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Fully funded PhD position at the IIT - neural coding - open now
by Stefano Panzeri Dec. 16, 2019

Dec. 16, 2019

Fully funded PhD Position at IIT - Computational approaches to study the neural code for somatosensation. I am are seeking candidates for a fully funded PhD position at the Italian Institute of Technology’s in my lab ( https://www.iit.it/people/stefano-panzeri ). IIT collaborates with SISSA and finances the positions at the PhD course at SISSA from the EU Marie Curie Training Network Neutouch (www.neutouch.eu) Although formally to be enrolled at SISSA, the successful candidate will conduct research in my laboratory at the IIT headquarters in Genova, Italy. The PhD project can focus on any of the research topics about somatosensory neural information processing that are of interest to the candidate, to my lab and to the Training Network (www.neutouch.eu) including: developing mathematical analysis methods and neural network models for studying neural population coding of somatosensory signals, for studying the neural bases of sensory perception and decision making, and for designing somatosensory neuro-inspired artificial sensors. The ideal candidate should have a strong background in numerate sciences, and have a strong propensity for interdisciplinary research. No extensive previous experience in neuroscience is required. However, a keen interest in understanding the brain is essential. The position is open immediately and will close when a suitable candidate is found. Interested candidates are invited to contact me informally by email (stefano.panzeri(a)iit.it) as soon as possible, by attaching their CV and briefly explaining their interest in this position, to initiate discussions about potential PhD projects of interest. For recent representative publications from my lab, please see: van Vugt B, et al, (2018) *Science* 360, 537-542 Zaldivar, D., et al, (2018) *Current Biology* 28: 224-235 Runyan C. A., et al (2017) *Nature*: 548: 92-96 Pica G. et al, *NIPS* (2017) Panzeri, S, et al (2017) *Neuron* 93: 491-507 Safaai, H. et al (2015) *Proc. Natl. Acad. Sci. USA* 112(41): 12834–12839 Fasoli, D. et al (2016) *PLoS Computational Biology*, 12(8): e1004992. Panzeri, S., et al (2015) *Trends in Cognitive Sciences* 19: 162-172 Einevoll, G., et al (2013) *Nature Reviews Neuroscience*, 14, 770-785 Yours truly, Stefano Panzeri stefano.panzeri(a)iit.it

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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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