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PhD student position in Decision Making, Sorbonne Universite, Paris (B. Girard, O. Davidenko)

by Benoît Girard

Fully funded PhD: Cognitive and computational neurosciences studies to decipher how the social context affects individual food decisions Institution: Sorbonne Université (Paris, France) Disciplins: Computational Neurosciences, Behavioral Neuroscience, Brain Imaging Hosting laboratory: ISIR, Institut des Systèmes Intelligents et de Robotique (SU/CNRS) Thesis Supervisors: Benoît Girard (ISIR, UPMC/CNRS) , supervisor Olga Davidenko (INRA/AgroParisTech/UPSay PNCA), co-supervisor Starting date: fall 2018 Key Words: Reinforcement learning, Human eating behavior, Brain imaging Scientific environment of the project: Excessive intake of sugars and salt are linked to deleterious consequences on Human health. Current strategies to design and favor healthier options have limited effects due to their poor acceptability. SHIFT proposes a multidisciplinary approach, combining life, social and computer sciences to understand the determinants, mechanisms, and levers to modulate the acceptability of a meal option. This project will address precise alimentary situations where margins of improvement with respect to salt and sugar reduction are possible, ie. acceptability of (i) water or low energy beverages in substitution of sodas and (ii) sugar- or salt-reduced options at the end of main meals. Interdisciplinary research activities will be conducted at the populational, contextual and individual scales to decipher criteria driving the acceptability foods. SHIFT gathers 5 academic partners: The “Physiologie de la Nutrition et du Comportement Alimentaire” lab (UMR PNCA; INRA-AgroParisTech-Université Paris-Saclay, project leader), the “Institut des Systèmes Intelligents et de Robotique” (ISIR, Sorbonne Université-CNRS-INSERM), the “Mathématiques et Informatique Appliquées” lab (UMR MIA; INRA-AgroParisTech-Université Paris-Saclay), the “Alimentation et Sciences Sociales” lab (ALISS; INRA), the School of Psychology of the University of Birmingham and an industrial partner: Danone Nutricia Research (Global Nutrition Department) Work Programme: In the selection of foods as in many other decision processes, individuals tend to conform to social norms (i.e. a collectively-established acceptable behaviour). For instance, when eating with others, if individuals are offered to choose between two foods, they will take the decision that conforms to the choices made by the others guests. In some cases, for instance when all guests need to make a choice within a very short time lapse, there might be an uncertainty on this social norm. Before making their decision, individuals infer the appropriate choice from the available information of the choices made by others and after taking their decision, subjects judge the appropriateness of their own decision the basis of the overall choices of commensals. The acceptability of a food option is modulated by whether or not it is imitated by the commensals. The aim of this thesis is to explore how the social context affects individual decisions. The student will study the question from the point of view of the individual: what are the contributions of various types of social modulation (imitation, conformity to a social norm) to food choices? Fundamental to every decision is the brain’s ability to internally evaluate subjective values. The theoretical framework of this thesis, the “value-based decision-making” (Pessiglione et al., 2006, Johnson & Ratcliff, 2014), suggests that, although from an external point of view, the outcome of a decision can be reduced to a binary phenomenon (acceptance or rejection) the underlying mental computation of the value is represented as a continuous function. Our working hypotheses are that the aforementioned social modulations to food choices can be integrated in an individual-centric modeling approach of decision-making (as has been shown in simpler contexts by Burke et al. (2010)), that the influences of these various types of modulations can be disentangled, so as to help identifying the possibly specific neural substrates. In this thesis, we will design a behavioural task dedicated to investigate the different causes of social modulations, and we will then explore which brain circuits are involved, using fMRI. We will use the theoretical tools of value-based decision-making to model the mechanisms by which social modulations affect decision. This will allow us to derive time series of internal variables of the model as regressors to refine the analysis of fMRI data. The student will work to establish a fully specified model of a decision task incorporating mathematical formalizations of the social modulations. The model will be based on the so-called model-free reinforcement learning algorithms (Sutton & Barto, 1998), to which additional value update modalities will be added in order to take into account the influence of commensals. Burke, C.J., Tobler, P.N., Baddeley, M., and Schultz, W. (2010). Neural mechanisms of observational learning. PNAS 201003111. Johnson, E.J., and Ratcliff, R. (2014). Chapter 3 - Computational and Process Models of Decision Making in Psychology and Behavioral Economics. In Neuroeconomics (Second Edition), P.W. Glimcher, and E. Fehr, eds. (San Diego: Academic Press), pp. 35–47. Pessiglione, M., Seymour, B., Flandin, G., Dolan, R.J., and Frith, C.D. (2006). Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans. Nature 442, 1042–1045. Sutton, R. S., & Barto, A. G. (1998). Reinforcement learning: An introduction. MIT press. To apply Applicants should send a CV, letter of motivation (max 2 pages), and references via e-mail to benoit.girard(a)sorbonne-universite.fr and olga.davidenko(a)agroparistech.fr, with [SHIFT] in the subject of the mail. Review of applicants will begin immediately, and will continue until the position is filled. The earliest start date is November 2018. -- Benoît Girard, ISIR, UPMC/CNRS Pyramide T55/65, CC 173 4 place Jussieu, 75252 Paris Cedex http://people.isir.upmc.fr/girard/ Submit your replications to ReScience: https://rescience.github.io/

Sept. 18, 2018

1-year position for an engineer to work in Parkinson, in the frontiers of imaging and machine learning (Bilbao, Spain)

by Jesus Cortes

We are looking for an Engineer with skills in computer vision, programming and machine learning to collaborate in the research project entitled: "Study of the retina and the visual pathway by neuroimaging in genetic and aggressive idiopathic synucleinopathies as a model to identify phenotypes and prognostic biomarkers in idiopathic Parkinson's disease" (Principal Investigator: Iñigo Gabilondo, MD, PhD) led by the Neurodegenerative Diseases Group. The data to analyse are multimodal and longitudinal, with a sample size bigger than N=100 and consisting in retina OCT, neuroimaging (structural, functional, tensor tensor and spectroscopy), neuropsychology and clinical scales. The engineer also will work in close collaboration with the Computational Neuroimaging Group, led by Prof. Jesus M Cortes. For further information about the groups, visit: https://biocrucesbizkaia.org/web/biocruces/bc5.01and https://biocrucesbizkaia.org/bc5.08 Requirements: - Bachelor of Engineering - Good academic marks (average score higher than 7 over 10) - Experience in computer vision, programming j(Matlab, Python and / or R), machine learning and other artificial intelligence techniques - Experience with the magnetic resonance imaging analysis packages SPM, FSL and Freesurfer - Advanced English level (demonstrable with official degree - C1) - Intention to develop a PhD in Biomedicine. The contract is for 1 year, but exists the possibility to extend it to finalize the PhD Working conditions: - Duration: 12 months (extendable) - Full working day (100%) (1592 annual hours) - Estimated annual gross salary: 23,004 euros per year - Expected start date: As soon as possible Interested candidates send 2 reference letters and updated CV to igabilon(a)gmail.com and/orjesus.m.cortes(a)gmail.com

Sept. 18, 2018

Postdoc position: Computational modelling & primate neurophysiology of multi-stable perception

by jobraun

Postdoc position: Computational modelling & primate neurophysiology of multi-stable perception Applications are invited for a postdoctoral fellowship with Jochen Braun in Magdeburg, Germany, and in collaboration with Kristine Krug in Oxford, UK. The research will examine the neural basis of multi-stable perception, by comparing single- and multi-unit recordings from non-human primates with computational models of hierarchical neural dynamics. Candidates must have a degree in physics (or similar), a Ph.D. in a relevant field (e.g., neuroscience, physiology, physics), and strong quantitative and writing skills. Experience with single- or multi-unit recordings from behaving vertebrates is highly desirable. The initial appointment will be for two years with the possibility of renewal. Cognitive Biology is part of a large and vibrant neuroscience community (www.neuroscience-magdeburg.de/research/professor-jazz) Magdeburg is a lively university town with a beautiful historical centre around the river Elbe and with convenient transport links to Leipzig and Berlin. To apply, please send a PDF file with a CV, a statement of research interests, and names of two references to jochen.braun(a)ovgu.de. Prof. Jochen Braun, Ph.D. Cognitive Biology Group Otto-von-Guericke University Magdeburg, Germany www.kobi-ovgu.de Prof. Kristine Krug, D.Phil. Dept. Physiology Anatomy & Genetics University of Oxford Oxford, UK www.dpag.ox.ac.uk/research/krug-group

Sept. 17, 2018

PhD positions in machine learning/neuroimaging available at Charité - University Medicine Berlin

by Stefan Haufe

Dear all, PhD positions for highly motivated graduate students are available in the ERC funded research group of Stefan Haufe at the Berlin Center for Advanced Neuroimaging (BCAN) of the Charité - University Medicine Berlin, Germany. The group will develop machine learning and signal processing methods for the analysis of non-invasive brain signals (primarily EEG/MEG) and apply these methods to patient data with the aim of better understanding neurological diseases such as Parkinson's and Alzheimer’s disease. Appointments can be made for up to four years starting from January 2019 or later. Remuneration is based on the German pay scale TVL E13 (65% working time). Candidates are required to hold a very good MSc or equivalent degree in a relevant field and are expected to demonstrate extraordinary skills in at least one of the following core areas A: Mathematics and quantitative data analysis/modeling (machine learning, signal processing, statistics, numerical optimization, etc.). Experience with efficient algorithms and large data sets. B: Neuroscience (psychology, cognitive science). Knowledge of general research practices and experience in the design, execution, and statistical evaluation of studies. C: Computer science. Experience in software development, programming in Matlab/Python/C, system administration. Further required are excellent communication skills in English (written and spoken), and a genuine interest in interdisciplinary work. Prior experience with functional neuroimaging data is a plus. Successful candidates will work at Charité's historic Mitte campus in the center of Berlin, and will be embedded in a stimulating research environment. Applications should be sent by email to stefan.haufe(a)charite.de quoting the reference number DM.143.18b. In addition to cv and cover letter, applicants are encouraged to include further documentation such as references, transcripts, copies of bachelor/master theses/research papers (in English or German), links to github repositories, etc. . All documents should be contained in a single pdf.

Sept. 16, 2018

Postdoctoral Position in Visual & Computational Neuroscience

by Burge, Johannes

A NIH-funded postdoctoral position is available in the lab of Johannes Burge at the University of Pennsylvania (http://burgelab.psych.upenn.edu) We use natural images, statistical learning tools, ideal observer analysis, and behavioral experiments to gain a precise understanding of the processes that support perception. We have ongoing projects across a range of topics in vision and computational neuroscience, but we tend to focus on projects directly or indirectly related to motion and depth perception. My lab is affiliated with the Computational Neuroscience Initiative at Penn, a community of top researchers working on an array of problems in sensation, perception, and cognition. Strong mathematical and programming skills are necessary, as well as strong communication skills and a record of research productivity. Familiarity designing and running psychophysical experiments via Matlab is also required. A solid background in computer graphics and knowledge of C/C++ and object oriented programming is also desirable. The lab has a high refresh-rate VPixx ProPixx projector, a haploscope driven by two high-resolution VPixx ViewPixx monitors, and a large suite of custom code for statistical learning and for the analysis of psychometric data. Applicants must have finished their Ph.D. in neuroscience, vision science, engineering, computer science, or related fields and have a demonstrated record of research productivity. The position is available immediately but the precise start date is flexible. Applicants should send a brief statement of interest, CV, and the names of three references to Johannes Burge (jburge(a)sas.upenn.edu<mailto:jburge@sas.upenn.edu>). Letters will be requested if your candidacy is being considered. Applications will be assessed as they arrive and the position will remain open until filled. Salary will be based on NIH post-doctoral rates and commensurate with experience. ======================== Johannes Burge, PhD Assistant Professor Department of Psychology Neuroscience Graduate Group University of Pennsylvania http://burgelab.psych.upenn.edu jburge(a)sas.upenn.edu (215) 573 6528

Sept. 15, 2018

Computer Models in 3R Research

by Peter Jedlicka

Dear colleagues, The programme and further information for the Kick-off Symposium of the 3R Centre JLU Giessen are available online at ICAR3R.de. The minisymposium covers also the topic of computer models in 3R research. You can register on the event website or at www.xing-events.com/3R-Symposium-Giessen.html. Abstracts for the 3R poster session can be submitted until 20th September at ICAR3R(a)uni-giessen.de. 1st International Symposium: New Prospects in Interdisciplinary 3R Research Date 18th/19th October 2018 Venue Aula at Justus Liebig University Gießen Registration fee is 90 Euro. Eight hours of training are granted for the event. Best regards, Peter Jedlicka -- Peter Jedlicka, MD, PhD Professorship for Computer-Based Modelling in the field of 3R Animal Protection Faculty of Medicine Justus-Liebig-University Rudolf-Buchheim-Str. 6 D-35392 Giessen Fax: ++49 (0)641 9941359 Interdisciplinary Centre for 3Rs in Animal Research (ICAR3R) Frankfurter Straße 104 35392 Gießen www.ICAR3R.de

Sept. 15, 2018

PhD position: US-German Collaboration in Computational Neuroscience

by Peter Jedlicka

Applications are invited for a 3-year PhD position in an NIH & BMBF funded US-Germany project aimed at creating biophysically realistic multi-scale computer models of TMS (transcranial magnetic stimulation)-induced changes of neuronal and synaptic properties. The position will be based at the Justus Liebig University (Giessen). This project is in collaboration with the University of Freiburg, the University of Minnesota and the Temple University (Philadelphia). The student will be using computer simulations to reproduce/predict data from electrophysiology and functional optical imaging experiments in hippocampal tissue cultures. Visits to Freiburg and to US for short-term and long-term periods of time to learn techniques and exchange information are part of the activities of this grant. The successful candidate should have a background in physics, mathematics, engineering, computational neuroscience or closely related field. Experience in scientific programming is highly desirable. The appointment will be starting in November/December 2018 or in 2019. Please submit a single pdf file including CV, list of publications, statement of research interests and names and email addresses of three references to: Prof. Dr. Peter Jedlicka; Peter.Jedlicka(a)informatik.med.uni-giessen.de The project is related to these recent publications: Lenz M, Galanis C, Müller-Dahlhaus F, Opitz A, Wierenga CJ, Szabó G, Ziemann U, Deller T, Funke K, Vlachos A (2016) Repetitive magnetic stimulation induces plasticity of inhibitory synapses. Nature Communications 7:10020 Beining M, Mongiat LA, Schwarzacher SW, Cuntz H, Jedlicka P (2017) T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells. Elife 6:e26517 Lenz M, Platschek S, Priesemann V, Becker D, Willems LM, Ziemann U, Deller T, Müller-Dahlhaus F, Jedlicka P, Vlachos A (2015) Repetitive magnetic stimulation induces plasticity of excitatory postsynapses on proximal dendrites of cultured mouse CA1 pyramidal neurons. Brain Structure & Function 220:3323–3337. P.S. If you are interested and will be attending Bernstein Conference in Berlin (27, 28 September), feel free to send me an email so that we can meet for an in-person interview. -- Peter Jedlicka, MD, PhD Professorship for Computer-Based Modelling in the field of 3R Animal Protection Faculty of Medicine Justus-Liebig-University Rudolf-Buchheim-Str. 6 D-35392 Giessen Phone: ++49 (0)69 179 238 6269 Fax: ++49 (0)641 9941359 NeuroScience Center Clinical Neuroanatomy (Anatomy I) Goethe-University Theodor-Stern-Kai 7 D-60590 Frankfurt am Main Fax: ++49 (69) 6301 6425 Email: jedlicka(a)em.uni-frankfurt.de

Sept. 14, 2018

Post-doc at FIAS - Computational Modeling of Epilepsy: Conducting Interviews at the Bernstein Conference 2018

by Peter Jedlicka

Dear Comp-Neuro community, I would like to inform you that a post-doc position will be available in 2019 in the context of Frankfurt's new Center for Personalized Translational Epilepsy Research (CePTER). The project focuses on better understanding circuit changes and neuroimmune interactions during the development of epilepsy and is jointly lead by Prof. Jochen Triesch and me. I am attending the Bernstein Conference in Berlin (September 27-28). If you are interested, contact me by email and attach your CV so that we can meet for an in-person interview. Best, Peter Jedlicka P.S. If you are not attending the Bernstein conference, you can send your applications (single pdf file including CV, list of publications, statement of research interests and names and email addresses of three references) to jedlicka(a)em.uni-frankfurt.de and triesch(a)fias.uni-frankfurt.de. The position will be based at the Frankfurt Institute for Advanced Studies (https://fias.uni-frankfurt.de/en/) Frankfurt has a vibrant Neuroscience community and the successful candidates will work closely together with experimental labs. An ideal candidate will have obtained a PhD/Master Degree in Computational Neuroscience or closely related field and have a strong interest in applying their knowledge to problems of medical relevance. Prior experience with modeling spiking neural networks or compartmental modeling is highly desirable. Experience in modeling epilepsy, neural plasticity and neuro-immune interactions is a plus. -- Peter Jedlicka, MD, PhD Professorship for Computer-Based Modelling in the field of 3R Animal Protection Faculty of Medicine Justus-Liebig-University Rudolf-Buchheim-Str. 6 D-35392 Giessen Phone: ++49 (0)69 179 238 6269 Fax: ++49 (0)641 9941359 NeuroScience Center Clinical Neuroanatomy (Anatomy I) Goethe-University Theodor-Stern-Kai 7 D-60590 Frankfurt am Main Fax: ++49 (69) 6301 6425 Email: jedlicka(a)em.uni-frankfurt.de

Sept. 14, 2018

[meetings] Call for Participation : Workshop on Continual Unsupervised Sensorimotor Learning - Tokyo - September 17th

by Nguyen, Sao Mai

*Call for Participation* Workshop on Continual Unsupervised Sensorimotor Learning at IEEE ICDL-Epirob 2018 - Tokyo - September 17th Website : http://conferences.au.dk/icdl-epirob-2018-workshop/ ============================================================ *Updated list of Invited Speakers* - Jochen Triesch, Frankfurt Institute of Advanced Studies, Germany Title: Active Efficient Coding - David Ha, Google Brain Title: Generative World Models - Kathryn Kasmarik, University of New South Wales, Australian Defence Force Academy (UNSW Canberra), Australia Title: Computational Motivation for Learning, Optimisation and Decision Making *Schedule* 09:50 – 10:10 Welcome and introduction 10:10 – 10:50 *Invited talk: **David Ha* Title: Generative World Models 10:50 – 11:10 Coffee break *Inference and Representations* 11:10 – 11:30 *Where do I move my sensors? Emergence of an internal representation from the sensorimotor flow*Valentin Marcel, Sylvain Argentieri and Bruno Gas 11:30 – 11:50 *Active inference in continual learning* Pablo Lanillos *Sensorimotor Learning* 11:50 – 12:10 *Towards Biological Plausibility of Sensorimotor Learning Models: a Short Review* Silvia Pagliarini, Arthur Leblois, and Xavier Hinaut 12:10 – 12:30 *A Computational Model For Action Prediction Development* Serkan Bugur, Yukie Nagai, Erhan Oztop, and Emre Ugur *Application/Tools* 12:30 – 12:50 *Flatland: a Lightweight First-Person 2-D Environment for Reinforcement Learning* Hugo Caselles-Dupré, Louis Annabi, Oksana Hagen, Michael Garcia-Ortiz, and David Filliat 12:50 – 14:10 Lunch break 14:10 – 14:50 *Invited talk. Jochen Triesch* Title: Active Efficient Coding *Intrinsic Motivation and alike* 14:50 – 15:10 *Learning Sequences of Policies by using an Intrinsically Motivated Learner and a Task Hierarchy* Nicolas Duminy, Alexandre Manoury, Sao Mai Nguyen, Cédric Buche, and Dominique Duhaut 15:10 – 15:30 *Emergent emotion as a regulatory mechanism for a cognitive task implemented on the iCub robot* Murat Kirtay, Lorenzo Vannucci, Egidio Falotico, Cecilia Laschi, and Erhan Oztop *Application/Tools* 15:30 – 15:50 *Towards Life Long Learning: Multimodal Learning of MNIST Handwritten Digits* Eli Sheppard, Hagen Lehmann, G. Rajendran, Peter E. McKenna, Oliver Lemon, and Katrin S. Lohan 15:50 – 16:10 Coffee break 16:10 – 16:40 *Invited talk: Kathryn Kasmarik* Title: Computational Motivation for Learning, Optimisation and Decision Making 16:40 – 17:40 Discussion 17:40 – 18:00 Conclusions and farewell ============================================================ *Scope* As the algorithms for learning single tasks in restricted environments are improving, new challenges have gained relevance. They include multi-task learning, multimodal sensorimotor learning in open worlds and lifelong adaptation to injury, growth and ageing. In this workshop we will discuss the developmental processes involved in the emergence of representations of action and perception in humans and artificial agents in continual learning. These processes include action-perception cycle, active perception, continual sensory-motor learning, environmental-driven scaffolding, and intrinsic motivation. The discussion will be strongly motivated by behavioural and neural data. We hope to provide a discussion friendly environment to connect with research with similar interest regardless of their area of expertise which could include robotics, computer science, psychology, neuroscience, etc. We would also like to devise a roadmap or strategies to develop mathematical and computational models to improve robot performance and/or to attempt to unveil the underlying mechanisms that lead to continual adaptation to changing environment or embodiment and continual learning in open-ended environments. The primary list of topics covers the following (but not limited to): - Emergence of representations via continual interaction - Continual sensory-motor learning - Action-perception cycle - Active perception - Environmental-driven scaffolding - Intrinsic motivation - Neural substrates, neural circuits and neural plasticity - Human and animal behaviour experiments and models - Reinforcement learning and deep reinforcement learning for life-long learning - Multisensory robot learning - Multimodal sensorimotor learning - Affordance learning - Prediction learning *Organizers:* Nicolás Navarro-Guerrero, Aarhus University, Aarhus, Denmark Sao Mai Nguyen, IMT Atlantique, France Erhan Öztop, Özyeğin University, Turkey Junpei Zhong, National Institute of Advanced Industrial Science and Technology (AIST), Japan ============================================================ Nguyen Sao Mai nguyensmai(a)gmail.com Researcher in Cognitive Developmental Robotics http://nguyensmai.free.fr

Sept. 14, 2018

PhD student position in neural data analysis, University of Edinburgh (Arno Onken)

by Arno Onken

A fully funded PhD position is available in the group of Arno Onken at the University of Edinburgh, on the development and application of novel methods for analysing multi-modal and multi-scale neural recordings. The group collaborates closely with the experimental groups of Nathalie Rochefort (University of Edinburgh, joint EPSRC-funded project to start in March) and Shuzo Sakata (University of Strathclyde). Potential projects are interdisciplinary, bridging computational neuroscience, statistical modelling and machine learning. The successful applicant will join the Institute for Adaptive and Neural Computation (http://www.anc.ed.ac.uk/) which hosts strong research groups in the relevant fields. Applicants should have a strong quantitative background (e.g. math, statistics, computer science, physics, computational neuroscience), good programming skills and a keen interest in interdisciplinary research. A background in neuroscience is desirable, but not essential. The position is available to UK/EU applicants. Other excellent applicants may be eligible for international postgraduate scholarships - please get in touch. The start date is flexible. Interested applicants should submit their application to the Institute for Adaptive and Neural Computation: https://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&ed… For further information, please contact Arno Onken (aonken(a)inf.ed.ac.uk) -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

Sept. 14, 2018