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AMAM 2019, Adaptive motion in animals and machines, Aug 19-23 2019, EPFL, Lausanne, Switzerland
by Auke Ijspeert Sept. 20, 2018

Sept. 20, 2018

AMAM 2019, Adaptive Motion in Animals and Machines, Aug 19-23 2019, EPFL, Lausanne, Switzerland https://amam2019.epfl.ch/ Mark the date and first call for abstracts Investigating how animals and humans excel at adaptive movements can help engineers to improve the adaptive capabilities of robots. In return, robots can serve as scientific tools to explore the basic principles of biological systems, in particular the neuromechanical mechanisms underlying their fascinating motor abilities. AMAM 2019 is the 9th international symposium dedicated to stimulate fruitful interactions among biologists and engineers interested in adaptive motion. It aims at bringing together researchers in robotics, biomechanics, neuroscience, sports science, and other fields related to motor behavior in biological and artificial systems. Previous symposia were held in Montreal, Canada (2000); Kyoto, Japan (2003); Ilmenau, Germany (2005); Cleveland, USA (2008); Awaji, Japan (2011); Darmstadt, Germany (2013); Cambridge, USA (2015); and Sapporo, Japan (2017). Abstract contributions are invited from all areas pertaining to adaptive motion in animals and machines. Accepted abstracts are presented in either oral or poster sessions based on assessed suitability by the program committee. Invited talks and some selected speakers will be presented in oral sessions in a single track. We also encourage participants to contribute hardware demonstrations, as part of the ‘Robot Zoo’@AMAM2019. Important dates: * Jan 18th, 2019 Opening of the extended abstract submission * March 8th, 2019 Deadline of extended abstracts submission * April 12th, 2019 Notification of acceptance for extended abstracts * May 31st, 2019 Deadline of submission for Robot Zoo (Robot Demos) * August 19-23, 2019 Conference Program Committee: * Hitoshi Aonuma, Hokkaido University, Japan * Jordan Boyle, Leeds University, UK * Monica Daley, Royal Veterinary College, UK * Koh Hosoda, Osaka University, Japan * Fumiya Iida, Cambridge, UK * Auke Ijspeert, EPFL, Lausanne, Switzerland * Akio Ishiguro, Tohoku University, Japan * Masato Ishikawa, Osaka University, Japan * Takeshi Kano, Tohoku University, Japan * Sangbae Kim, MIT, USA * Jun Nishii, Yamaguchi University, Japan * Dai Owaki, Tohoku University, Japan * Andre Seyfarth, TU Darmstadt, Germany * Emily Standen, University of Ottawa, Canada * Dagmar Sternad, Northeastern University, USA * Barry Trimmer, Tufts University, USA * Eric Tytell, Tufts University, USA * Hartmut Witte, TU Ilmenau, Germany General Chair: * Auke Ijspeert, EPFL, Lausanne, Switzerland -- ----------------------------------------------------------------- Prof Auke Jan Ijspeert Biorobotics Laboratory EPFL-STI-IBI-BIOROB, ME D1 1226, Station 9 EPFL, Ecole Polytechnique Fédérale de Lausanne CH 1015 Lausanne, Switzerland Office: ME D1 1226 Tel: +41 21 693 2658 Fax: +41 21 693 3705 www:http://biorob.epfl.ch Email:Auke.Ijspeert@epfl.ch -----------------------------------------------------------------

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Postdoctoral researchers - multimodal fMRI
by Alessandro Gozzi Sept. 20, 2018

Sept. 20, 2018

The Functional Neuroimaging Laboratory, at Istituto Italiano di Tecnologia, Rovereto, Italy, is seeking postdoctoral researchers interested in studying the neural basis of connectivity disruption in brain disorders. Our research, funded by the European Research Council (ERC - project "DisConn"), is aimed at identifying the general neural and cellular principles governing the assembly of spontaneous neural activity, and its breakdown in developmental disorders. We address these questions at the level of identified cell types by combining cutting-edge functional MRI methods with neural manipulations in the living mouse. This research sits at the intersection of computational neuroscience, neurobiology and neuroimaging. The successful candidate will have a PhD in neuroscience, biotechnology, computer science, physics, or equivalent. Training in experimental neuroscience is desirable, but not mandatory. The IIT center in Rovereto (http://cncs.iit.it/) is actively expanding its infrastructure and space for system-level neuroscience research. The center is inserted both in the vibrant community of the IIT (http://www.iit.it) and of the CIMeC center of the University of Trento (http://www.cimec.unitn.it) which specializes in cognitive neuroscience. Rovereto is conveniently located near Trento and Verona, two of the most important "Citta d'Arte" in Italy. The Trentino area is a region of Northern Italy nestled in the Dolomite Mountains, offering spectacular natural beauty, vibrant culture and exceptional quality of life. Please send your application (full CV, research statement, and names of 2 referees) by email to mailto:alessandro.gozzi@iit.it. Applications will be examined until the positions are filled. https://www.iit.it/careers/openings/opening/846-postdoctoral-positions-in-n… Alessandro Gozzi, PhD Senior Scientist, Group Leadel Functional Neuroimaging Laboratory Istituto Italiano di Tecnologia Center for Neuroscience and Cognitive Systems @ UNITN Corso Bettini 31, 38068 Rovereto, Italy Tel: +39 0464 808 701

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PhD studentship in "Computational modelling of cryopreservation"
by roman bauer Sept. 19, 2018

Sept. 19, 2018

*We are seeking a PhD student with excellent programming skills and an interest in biology. The studentship will be based at Newcastle University (UK) and benefit from collaboration with CERN.* Interested in computers as well as biology? Then this project might be what you are looking for! The aim is to use novel software and high-performance computers to model how biological tissue, including neural tissue, behaves during freezing and thawing. Cryopreservation of biological tissue is in its infancy. State-of-the-art freezing and thawing techniques lead to tissue damage in anything larger than 1-3 mm3. Above-freezing storage times of human organs range from approximately 3 to 24 hours - depending on organ - before becoming unviable. This lack of preservation capacity results in 2/3 of donor hearts and 4/5 of lungs being rejected for transplant for logistical reasons. By improving our knowledge of how cryogenic processing affects biological/neural tissue, new methodologies for cryogenic processing will be studied. To this end, you will work together with experts in the field, learn to incorporate the results in detailed 3D computer simulations, and produce novel hypotheses that will generate better methodologies. For informal enquiries please contact Dr Roman Bauer (roman.bauer(a)ncl.ac.uk ). Further details on this PhD studentship and how to apply can be found via this link: *https://www.findaphd.com/search/ProjectDetails.aspx?PJID=100152 <https://www.findaphd.com/search/ProjectDetails.aspx?PJID=100152>*

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Lecturer/Senior Lecturer in Computational Neuroscience - Ref 80046
by Chris Miall Sept. 19, 2018

Sept. 19, 2018

Lecturer/Senior Lecturer in Computational Neuroscience - Ref. 80046 The School of Psychology at the University of Birmingham wishes to strengthen our School with the appointment of a Lecturer/Senior Lecturer with specific expertise in computational modelling. The School is continuing to recruit as a result of outstanding performance in the 2014 Research Excellence Framework (REF) and major investment provided to the School by the University. The School The School of Psychology at the University of Birmingham (http://www.birmingham.ac.uk/schools/psychology/index.aspx) is one of the largest and most successful in the UK, currently ranked in the top 5 Schools in the country (REF 2014). The University of Birmingham is an equal opportunities employer and welcomes applications from currently under-represented groups. The School of Psychology has a Bronze Athena SWAN award and strives to maintain a flexible and supportive environment that enables its staff to flourish. Role purpose We welcome applicants whose research expertise will complement and extend any of our existing four Research Themes: Perception, Cognition, and Action; Mental Health and Wellbeing; Language, Interaction, and Social Cognition; Memory and Attention. One strategic objective for the School is to build on the strength of our Centre for Computational Neuroscience and Cognitive Robotics, and so we particularly welcome applicants with strength in computational science approaches, including machine learning, Bayesian modelling, and computational models of perception, categorisation and attention. We will consider a joint appointment with the School of Computer Science, which has staff whose research expertise complement and extend those of Psychology. Closing Date: 28 Oct 2018 A full job description is available in PDF format here: http://www.download.bham.ac.uk/vacancies/jd/80046.pdf -------------------------------------------------------------------------------- Professor R.C. Miall Hills Building Tel +44 121 414 2867 School of Psychology, Fax +44 121 414 4897 University of Birmingham, Mobile: 07709 586997 Edgbaston, Email: r.c.miall(a)bham.ac.uk<mailto:r.c.miall@bham.ac.uk> Birmingham B15 2TT UK Web: http://prism.bham.ac.uk ---------------------------------------------------------------------------------

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NEURON Course at SFN 2018
by Ted Carnevale Sept. 18, 2018

Sept. 18, 2018

The registration deadline for the NEURON course at the SFN 2018 meeting is Friday, October 12--less than a month from now. The online registration form is at https://neuron.yale.edu/neuron/static/courses/sd2018/sd2018.html This course is suitable for applicants with a wide range of interests and expertise, ranging from experimentalists who have never done any computational modeling, to advanced modelers who want to know the latest tips for using NEURON with Python. Topics that will be covered include: --using Python and NEURON's graphical tools to build and work with models of individual cells --using the Import3d tool to import detailed anatomical neuronal data from NeuroLucida and SWC files --using the CellBuilder to specify the biophysical properties of model cells with detailed anatomical structure --expanding NEURON's library of ion channels and other biophysical mechanisms --analyzing models with the Model View tool --building network models --speeding up simulations on parallel hardware --Ted

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PhD student position in Decision Making, Sorbonne Universite, Paris (B. Girard, O. Davidenko)
by Benoît Girard Sept. 18, 2018

Sept. 18, 2018

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/

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1-year position for an engineer to work in Parkinson, in the frontiers of imaging and machine learning (Bilbao, Spain)
by Jesus Cortes Sept. 18, 2018

Sept. 18, 2018

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

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Postdoc position: Computational modelling & primate neurophysiology of multi-stable perception
by jobraun Sept. 17, 2018

Sept. 17, 2018

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

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PhD positions in machine learning/neuroimaging available at Charité - University Medicine Berlin
by Stefan Haufe Sept. 16, 2018

Sept. 16, 2018

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.

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Postdoctoral Position in Visual & Computational Neuroscience
by Burge, Johannes Sept. 15, 2018

Sept. 15, 2018

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

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