can you circulate? - The Faculty of Engineering at Université de Sherbrooke is launching a competition that fits perfectly with its bold and creative mission. Female doctoral candidates and young doctoral graduates can now participate in the Claire-Deschênes Postdoctoral Fellowship Competition. - The goal of the Claire-Deschênes Postdoctoral Fellowship Competition is to promote postdoctoral training for women who will also be offered a professorship position in engineering at Université de Sherbrooke. - Submit your application and you could get one of eight postdoctoral fellowships ($ 40,000/year, up to 2 years) each attached to a professorship at the Université de Sherbrooke. - For more information follow these links: English: https://www.usherbrooke.ca/promo/genie/claire-deschenes-en/ Français: https://www.usherbrooke.ca/promo/genie/claire-deschenes/ All the best Jean Jean Rouat, Prof., coord. IGLU, http://iglu-chistera.github.io Université de Sherbrooke Member of the centre for Interdisciplinary research Professeur titulaire, in Music Media and Technology NECOTIS: Computational Neurosciences McGill Schulich School of Music and Intelligent Signal Processing 527 Sherbrooke St. West Faculté de génie, GEGI, C1-3108 Montreal, Qc, 2500 boul. de l'université Canada, H3A 1E3 Sherbrooke, Québec Canada, J1K 2R1 Tél.: +1(819)-821-8000 ext. 63864 http://www.gel.usherbrooke.ca/rouat http://www.gel.usherbrooke.ca/necotis http://www.usherbrooke.ca/gelecinfo/fr/pers/profs/rouj-fr/ Jean.Rouat(a)umontreal.ca ou Jean.Rouat(a)usherbrooke.ca https://www.usherbrooke.ca/recherche/fr/expertus/?getSpecialist=369656&page… https://www.gel.usherbrooke.ca/rouat/publications/publiDeJRouat.html

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postdoctoral position Canavier lab New Orleans- hippocampal modeling
by Canavier, Carmen C. Dec. 12, 2019

Dec. 12, 2019

A Postdoctoral Researcher position is available in the computational neuroscience lab of Carmen Canavier in the School of Medicine, Department of Cell Biology and Anatomy at LSU Health Sciences Center in New Orleans, Louisiana, USA. The position is to study cholinergic contributions to hippocampal information processing in close collaboration with electrophysiologist Sonia Gasparini. The successful candidate will construct a morphologically and biophysically realistic model of a hippocampal CA1 pyramidal neuron to explain the observed integration of synaptic inputs and the effects of neuromodulation. Some network modeling will also be required for the project. If interested, please apply at https://lsuhsc.peopleadmin.com/postings/6717 The primary duties will involve linear and non-linear analyses, writing code, calibrating single neuron models, and generating predictions that lead to additional experiments. Candidates must have a Ph.D. in Neuroscience, Engineering, Mathematics, Physics, Computer Science or a related field of study. The ideal candidate would have experience with the simulation package NEURON and some knowledge of the hippocampus. Familiarity with nonlinear dynamics, signal processing, and coding in C and or python in a Linux environment is also desirable. If you have questions, please email Dr. Canavier at ccanav(a)lsuhsc.edu<mailto:ccanav@lsuhsc.edu>. LSUHSC is an Equal Opportunity Employer for females, minorities, individuals with disabilities and protected veterans.

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BBSRC MIBTP PhD Studentships in Computational Neuroscience at Leicester
by Jian Liu Dec. 12, 2019

Dec. 12, 2019

Three fully-funded BBSRC MIBTP PhD Studentships in Computational Neuroscience are available at the Centre for Systems Neuroscience, the University of Leicester (UK). To apply, please visit: https://le.ac.uk/study/research-degrees/funded-opportunities/bbsrc-mibtp <https://www.google.com/url?q=https%3A%2F%2Fle.ac.uk%2Fstudy%2Fresearch-degr…> https://sites.google.com/site/jiankliu/join-us *The application deadline is 12 January 2020.* *1. Neuronal coupling across spatiotemporal scales and dimensions of cortical population activity* * Dr. Michael Okun and Dr. Jian Liu, CSN/NPB, University of Leicester* https://www.findaphd.com/phds/project/neuronal-coupling-across-spatiotempor… The human cortex is the most complex known system. It is responsible for a vast range of sensorimotor, decision making, and other cognitive abilities of humans and other mammals. The activity of cortical neuronal networks is organised across multiple spatiotemporal scales, and remains poorly understood. Our laboratory is particularly interested in the relationship between the activity of an individual neuron and of the larger networks within which the neuron is embedded (Lewis, 2015). For example, we have recently compared the coupling between neurons and their local network across an extensive range of timescales, finding major timescale-dependent distinctions, suggestive of different mechanisms regulating cortical activity on different timescales (Okun et al., 2019). We use recordings using next-generation high-density silicon probes for data collection (Jun et al., 2017) and advanced computational methods for their analysis. There are several computational projects available in the above research area, relying on data we are collecting in the laboratory as part of ongoing projects, as well as on publicly available datasets. The projects are suitable for students with a background in exact sciences or computer science and programming. *2. Decoding movement kinematics from subpopulations of motor cortex neurons* * Dr. Todor Gerdjikov and Dr. Jian Liu, CSN/NPB, University of Leicester* https://www.findaphd.com/phds/project/decoding-movement-kinematics-from-sub… The purpose of the current project is to investigate novel approaches for decoding movement parameters from neural data acquired from morphologically distinct motor cortex neurons. Using computational approaches we will investigate the relationship between forelimb movement kinetics and neural activity in subpopulations of output-defined motor cortex neurons. Firstly, we will link activity in discrete output-defined M1 neuronal populations to movement parameters in rats trained in a skilled reaching task. This aspect of the work will rely on modern viral approaches to separately tag neurons belonging to different projections and record their activity in behaving rats using fibre photometry and/or extracellular neurophysiology. Computational approaches such as machine learning and neural network modelling will be used to decode kinematics derived from movement data. A second aspect of the work will involve causal experiments where we will use optogenetics to selectively ‘turn off’ the activity of discrete projections. We will investigate how these manipulations affect fine motor control in behaving rats to causally tease apart the contribution of each projection to motor control. *3. Towards a functional model for associate learning and memory formation* * Dr. Jian Liu and Professor Rodrigo Quian Quiroga, CSN/NPB, University of Leicester* https://www.findaphd.com/phds/project/towards-a-functional-model-for-associ… This project aims to study the most up-to-date experimental data regarding single-neuron and network learning and coding in humans, with the expectation that a functional model could be established thereon. If possible, this model shall be not just biologically descriptive but also computationally implementable, as the stimulation protocol is based on the natural scenes of visual and auditory scenes that are beyond the simple protocols. This project involves data analysis where the data of human recordings will be provided by local researchers at our Centre. We will have access to the data of single-cell hippocampal recordings during memory and learning tasks of human subjects under the natural stimulations. Based on these data, we will draw a hypothesised theoretical model that is plausible for these new sets of experimental data as well as for other related published results. Furthermore, designs of new experiments based on the theoretical predictions shall also be made such that the model could be experimentally testified or falsified.

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Postdoc position at CNRS/Inserm
by James Bonaiuto Dec. 11, 2019

Dec. 11, 2019

Dear all, I'd like to announce the following postdoctoral position on the role of oscillations in brain communication and motor behavior: This position is available for a highly motivated postdoctoral researcher in Lyon, France, at the Lyon Neuroscience Research Center (CRNL) and at the Institute for Cognitives Sciences Marc Jeannerod (ISCMJ) under the direction of Mathilde Bonnefond, Ph.D and James Bonaiuto, PhD. The position is funded for 7 months and 2 years by two grants from the European Research Council (n°716862 and n°864550 respectively). The project is aimed at determining the role 1) of brain oscillations at different frequencies in brain communication and 2) of beta bursts in motor behavior. The candidate will use cutting edge techniques in both high precision magnetoencephalography (MEG) and high resolution functional magnetic resonance imaging (fMRI, 3.0 T Siemens scanner) with healthy human volunteers. The post-doctoral fellow will: • develop and optimize the analysis of laminar level source signals as well as cortico-cortical functional connectivity applied to oscillatory activities. • analyze data from an fMRI experiment aiming at optimizing the analysis of MEG data for each participant. • analyze the relationship between three-dimensional movement kinematics and beta burst activity • synthesize results, write reports and scientific articles. The postdoctoral fellow will work together with a research assistant whose involvement in MEG/fMRI recording will be limited. Enthusiastic and self-motivated candidates are encouraged to apply. The successful candidate will benefit from structured mentoring support and opportunities for travel and presentation at national meetings. The CRNL and ISCMJ are multidisciplinary research institutes offering a vibrant working atmosphere in an international environment with multiple opportunities for seminars, workshops and methodological clubs. *Expected starting date*: Mid-February 2018 the earliest, but applications will be considered until the position is filled. *Job Requirements: * * [Mandatory] Ph.D. in Cognitive Neuroscience, Engineering or related field * [Mandatory] Autonomy in programming in MATLAB or Python * [Mandatory] Experience in using imaging analysis software (MNE, SPM, Fieldtrip, FSL, BrainVisa ...) * Knowledge of brain oscillations and signal processing * Experience with computer vision and analysis of movement kinematics is a plus * Fluency and solid writing skills in English are expected. French is absolutely not a requirement. *How to Apply: * Please send your application to BraindynMobeta(a)gmail.com with the following information: -CV including a brief (1/2 page) summary of previous research -Short letter of motivation describing research interests -Name of two colleagues who could provide a recommendation Please indicate "Post-doc application Braindyn Mobeta" as the subject of your email. James Bonaiuto Institut des Sciences Cognitives Marc Jeannerod 67 Bd Pinel <https://maps.google.com/?q=67+Bd+Pinel&entry=gmail&source=g>, 69675, Bron Cedex, France james.bonaiuto(a)isc.cnrs.fr

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[jobs] Neural Network models for language and interactive robots
by Wermter, Stefan Dec. 10, 2019

Dec. 10, 2019

The Department of Informatics, Institute of Knowledge Technology, invites applications for multiple positions as RESEARCH ASSOCIATES (Postdocs and PhD Students) in the context of the project CROSSMODAL LEARNING: Neural network models for language and interactive robots. Positions commence from January 2020 or as soon as possible thereafter and are in accordance with Section 28 subsection 3 of the Hamburg higher education act (Hamburgisches Hochschulgesetz, HmbHG) on SALARY LEVEL 13 TV-L. These are fixed-term contracts in accordance with Section 2 of the academic fixed-term labor contract act (Wissenschaftszeitvertragsgesetz, WissZeitVG). The term is fixed for up to 4 years until 31st of December 2023. The full-time positions call for 39 hours per week. Responsibilities: Duties include academic services in the project named above. Research associates may also pursue independent research and further academic qualifications. Specific Duties: Duties in the project include the design, development and evaluation of neurocognitive models of crossmodal language learning as well as neurorobotic models for crossmodal joint attention and social interaction. The overall project aims to deepen interdisciplinary research between computer science, neuroscience, and psychology in order to set up collaborative research with a focus on human-robot-collaboration, artificial intelligence, neuroscience and psychology while focusing on the topic of cross-modal learning. The long-term challenge is to understand the neural, cognitive and computational evidence of cross-modal learning and to use this understanding for (1) better analyzing human performance with cross-modal correspondence and (2) building effective cross-modal computational and robot systems. Requirements: A university degree in a relevant subject. For doctoral positions, academic degree of MSc in computer science, computer engineering or similar. For post-doctoral positions, a doctorate, or equivalently the experience of more than three years of doctoral studies plus publications in the area of Intelligent Systems are required. The degree must qualify the post holder to carry out the above-mentioned duties. Programming skills in some of Python, C, ROS, Tensorflow or PyTorch are required. Your demonstrated research interests should be in some of the areas of Intelligent Systems (e.g. Neural Networks, Robotics, Machine Learning, Speech, Vision, or Affective Processing). International publication experience is expected. Very good communication skills in English are expected. The University aims to increase the number of women in research and teaching and explicitly encourages qualified women to apply. Equally qualified female applicants will receive preference in accordance with the Hamburg act on gender equality (Hamburgisches Gleichstellungsgesetz, HmbGleiG). Qualified disabled candidates or applicants with equivalent status receive preference in the application process. As a University of Excellence, Universität Hamburg is one of the strongest research universities in Germany. As a flagship university in the greater Hamburg region, it nurtures innovative, cooperative contacts to partners within and outside academia. It also provides and promotes sustainable education, knowledge, and knowledge exchange locally, nationally, and internationally. For further information, please contact Prof. Dr. Stefan Wermter or consult our website at: https://www.informatik.uni-hamburg.de/wtm/ Applications should include a cover letter, a tabular curriculum vitae, pdf of best publications, and copies of degree certificate(s). Please send applications by 15.01.2020 or until the post gets filled to Ms Katja Koesters (katja.koesters(a)informatik.uni-hamburg.de) in a single pdf document. *********************************************** Professor Dr. Stefan Wermter Director of Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Email: wermter AT informatik.uni-hamburg.de https://www.informatik.uni-hamburg.de/WTM/ ***********************************************

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Fully funded PhD position: interdisciplinary work on machine/deep learning and visual cognitive neuroscience
by Tim Kietzmann Dec. 10, 2019

Dec. 10, 2019

Dear all, I am hiring a graduate student to join our group at the Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, NL. Please spread the word, or consider applying if you are interested in working with us on machine/deep learning and visual cognitive neuroscience. - 40 hours per week - Maximum gross monthly salary: € 2,972 - Up to four years, fully funded - Application deadline: 15 December 2019 Please find more details on the job post here: https://www.ru.nl/werken-bij/vacature/details-vacature/?recid=1072356 Details on our work can be found here: http://www.timkietzmann.de Best wishes Tim __________________________________ *Dr. rer. nat. Tim C Kietzmann* Assistant Professor Donders Institute for Brain, Cognition and Behaviour DCC Department for Artificial Intelligence Radboud University, NL Senior Research Associate, Graduate Supervisor MRC Cognition and Brain Sciences Unit University of Cambridge Web: http://www.timkietzmann.de Email: t.kietzmann(a)donders.ru.nl Twitter: @timkietzmann

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PhD position at Tel Aviv University: Enhancing motor learning with computational scaffolding
by Jason Friedman Dec. 10, 2019

Dec. 10, 2019

A funded PhD position is available at Tel Aviv University in the Movement Sciences lab with Dr. Jason Friedman, in the field of human motor control, on the topic of enhancing motor learning. The PhD will be part of a larger collaborative project with Prof. Helge Ritter from Bielefeld University, Germany, where they investigate manual intelligence of both humans and robots. In this project, we will use a technique called computational scaffolding in order to speed up the process of motor learning. In this technique, a temporary structure (scaffold) is provided during the learning process and slowly removed as learning takes place. We will use this technique to individualize and enhance the motor learning process in two applications – learning how to play the piano and learning a new swimming stroke. The student will be involved in all aspects of the project, included running experiments, recording and analyzing movement data, applying motor guidance for enhancing learning, and active collaboration with our partners. Students with a background in Motor Control, Physical Therapy, Neuroscience, Psychology, Physics, Computer Science, Biomedical engineering or related areas are encouraged to apply. Programming experience in Python or other languages, and a musical background is an advantage. Please contact Dr. Friedman (jason(a)tau.ac.il) with a CV for further information.

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Call for Applications - 2020 Nengo Summer School
by Peter Blouw Dec. 9, 2019

Dec. 9, 2019

[All details about this school can be found online at https://www.nengo.ai/summer-school] The Centre for Theoretical Neuroscience at the University of Waterloo is excited to announce our 7th annual Nengo summer school on large-scale brain modelling and neuromorphic computing. This two-week school will teach participants to use the Nengo simulation package to build state-of-the-art cognitive and neural models to run both in simulation and on neuromorphic hardware. Summer school participants will be given on-site access to Loihi, Intel’s neuromorphic research chip [1], and will learn to run high-level applications on Loihi using Nengo! More generally, Nengo provides users with a versatile and powerful environment for designing cognitive and neural systems, and has been used to build what is currently the world's largest functional brain model, Spaun [2], which includes spiking deep learning, reinforcement learning, adaptive motor control, and cognitive control networks. For a look at a recent summer school, check out this short video: https://goo.gl/4tVUkQ <https://www.youtube.com/watch?v=NwtYgBB2N6I&t=1s> We welcome applications from all interested graduate students, postdocs, professors, and industry professionals with a relevant background. [1] Davies, et al. (2018). Loihi: A neuromorphic manycore processor with on-chip learning. IEEE Micro. Vol. 38 no. 1 pp. 82-99. [ https://ieeexplore.ieee.org/document/8259423] [2] Eliasmith, C., Stewart T. C., Choo X., Bekolay T., DeWolf T., Tang Y., Rasmussen, D. (2012). A large-scale model of the functioning brain. Science. Vol. 338 no. 6111 pp. 1202-1205. DOI: 10.1126/science.1225266. [ http://compneuro.uwaterloo.ca/files/publications/eliasmith.2012.pdf] ***Application Deadline: February 15, 2020*** Format: A combination of tutorials and project-based work. Participants are encouraged to bring their own ideas for projects, which may focus on building neuromorphic applications, modeling neural or cognitive data, implementing specific behavioural functions with neurons, expanding past models, or providing a proof-of-concept of various neural mechanisms. Hands-on tutorials, work on individual or group projects, and talks from invited faculty members will make up the bulk of day-to-day activities. A project demonstration event will be held on the last day of the school, with prizes for strong projects! Participants will have the opportunity to learn how to: - interface Nengo with various kinds of neuromorphic hardware (e.g. Loihi, SpiNNaker, BrainDrop) - interface Nengo with (spiking and normal) cameras and robotic systems - integrate machine learning methods into biologically oriented models - implement modern nonlinear control methods in neural models - build perceptual, motor, and sophisticated cognitive models using spiking neurons - model anatomical, electrophysiological, cognitive, and behavioural data - use a variety of single cell models within a large-scale model - and much more… Date and Location: June 7th to June 19th, 2020 at the University of Waterloo, Ontario, Canada. Applications: Please visit https://www.nengo.ai/summer-school/, where you can find more information regarding costs, travel, lodging, along with an application form. We ask that you provide a short description of a possible project, and to briefly indicate how this project might make use of the tools and methods that the summer school will be covering, as listed above. If you have any questions about the school or the application process, please contact Peter Blouw (peter.blouw(a)appliedbrainresearch.com) The school is partially supported by Applied Brain Research, Inc. We look forward to hearing from you!

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NEURONUS 2020 IBRO Neuroscience Forum (24-26 April 2020, Krakow, Poland)
by Michał Zaręba Dec. 9, 2019

Dec. 9, 2019

CALL FOR ABSTRACTS and REGISTRATION for NEURONUS 2020 IBRO Neuroscience Forum (24-26 April 2020, Krakow, Poland) are now OPEN! More information and the application forms can be found on our website: http://neuronusforum.pl/. With prominent speakers and an unique atmosphere of one of the oldest and most beautiful Polish cities, NEURONUS IBRO Neuroscience Forums have established themselves in the European calendar of scientific events as a platform for communication between scientists from different fields of neuroscience. The program of the conference consists of numerous sessions on biological, cognitive, computational and medical aspects of neuroscience, creating a dynamic environment for sharing knowledge. The schedule of the meeting is further complemented with lectures by invited guests, and we invest a lot of effort to attract as influential neuroscientists as possible. This year’s keynote speakers include: - Karl Friston (University College London, the UK) - Pico Caroni (University of Basel, Switzerland) - Karin Roelofs (Radboud University Nijmegen, the Netherlands) - Alejandro Schinder (Leloir Institute, Buenos Aires, Argentina) - Adam Hampshire (Imperial College London, the UK) - Dayu Lin (New York University School of Medicine, the USA) Furthermore, a special panel concerning the Future of Neuroscience will be held. So far, we have confirmed participation of two pioneering researchers: - Viktor Jirsa (Aix-Marseille University, France) - Dominik Paquet (Ludwig Maximilian University of Munich, Germany) During the upcoming 11th edition of the conference, we will traditionally continue to put emphasis on development of early-career researchers. The main purpose of this event is to provide means for both young and experienced neuroscientists to share the latest discoveries, knowledge and experience in neuroscience, as well as make valuable contacts with scientists representing various fields of neurobiology. We actively promote young scientists through preferentially allocating oral presentations of their experimental results. We strongly encourage you to join this special initiative, and hope to see you in the pleasant spring scenery of Krakow! On behalf of the Organising Committee, Michał Zaręba

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Openings for Machine Learning Engineer / Healthcare Data Analyst / Neural Engineer (multiple levels)
by Zanos, Theodoros Dec. 9, 2019

Dec. 9, 2019

The Neural and Data Science Lab at the Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research is currently recruiting for a Machine Learning Engineer / Healthcare Data Analyst / Neural Engineer (multiple levels). The lab focuses on data analysis and machine learning methods to develop algorithms that will power the next generation bioelectronic medicine devices to enable early diagnosis, disease severity assessment and personalization and adaptability of a therapy. The specific opening is part of our lab's ongoing efforts to gain actionable insights into advanced diagnostics and healthcare processes to improve the quality of care and enhance the patient experience. The successful candidate will lead cutting edge projects in healthcare data analytics, having access to state-of-the-art computing power (both on-prem and cloud-based) and access to enormous amounts of data from one of the largest health systems in the world. They will collect, organize and analyze data from various sources, collaborate with physicians and other research staff and publish and present data in a timely manner. They will also work collaboratively with other investigators to facilitate their scientific research and training. Furthermore, they will participate in various types of institute and community activities and may apply for grant funding and/or patents as appropriate. Required Qualifications/Skills - Graduate-level degree in electrical/biomedical engineering, computer science, or related fields - Fluent programming in Python and Matlab - Experience with scientific packages in Python: Numpy, Scipy, Pandas, Matplotlib - Background in machine learning: basic ML concepts, training, and evaluation of model Preferred Skills - Experience implementing custom ML models using Tensorflow - Worked both on Windows and Linux - Authored/co-authored research papers and/or scientific abstracts - Experience with various signal processing methods To apply, please send a cover letter describing your qualifications and an academic CV to tzanos at northwell.edu and include Machine Learning Engineer / Healthcare Data Analyst / Neural Engineer in the subject heading. Work Visa Sponsorship is available. Theodoros Zanos, PhD Assistant Professor Head, Neural & Data Science Lab www.neuraldatascience.org<http://www.neuraldatascience.org/> Institute of Bioelectronic Medicine, Room 1257 The Feinstein Institute for Medical Research Hofstra Northwell School of Medicine Phone: +1-516-562-0484 Email: tzanos(a)northwell.edu<mailto:tzanos@northwell.edu> The information contained in this electronic e-mail transmission and any attachments are intended only for the use of the individual or entity to whom or to which it is addressed, and may contain information that is privileged, confidential and exempt from disclosure under applicable law. If the reader of this communication is not the intended recipient, or the employee or agent responsible for delivering this communication to the intended recipient, you are hereby notified that any dissemination, distribution, copying or disclosure of this communication and any attachment is strictly prohibited. If you have received this transmission in error, please notify the sender immediately by telephone and electronic mail, and delete the original communication and any attachment from any computer, server or other electronic recording or storage device or medium. Receipt by anyone other than the intended recipient is not a waiver of any attorney-client, physician-patient or other privilege.

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two post-doc positions at the University of Bristol
by Jeffrey Bowers Dec. 9, 2019

Dec. 9, 2019

Please find links two RA (postdoc) positions to join the ERC project "Generalisation in Mind and Machine" at University of Bristol, UK. Also, here is a link to our lab page: https://mindandmachine.blogs.bristol.ac.uk/ Feel free to email me if you have any questions, Jeff https://www.jobs.ac.uk/job/BXD841/senior-research-associate https://www.jobs.ac.uk/job/BXF540/erc-research-associate Jeffrey Bowers School of Experimental Psychology University of Bristol Personal website: https://jeffbowers.blogs.bristol.ac.uk/ ERC lab website: https://mindandmachine.blogs.bristol.ac.uk/

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Recruitment of postdoctoral researchers and PhD students in computational brain science, Yonsei University College of Medicine
by Jiyoung Kang Dec. 9, 2019

Dec. 9, 2019

Dear all, It is our pleasure to announce an exciting opportunity for post-doc (or any other research) positions at Center for Systems and Translational Brain Science, Yonsei University, Republic of Korea (P.I. Professor Hae-Jeong Park). We develop computational methods to explore brain dynamics at various levels (from neuron to behavior), and seek for highly motivated candidates who find interest in computational neuroscience. The center specializes in the following domains: - Computational modeling based on dynamic causal modelling of the neural circuit observed in vitro and in vivo animal and human data (CaI, VSDI, LFP, M/EEG, BOLD). - Computational and systems neuroscience for the network controllability - Computational modeling of human behaviors We have neuroimaging facility of 3T fMRI, PET, EEG-fMRI, MEG, TMS+(navigation). Our research team is composed of multidisciplinary researchers from biophysics, biomedical engineering and cognitive science with strong clinical support. For details, please see the following web link: http://neuroimage.yonsei.ac.kr. If you have any questions, please contact Dr. Jiyoung Kang (jykang(a)yuhs.ac) Best regards Jiyoung Kang Center for Systems and Translational Brain Science Department of Nuclear Medicine, Radiology, Psychiatry, Department of Cognitive Science, Yonsei University College of Medicine, Seoul, Korea

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PhD Opening on large-scale dynamics of functional networks and information routing (@Aix-Marseille University)
by BATTAGLIA Demian Dec. 9, 2019

Dec. 9, 2019

We are recruiting one PhD fellow at the Institute for Systems Neuroscience at Aix-Marseille University. The student will work within Dr. Demian Battaglia’s group (theoretical neuroscientist), in strict interaction with other researchers at Aix-Marseille University (Andrea Brovelli, systems and cognitive neuroscientist; Alain Barrat, complex networks physicist). The project will delve with the analysis of multi-frequency dynamic brain networks in large-scale electrophysiological recordings. Brain regions interact between them in a highly dynamic manner even to perform very simple tasks, preventing too simplistic attempts of description. Flexibly changing patterns of information exchange and integration can be tracked using novel information theoretical and time-series analyses tools and generating directed multi-layer temporal networks representations of the data. In the framework of this project, a variety of different large-scale electrophysiological datasets (from rodents to non-human primates and humans), will be characterized based on complex network analyses tools that, initially forged in statistical physics, have not yet been adapted to be compliant with neural datasets, although they provide a natural language to describe the complex “life” of cell assemblies and transiently integrated coalitions of brain regions. The PhD fellow will characterize how spatio-spectro-temporal network patterns correlate or predict behavior and cognitive performance (e.g. in working memory or spatial navigation tasks) and, potentially, how these patterns are altered in specific animal pathology models (AD, ALS…). Network analyses of empirical data may be complemented by the design of connectome-based computational models of multi-scale oscillations, to reverse engineer physiological mechanisms (e.g. alterations of excitability) that may underpin generalized functional connectivity changes, in control or pathological conditions. This project is one of the “ESR” (Early Stage Researcher) positions opening within the Marie Skłodowska-Curie Innovative Training Network (ITN) project “i-Conn” funded by the European Commission, under their H2020 program. Such prestige program offers ideal conditions to the successful candidate such as: a salary well superior to the national average of ~1.9k euros monthly (plus family allowance when applies), net after taxes, with full social security coverage; and generous grant money for training and traveling to conferences. Through the ITN project activities, the PhD fellow will have the opportunity to come in contact with leading research groups in the UK, Germany, Czech Republic, Austria and Cyprus adopting network science techniques in a wide variety of disciplines, including neuroscience, but also socio-economics, geography, astronomy, etc. At Aix-Marseille University, the PhD fellow will integrate the second largest neuroscience community in France in a dynamic university with emphasis on interdisciplinary approaches. The PhD fellow will profit of the high-level training opportunities provided by the local “NeuroSchool” (https://neuro-marseille.org/en) an excellence PhD program in clinical and integrative neuroscience, as well as by convergence institutes as the Turing Center for Living Systems (http://centuri-livingsystems.org) In addition, Marseille is a vibrant multi-cultural city located in the beautiful natural and cultural context of Southern France, at a few hours only by direct high-speed train from European cities as Paris, Barcelona, Brussels or Frankfurt. We seek for candidates with computational neuroscience, physics or computer science/machine learning background (ideally but not necessarily). The most important prerequisite is the willingness and skill to explore large-scale datasets. Previous experience in programming, computational modeling or network analyses is a plus. The working and training language is English. IMPORTANT! some strict eligibility requirements apply to be eligible as an Early Stage Researcher funded by Marie Skłodowska-Curie program: 1) The applicant should have — at the date of recruitment — less than 4 years of a research career, and not have a doctoral degree. The 4 years are measured from the date when they obtained the degree which would formally entitle them to embark on a PhD, either in the country where the degree was obtained or in the country where the PhD is provided. 2) Trans-national mobility: The applicant — at the date of recruitment— should not have resided in the country where the research training takes place for more than 12 months in the 3 years immediately prior to recruitment, and not have carried out their main activity (work ,studies, etc.) in that country. For refugees under the Geneva Convention (1951 Refugee Convention and the 1967 Protocol), the refugee procedure (i.e. before refugee status is conferred) will not be counted as ‘period of residence/activity in the country of the beneficiary’. To register your interest in applying for this position please, and to ask for any further information, please contact demian.battaglia(a)univ-amu.fr. To apply for this position, we require a copy of your CV, degree transcripts, motivation letter and the names and/or recommendation letters of 2 referees. Please include your master thesis as well and any publication you authored (included manuscripts at preprint or sufficiently advanced draft stages).

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Research Associate in the Open Source Brain project, University College London
by Gleeson, Padraig Dec. 9, 2019

Dec. 9, 2019

(Apologies for cross postings) The Silver lab (http://silverlab.org) at University College London is looking to hire a postdoc/research associate to work on a project to extend the functionality of the Open Source Brain platform (http://www.opensourcebrain.org, Gleeson et al. Neuron 2019) to support the sharing of standardised experimental neuroscience data alongside neuronal models. This will involve building web-based infrastructure and the curation and standardisation of neuroscience models (in NeuroML format) and data (in Neurodata Without Borders format). This will facilitate collaborative model development and model reuse by the community as well as enable interactive display and analysis of models and neuroscience data through the browser. A PhD in neuroscience, physics, computer science or a related field is required, as well as experience in computational neuroscience, neuroinformatics, or development of analysis pipelines for electrophysiology and imaging data. A strong foundation in computer programming, with strong competencies in data structures, algorithms and software design is essential, along with demonstrable knowledge of UNIX/Linux, experience of web development technologies and Python and/or JavaScript programming experience. The successful applicant will have the opportunity to fully participate in the academic activities related to this initiative including contributing to research and attending scientific conferences. Deadline for applications is 3rd Jan 2020. The post is funded for 2 years in the first instance. Full details can be found here<https://atsv7.wcn.co.uk/search_engine/jobs.cgi?owner=5041179&ownertype=fair…>. For informal enquiries, please contact p.gleeson(a)ucl.ac.uk<mailto:p.gleeson@ucl.ac.uk> ----------------------------------------------------- Padraig Gleeson Room 321, Anatomy Building Department of Neuroscience, Physiology& Pharmacology University College London Gower Street London WC1E 6BT United Kingdom +44 207 679 3214 p.gleeson(a)ucl.ac.uk<mailto:p.gleeson@ucl.ac.uk> -----------------------------------------------------

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Workshop on Modelling Consciousness
by Xerxes D. Arsiwalla Dec. 9, 2019

Dec. 9, 2019

Dear Computational Neuroscience Community, We would like to announce a workshop on formal approaches to consciousness studies: https://modelling-consciousness.org/ This workshop brings together researchers who have a deep interest in questions related to the scientific study of consciousness as well as background in formal research topics in order to discuss mathematical questions in the scientific study of consciousness and formal models of the mind-matter relation. The workshop takes place in a mountain cabin in the Austrian alps in Dorfgastein from March 21st to 28th, 2020. Unlike usual workshops and conferences, the focus is not placed upon presentation of recent results, but on creating an atmosphere that stimulates discussion of open questions and new ideas concerning models of consciousness. The workshop is aimed at researchers of any age who are interested in the problems discussed in contemporary consciousness studies. A background in mathematics, physics or other formal disciplines of sciences is appreciated. The deadline for applications is January 31st, 2020. Application details can be found on our website given above. Best wishes on behalf of the workshop organizing committee, Xerxes D. Arsiwalla (IBEC & Universitat Pompeu Fabra) Ian Durham (Saint Anselm College) Johannes Kleiner Giovanni Rabuffo (University of Aix-Marseille) Joanna Szczotka (University of Sussex & Jagiellonian University) Sean Tull (Cambridge Quantum Computing)

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PhD position in Computational and Mathematical Neuroscience: Drug Discovery
by Serafim Rodrigues Dec. 8, 2019

Dec. 8, 2019

*This position encourages students in Engineering, Mathematics, Physics (or Biophysics) or Computer Science to apply.* We are seeking students that are highly motivated to pursue a PhD project that interfaces several fields, including Neuroscience, Computer Science, Biophysics with the aim to screen new drugs against Alzheimer’s Disease. The project will employ advanced methods in computer science (e.g. machine learning, molecular simulations) and other advanced methods from mathematics and biophysics to develop drugs with high therapeutic efficacy against identified pathways in Alzheimer’s patients. The project will be developed at BCAM (Basque Centre for Applied Mathematics) in Bilbao in collaboration with several centres in France, Canada and Singapore. Candidate’s requirements: - Should have completed an MSc. - The following background knowledge are desirable - Programming. - Mathematics. - Biophysics. Interested students, please contact srodrigues(a)bcamath.org

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Fwd: PhD and postdoctoral positions, University of Utah
by Alla Borisyuk Dec. 6, 2019

Dec. 6, 2019

Postdoctoral and PhD student positions are available at the University of Utah (Salt Lake City, USA) in the Computational Neuroscience group of Dr. Alla Borisyuk. Dr Borisyuk is affiliated with both Department of Mathematics and the Neuroscience program. Depending on the background of the trainee the placement might be possible in either program. Current projects include: - A mutiscale study of the role of astrocytes in neural networks; - Elucidating the odor coding and connectivity in mammalian and insect olfactory systems. All projects are in collaboration with local experimental neuroscience labs. We have dynamic, active, student-centered and supportive environment, with a multitude of opportunities for trainees to get involved in. Outside of the academics - the outdoor recreational opportunities (National parks, skiing, hiking, climbing) all around us in Utah are unparalleled. Salt Lake City is the center of a metropolitan area with a population of approximately one million residents, has extensive arts and cultural activities, and has a major international airport with a Delta Airlines hub and direct flights to most U.S. cities and direct international flights to Paris, London, Amsterdam, and Mexico City. The area has received international recognition for its new light rail system, foodie culture, downtown renewal, and increasing diversity. For project and position details and other inquiries please contact Alla Borisyuk: borisyuk(a)math.utah.edu Screening of candidates is ongoing, do not delay with your application!

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Post-doctoral Researcher - Statistical machine learning of neural time-series data and mechanisms of network coordination
by Kirst, Christoph Dec. 6, 2019

Dec. 6, 2019

Dear computational neuroscience community, The Kirst lab at UCSF<https://neurograd.ucsf.edu/people/christoph-kirst-phd-ms-bs> and the Bouchard lab at LBNL/UC Berkeley<https://bouchardlab.lbl.gov/> are looking for a joint post-doctoral researcher to work at the interface of dynamical systems, statistical machine learning, and neural time-series data. The goal is to better understand mechanisms underlying flexible network coordination in the brain. This position will focus on developing and applying methods to analyze neurophysiological signals from diverse brain areas.The post-doc will advance the state of the art in analysis methods to characterize brain dynamics and understand distributed computations in diverse brains areas. State-space modeling approaches will be integrated with emerging unsupervised learning and supervised inference procedures. This position will include a strong collaboration with both basic and clinical neuroscience labs across UCSF, UC Berkeley, and LBNL. The position is located at the University of California, San Francisco (UCSF) and LawrenceBerkeley National Laboratory (LBNL), and is part of a broader collaborative effort between UCSF, LBNL, and UCB. This Bay Area collaboration combines UCSF's strong clinical and experimental neuroscience experience with in vivo cortical electrophysiology, UCB's expertise in theoretical neuroscience, statistical learning and data analysis, and LBNL's supercomputing and applied mathematics together with electronics and microfabrication.Successful applicants will have access to the full range of facilities andexpertise uniquely allowed by this collaboration. The position has significant flexibility and the lab is committed to the professional development of the members, making it valuable preparation for people who are interested in academic, industrial or entrepreneurial careers. The position has no mandatory teaching or administrative duties, but the successful candidate will take an active role in mentoring students and further developing the research program. Excellent (written and oral) communication skills in English are required. The start date is flexible but ideally would be in June of 2020. Compensation will be commensurate with relevant experience. UCSF has competitive benefits and is an equal opportunity employer. UCSF is located in the Bay Area, which is one of the fastest-growing neurobiology-neurotechnology centers in the United States. The Bay Area offers a wide range of opportunities for recreation, culture, and easy access to domestic and international transportation. Applicants should have aPh.D. (or equivalent degree) in a computational oriented field (e.g., physics, computer science, electrical engineering, data science, etc.,) and/or a track record of advanced data statistical analysis of neural time-series data. Applicants must be able to work in a collaborative, multi-disciplinary environment and exhibit good communication skills. Experience with scientific programing languages (e.g., C/C++,Python, Matlab) is also required. To apply, please submit a CV and three letters of reference to: christoph.kirst(a)ucsf.edu and kebouchard(a)lbl.gov Yours sincerely, Christoph Kirst and Kristofer Bouchard

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Ph.D. positions in Math Biology and Computational Neuroscience at NJIT
by Victor Matveev Dec. 6, 2019

Dec. 6, 2019

Dear all, The Department of Mathematical Sciences at New Jersey Institute of Technology (NJIT) is inviting candidates to apply to one of our doctoral program tracks: (1) Applied Mathematics or (2) Applied Probability & Statistics. The Department's research focus spans Mathematical Biology and Computational Neuroscience, Scientific Computing, Fluid Dynamics, Materials Science, Wave Propagation, Applied Analysis, Applied Probability & Statistics, including Biostatistics and Data Science. Teaching and research assistantships are available, and include a tuition waiver and a competitive stipend. Application target date is December 15, 2019 but ongoing review will continue until all available positions are filled. To apply, please visit our homepage: https://www.njit.edu/graduatestudies/department-mathematical-sciences/ For more information, please email us (math(a)njit.edu, CC to:misieg@njit.edu, matveev(a)njit.edu) PhD Program advertisement flyer is available at http://web.njit.edu/~matveev/NJIT_DMS_PhD_flyer.pdf Sincerely, -- Admissions Committee, Department of Mathematical Sciences, NJIT -- _____________________________________________ Victor Matveev, Professor Applied Math, Biophysics, Neuroscience Department of Mathematical Sciences Graduate Faculty, Dept of Biological Sciences New Jersey Institute of Technology Newark, NJ 07102-1982 Office: Cullimore Hall 616 E-mail: matveev(a)njit.edu http://web.njit.edu/~matveev/

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Groningen Spring School on Cognitive Modeling: March 30 to April 3, 2020
by Jelmer Borst Dec. 5, 2019

Dec. 5, 2019

Fifth Groningen Spring School on Cognitive Modeling – ACT-R, Nengo, PRIMs, error-driven learning, and dynamical systems. – Date: March 30 to April 3, 2020 Location: Groningen, the Netherlands Fee: € 250 (late fee after February 15 will be € 300) More information and registration: www.cognitive-modeling.com/springschool <http://www.cognitive-modeling.com/springschool> We are happy to announce the fifth Groningen Spring School on Cognitive Modeling (March 30 to April 3, 2020). This year, the Spring School will again cover four different modeling paradigms: ACT-R, Nengo, PRIMs, and error-driven learning. It thereby offers a unique opportunity to learn the relative strengths and weaknesses of these approaches. Moreover, this year we are offering a lecture series on dynamical systems, which should be interesting for anyone looking into modeling cognitive dynamics at some level of abstraction. We recommend this lecture series as an excellent combination with Nengo, for those interested in neuromorphic computing. The first day will provide an introduction to all five topics. From day two, spring school students will be asked to commit to one topic, for which they will attend lectures as well as tutorials. In addition, students can sign up for a second topic, for which they will attend lectures only. All students are invited to join a series of plenary research talks on the different paradigms. On the first day, spring school students are asked to introduce themselves and their research interests in a poster session. Registration is now open. For more information and registration, please see the website: www.cognitive-modeling.com/springschool <http://www.cognitive-modeling.com/springschool> Please feel free to forward the information to anyone who might be interested in the Spring School. We are looking forward to welcoming you in Groningen, The Spring School team ______________ ACT-R Teachers: Jelmer Borst, Maarten van der Velde, Stephen Jones, & Katja Mehlhorn (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. 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: https://www.ai.rug.nl/~niels/prims/index.html <https://www.ai.rug.nl/~niels/prims/index.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. Error-driven learning Teachers: Jacolien van Rij and Dorothée Hoppe (University of Groningen) Error-driven learning (also called discrimination learning) allows to simulate the time course of learning. It is based on the Rescorla-Wagner model (Rescorla & Wagner, 1972) for animal cognition, which assumes that learning is driven by expectation error, instead of behaviorist association (Rescorla, 1988). The equations formulated by Rescorla and Wagner have been used to investigate different aspects of cognition, including language acquisition (e.g., Hsu, Chater, and Vitányi, 2011; St. Clair, Monaghan, and Ramscar, 2009), second language learning (Ellis, 2006), and reading of complex words (Baayen et al, 2011). Although error-driven learning can be applied for all domains in cognitive science, in this course we will focus on how it could be used for modeling language processing and language learning. Dynamical Systems: a Navigation Guide Teacher: Herbert Jaeger (University of Groningen) This lecture-series gives a broad overview over the zillions of formal models and methods invented by mathematicians and physicists for describing “dynamical systems”. Here is a list of covered items: Finite-state automata with and without input, deterministic and non-deterministic, probabilistic), hidden Markov models and partially observable Markov decision processes, cellular automata, dynamical Bayesian networks, iterated function systems, ordinary differential equations, stochastic differential equations, delay differential equations, partial differential equations, (neural) field equations, Takens’ theorem, the engineering view on “signals”, describing sequential data by grammars, Chomsky hierarchy, exponential and power-law long-range interactions, attractors, structural stability, bifurcations, phase transitions, topological dynamics, nonautonomous attractor concepts. In the lectures, I try to work out the underlying connecting lines between the “dots” listed above. -- Jelmer Borst Assistant Professor Model-Based & Computational Neuroscience University of Groningen, Bernoulli Institute, dept. of Artificial Intelligence http://www.jelmerborst.nl/

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Postdoctoral positions, Brown University (Truccolo Lab)
by Wilson Truccolo Dec. 3, 2019

Dec. 3, 2019

Applications for postdoctoral positions in Computational Neuroscience are invited for the laboratory of Dr. Wilson Truccolo in the Department of Neuroscience at Brown University, Providence, RI, USA. The positions are for the development of theoretical and data-driven stochastic models of neuronal network dynamics, including applications to collective dynamics in normal neocortex, and propagation and control of epileptic seizures. Neural data consist of recordings of ensembles of single-neurons and high-density local field potentials obtained via multiple intracortical microelectrode arrays implanted in human and nonhuman primates. The ideal candidate will have a strong background in computational/theoretical neuroscience, and modeling of stochastic neural dynamics. Related publications can be found on the Truccolo lab website ( http://www.truccololab.com/) Inquiries should be addressed to Dr. Truccolo (wilson_truccolo(a)brown.edu) Applications including a CV, statement of research interests, and the names and full contact details of three referees should be sent to wilson_truccolo(a)brown.edu. -- Wilson Truccolo, Ph.D. Associate Professor of Neuroscience Department of Neuroscience & Carney Institute for Brain Science, Brown University Lab website: http://www.truccololab.com/

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