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PhD positions at the Max Planck Research School for Neural Circuits, Frankfurt am Main, Germany

by Jochen Triesch

8th Call for applications: International Max Planck Research School for Neural Circuits, Frankfurt am Main, Germany The International Max Planck Research School (IMPRS) for Neural Circuits was established in 2011 and offers up to ten fully-paid positions every year for talented students holding a relevant Master´s or Bachelor´s as their highest degree to perform research resulting in a PhD. The program is taught in English. The common focus of the the International Max Planck Research School (IMPRS) for Neural Circuits will be the understanding of neural circuits (from the simple to the large and complex), at all scales required to achieve this understanding. This ambitious objective will require analyses at the molecular, cellular, multi-cellular, network and behavioral levels, with the full understanding that macroscopic phenomena (spatial patterns, dynamics) can be scale-dependent, and that reductionism is not always sufficient as a method. Research areas are perception, connectomics, theoretical neuroscience, synaptic plasticity, brain dynamics, neural circuits, behavior and systems neuroscience. In the IMPRS for Neural Circuits we offer a multidisciplinary program to excellent doctoral students with backgrounds in neuroscience, mathematics, physics, computer science, (bio) chemistry, biology and medicine as well as research experience in the participating institutions of the Frankfurt Neuroscience community. Students will participate in a tailor-made educational program including research rotations and neuroscience courses but also in trainings in transferable skills as well as retreats, conferences and summer schools and lecture series. We welcome excellent students to apply to the program. Till December 1, 2017, it will be possible to apply for a position starting in the Fall of 2018. You can apply via our electronic registration system. After the deadline, the Faculty members will select around 25 students to participate in the interview symposium in Frankfurt, taking place in February 5-7, 2018. Shortly after the symposium, the students will receive a letter with an offer or rejection. More information, including Frequently Asked Questions, can be found on our website www.imprs.brain.mpg.de. -- Prof. Dr. Jochen Triesch Johanna Quandt Research Professor Frankfurt Institute for Advanced Studies http://fias.uni-frankfurt.de/~triesch/ Tel: +49 (0)69 798-47531 Fax: +49 (0)69 798-47611

Oct. 10, 2017

2 postdoc positions in Geometric Methods for Deep and Reinforcement Learning at RIST

by Luigi Malagò

=========================================================== *Subject*: 2 postdoc positions in Machine Learning (1 year, renewable up to 3 years) *Institution*: RIST - Romanian Institute of Science and Technology, Cluj-Napoca *Keywords*: Deep Learning, Reinforcement Learning, Stochastic Optimization, Optimization over Manifolds, Information Geometry, Riemannian Geometry *Application deadline*: 20 October 2017 (applicants are encouraged to apply earlier) *Salary*: around 2190 euro net *Official announcement*: http://rist.ro/en/details/news/postdoc- positions-in-deep-learning-and-machine-learning.html =========================================================== Dear colleagues, the Romanian Institute of Science and Technology (RIST) has an opening for 2 postdoc positions, in the context of the DeepRiemann project “Riemannian Optimization Methods for Deep Learning”, funded by European structural funds through the Competitiveness Operational Program (POC 2014-2020). The appointments will be for 1 year, with possible extensions up to 3 years. The DeepRiemann project aims at the design and analysis of novel training algorithms for Neural Networks in Deep Learning, by applying notions of Riemannian optimization and differential geometry. The task of the training a Neural Network is studied by employing tools from Optimization over Manifolds and Information Geometry, by casting the learning process to an optimization problem defined over a statistical manifold, i.e., a set of probability distributions. The project is highly interdisciplinary, with competences spanning from Machine Learning to Optimization, Deep Learning, Statistics, and Differential Geometry. The objectives of the project are multiple and include both theoretical and applied research, together with industrial activities oriented to transfer knowledge, from the institute to a startup or spin-off of the research group. The positions will be part of the new Machine Learning and Optimization group http://luigimalago.it/group.html, which performs research at the intersection of Machine Learning, Stochastic Optimization, Deep Learning, and Optimization over Manifolds, from the unifying perspective of Information Geometry. The group is one of two newly-formed groups in Machine Learning at RIST, where about 20 new postdoctoral research associates and research software developers will be hired by 2018. The official job announcement can be seen here: http://rist.ro/en/details/news/postdoc-positions-in- deep-learning-and-machine-learning.html Informal inquiries can be sent to Dr. Luigi Malagò <malago(a)rist.ro>, principal investigator of the DeepRiemann project. Application deadline: 20 October 2017 (applicants are encouraged to apply earlier) best regards, Luigi Malagò

Oct. 9, 2017

Doctoral studies in Computational/Theoretical Neuroscience at NYU

by Eero Simoncelli

New York University is home to a thriving interdisciplinary community of researchers using computational and theoretical approaches in neuroscience. We are interested in PhD candidates with strong quantitative training (e.g., physics, mathematics, engineering) coupled with a clear interest in brain sciences. A list of relevant faculty, sorted by their primary departmental affiliation, is provided below. Doctoral programs are flexible, allowing students to pursue research across departmental boundaries. Nevertheless, admissions are handled separately by each department, and students interested in pursuing graduate studies should submit an application to the program that best fits their goals and interests. Neural Science (CNS) (deadline: 1 December) [http://www.cns.nyu.edu/doctoral/] * AndrÃ© A. Fenton - Molecular, neural, behavioral, and computationalaspects of memory. * Paul W. Glimcher - Decision-making in humans and animals. Neuroeconomics. * Roozbeh Kiani - Vision and decision-making. * Wei Ji Ma (also in Psychology) - Perception, working memory, and decision-making. * Tony Movshon - Vision and visual development. * Bijan Pesaran - Neuronal dynamics and decision-making. * Alex Reyes - Functional interactions of neurons in a network. * John Rinzel (also in Mathematics) - Biophysical mechanisms and theory of neural computation. * Cristina Savin (also in CDS) - Computational models of memory, machine learning. * Robert Shapley - Visual physiology and perception. * Eero Simoncelli - Computational vision and audition, image processing. * Xiao-Jing Wang - Computational neuroscience, decision-making and working memory, neural circuits. Neuroscience and Physiology program, School of Medicine (deadline: 1 December) [http://neuroscience.med.nyu.edu/training-programs/graduate-program-neurosci…] * Gyorgy Buzsaki - Rhythms in neural networks. * Dmitri Chklovskii (also in the Simons Foundation) - Neural computation and connectomics. * Dmitry Rinberg - Sensory information processing in the behaving animal. * Mario Svirsky - Auditory neural prostheses; experimental/computational studies of speech production/perception. Psychology, Cognition & Perception program (deadline: 1 December) [http://www.psych.nyu.edu/programs/cp/] * Todd Gureckis - Memory, learning, and decision processes. * David Heeger (also in CNS) - fMRI, computational neuroscience, vision, attention. * Brenden Lake (also in CDS) - Computational modeling of cognition. * Michael Landy - Computational approaches to vision. * Laurence Maloney - Mathematical approaches to psychology and neuroscience. * Gary Marcus - Origins of the human mind. * Denis Pelli - Visual object recognition. * Jonathan Winawer - Visual perception and memory. Center for Data Science (CDS) (deadline: 18 December) [https://cds.nyu.edu/academics/phd-in-data-science/] * Joan Bruna (also in Computer Science) - Machine learning, signal/image processing. * Kyungyun Cho (also in Computer Science) - Machine learning, natural language processing. * Carlos Fernandez-Granda (also in Mathematics) - Optimization methods for medical imaging, neuroscience, computer vision. Mathematics (deadline: 18 December) [http://math.nyu.edu/degree/phd/] * David Cai - Nonlinear stochastic behavior in physical and biological systems. * Aaditya Rangan - Computational neurobiology, numerical analysis. * Michael Shelley - Modeling and large-scale computation, computational visual neuroscience. * Daniel Tranchina - Information processing in the retina. * Lai-Sang Young - Dynamical systems, statistical physics, computational modeling and theoretical neuroscience. Physics (deadline: 18 December) [http://physics.as.nyu.edu/page/graduate] * Marc Gershow - Perception, decision-making, and learning in neural circuits. Computer Science (deadline: 12 December) [http://www.cs.nyu.edu/home/phd/] * Davi Geiger - Computational vision and learning. * Yann LeCun - Machine learning, hierarchical visual processing, robotics. Economics (deadline: 18 December) [http://as.nyu.edu/econ/degree-programs/phd.html] * Andrew Caplin - Economic theory, neurobiology of decision. * Andrew Schotter - Experimental economics, game theory, neurobiology of decision.

Oct. 9, 2017

Workshop announcement: The Probabilistic Brain, March 2018

by Ulrik Beierholm

Dear Colleagues We are very pleased to invite you to an exciting 2-day workshop on *probabilistic approaches to learning, perception, and action* in the historic city of Durham in the North-East of England: see the workshop website <https://sites.google.com/view/tpbw2018/>. The workshop will take place on *March 23rd-24th 2018*, and registration is *open now*. Speakers: Vikranth Rao Bejjanki, Hamilton College ● Nick Chater, University of Warwick ● József Fiser, Central European University ● Aldo Faisal, Imperial College London ● Samuel Gershman, Harvard University ● Janneke Jehee, Donders Institute ● Rebecca Lawson, UCL / Cambridge ● Laurence T Maloney, NYU ● Pascal Mamassian, Ecole Normale Supérieure ● Christopher Summerfield, University of Oxford ● Jane Wang, Google DeepMind The workshop is supported by the Experimental Psychology Society and Durham University. For full info on the workshop format and topics, our location and travel, and Registration, please see the workshop website <https://sites.google.com/view/tpbw2018/>. Hope to see you there, The organisers, Marko Nardini ● Ulrik Beierholm ● Maria Olkkonen (Durham University) ● Tessa Dekker (UCL) ● Laurence T Maloney (NYU)

Oct. 9, 2017

[jobs] Assistant and Associate Professor positions in Bio- and Neural Robotics in Odense

by Poramate Manoonpong

The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, invites applications for Assistant or Associate Professor with research focus in Neural Robotics, Bio-inspired or Biorobotics, available from January 2018 and based in Odense. The positions are based in the Embodied Systems for Robotics and Learning (ESRL) unit and will complement the unit's existing research activities: - biorobotics; - neural models of control for embodied robots; - bio-inspired / neural learning mechanisms; - cross-modal and multi-modal sensory interpretation; - development of bio-inspired and embodied robotic hardware; - bio-inspired collective behaviour in robot groups; - embedded electronics design and research; - development and use of robotic educational tools; - morphological computation and the role of embodiment. Duties comprise research and teaching, student project supervision and acquisition of external funding. If you have a Ph.D. in a computing, mathematical, computational neuroscience or robotics-related discipline and a research track record including strong interdisciplinary work in one or more of the topics above, send us an application: for more detail and application form see [1]. The closing date is the 27th of October, 2017. For more information about these positions, please contact Professor John Hallam <john(a)mmmi.sdu.dk<mailto:john@mmmi.sdu.dk>>. [1] https://ssl1.peoplexs.com/Peoplexs22/CandidatesPortalNoLogin/Vacancy.cfm?Po…

Oct. 8, 2017

M-GATE: 15 PhD positions available in leading labs across Europe on the physiology and circuits of memory [WITH FIXED LINK; APOLOGIES]

by Francesco Battaglia

M-GATE is a network of 8 leading European institutions funded by a Marie Sklodowska-Curie Action of the European Commission, for 15 PhD students Healthy brain physiology, as well as diseases of memory circuits such as epilepsy and Alzheimer will be studied. Detailed circuit analysis approaches in animals will be combined with work on human subjects and theoretical approaches. New experimental and analytical technologies will be developed and deployed, also in collaboration with industrial partners. Positions are available with the following PIs: - Dr. Francesco Battaglia (network coordinator)/Dr. Lisa Genzel Donders Institute, Radboud University Nijmegen, The Netherlands; - Dr. Clifford Kentros; NTNU, Trondheim, Norway - Dr. Hugo Spiers; University College London - Dr. Christophe Bernard Université d’Aix/Marseille, France - Dr. Pim Drinkenburg; Janssen Pharmaceutica BV, Beerse, Belgium - Dr. Alessandro Treves; SISSA International School for Advanced Studies, Trieste, Italy - Dr. Nachum Ulanovsky; Weizmann Institute, Rehovot, Israel - Dr. Misha Tsodyks; Weizmann Institute, Rehovot Israel - Dr. Rosa Cossart; Institut de neurobiologie de la Mediterranée, Marseille France We will offer to the students a training program including events at all participating institutions, including theoretical courses, experimental methodologies and transferable skills. The details of the network and all projects are available at our website http://www.mgate.eu <http://www.mgate.eu/> requirements and application procedures vary by PhD project, as described in the website. Please contact the project PIs (addresses available on the website) for questions on the project. General inquiries may be directed to the network coordinators at info(a)mgate.eu <mailto:info@mgate.eu>. In general, we will give full consideration to applications received by Nov., 30 2017.

Oct. 6, 2017

Two Post-doctoral positions available in Rome

by Aldo Genovesio

Two ERC funded Post-doctoral positions in Primate Neurophysiology are available in the laboratory of Aldo Genovesio at the Medical School of the Sapienza University of Rome, Italy. Both positions are of one year renewable for at least other two years. We are looking for candidates with a PhD in the field of neuroscience, statistics, biomedical engineering, computer science, or related fields with a background in training animals, recording and analysis of neuronal data or in computational neuroscience. Experience with data analysis, programming (C/C++ and Matlab), and a quantitative approach are important. One position is for a candidate with previous experience in training animals, recording and analysis of neuronal data. The other position is for a candidate with a background in computational neuroscience or computer science. He is expected to analyze the activity of large sets of single cells of simultaneously recorded neurons and local fields and to develop computational models of the data. The ERC project investigates using multi-site electrode arrays the neural activity underlying prediction, categorization, and monitoring of self and others goals actions in the prefrontal cortex during social interaction with a focus on the Frontal Pole cortex, a prefrontal area only recently investigated at the single cell level in our past studies. Inquiries should be addressed to genovesiolab(a)gmail.com. All interested candidates should send a CV, a brief description of research interests for a preliminary evaluation and names and contact of 2 references to genovesiolab(a)gmail.com. The start date is flexible. The salary will be determined based on the experience. Prof. Aldo Genovesio Department of Physiology and Pharmacology Sapienza University of Roma Piazzale Aldo Moro 5; 00185 Roma E-mail: aldo.genovesio(a)uniroma1.it

Oct. 6, 2017

AoN Brainhack Warsaw 2017 - call for participants - early bird registration till 15.10

by Daniel Borek

*AoN Brainhack Warsaw 2017* *November 17-19, 2017* *University of Warsaw, Warsaw, Poland* *— The early bird registration extended to 15th October2017 — * On the weekend of *17-19th November 2017*, the first edition of AoN Brainhack Warsaw will take place. During this three-day event dedicated to students and PhD students, we will work in teams on* neuroscience-related projects*. The aim of the event is to meet new, enthusiastic researchers, make new friendships in academia, learn, share the knowledge on data mining and brain research, but also promote open science in the spirit of the whole Brainhack community ( <https://gigascience.biomedcentral.com/articles/10.1186/s13742-016-0121-x>Craddock et al., 2016) <https://gigascience.biomedcentral.com/articles/10.1186/s13742-016-0121-x>. Attendees of various backgrounds are welcome to join! Below you could see list of projects which will be realised during our three day event: 1. Functional connectivity research: can we find a common ground? <https://brainhackwarsaw.github.io/#connectivity> 2. Detecting trypophobia triggers <https://brainhackwarsaw.github.io/#connectivity%23trypophobia> 3. Development of video game for studying joint action dynamics <https://brainhackwarsaw.github.io/#connectivity%23game> 4. Training a human-like movie evaluation system based on the semantic features of the storylines <https://brainhackwarsaw.github.io/#connectivity%23movies> 5. Hypothesis-driven white matter tractography from T1-weighted MRI images <https://brainhackwarsaw.github.io/#connectivity%23whitematter> 6. One channel EEG sleep staging with open source and open hardware NeuroOn sleep mask <https://brainhackwarsaw.github.io/#connectivity%23neuroon> 7. Building a brain-ageing biomarker using machine learning <https://brainhackwarsaw.github.io/#connectivity%23ageingbiomarker> 8. Building and using the “FlyPi”: the 3D-printed Neurobiology Lab <https://brainhackwarsaw.github.io/#connectivity%23flypi> *‘Early bird’* registration for project participants,* closes on 15th October 2017*. The applications will be reviewed and the notification of acceptance will be sent to the applicants until 20th October2017. We welcome everyone at the AoN Brainhack Warsaw 2017 event. We would like to prepare the equipment and the clusters properly before the event, therefore we are asking the participants to register in advance and choose the projects of their preference. We will do our best to make sure that everyone can take part in the project they like, and that the projects are well prepared for the participants. In any case, we welcome everyone to come, watch the event and help us at the first Brainhack in the history of AoN conference! A registration fee of 25EUR (or 100PLN) will be requested upon acceptance. The registration fee will be spent on the catering during the event. To register please visit our page and learn more about the Brainhack Warsaw! https://brainhackwarsaw.github.io/ <https://brainhackwarsaw.github.io/> We looking forward to see you in Warsaw! *The AoN Brainhack Warsaw 2017 team*

Oct. 6, 2017

M-GATE: 15 PhD positions available in leading labs across Europe on the physiology and circuits of memory

by Francesco Battaglia

M-GATE is a network of 8 leading European institutions funded by a Marie Sklodowska-Curie Action of the European Commission. We offer to 15 promising young researchers the opportunity to get a world-class doctoral training and do cutting edge research on memory circuits. Healthy brain physiology, as well as diseases of memory circuits such as epilepsy and Alzheimer will be studied. Detailed circuit analysis approaches in animals will be combined with work on human subjects and theoretical approaches. New experimental and analytical technologies will be developed and deployed, also in collaboration with industrial partners. Positions are available with the following PIs: - Dr. Francesco Battaglia (network coordinator) Donders Institute, Radboud University Nijmegen, The Netherlands; - Dr. Rosa Cossart; Institut de neurobiologie de la Mediterranée, Marseille France - Dr. Hugo Spiers; University College London - Dr. Christophe Bernard Université d’Aix/Marseille, France - Dr. Pim Drinkenburg; Janssen Pharmaceutica BV, Beerse, Belgium - Dr. Clifford Kentros; NTNU, Trondheim, Norway - Dr. Alessandro Treves; SISSA International School for Advanced Studies, Trieste, Italy - Dr. Nachum Ulanovsky; Weizmann Institute, Rehovot, Israel - Dr. Misha Tsodyks; Weizmann Institute, Rehovot Israel We will offer to the students a training program including events at all participating institutions, including theoretical courses, experimental methodologies and transferable skills. The details of the network and all projects are available at our website http://www.mgate.eu <http://www.maget.eu/>. Job requirements and application procedures vary by PhD project, as described in the website. Please contact the project PIs (addresses available on the website) for questions on the project. General inquiries may be directed to the network coordinators at info(a)mgate.eu <mailto:info@mgate.eu>. In general, we will give full consideration to applications received by Nov., 30 2017.

Oct. 6, 2017

Open position: Expert in machine learning and high-performance computing

by Daniel Zysman

The Department of Brain and Cognitive Sciences seeks an expert in machine learning and high-performance computing to collaborate on cutting edge research on neuroscience, perception, cognition, and artificial intelligence. The department is a world leader in computational approaches to brain science, and is home to state-of-the-art computing resources as well as the Center for Brains, Minds and Machines, a multi-institutional NSF Science and Technology Center dedicated to the study of intelligence. Salary will be competitive with industry. To apply: https://careers.peopleclick.com/careerscp/client_mit/external/jobDetails.do… <https://careers.peopleclick.com/careerscp/client_mit/external/jobDetails.do…> For more information about our department: https://bcs.mit.edu/ <https://bcs.mit.edu/> Job Description: PROGRAMMER/SOFTWARE DEVELOPMENT ENGINEER/COMPUTATIONAL AND MACHINE LEARNING SPECIALIST, Brain and Cognitive Sciences, to help tackle challenging problems in high-performance computing methods and systems, machine learning, management of large datasets, and artificial intelligence. Responsibilities include helping researchers translate computational algorithms into efficiently functioning (especially parallelized and GPU optimized) code; assisting with installation and implementation of third-party tools; staying up-to-date with cutting-edge computational techniques; providing guidance for storage and management of large data sets; developing and maintaining online courses for computing resources, running in-person tutorials on specific software packages/tools, and helping transition users to new computing tools; providing educational support and training to users of the departmental computing cluster; and monitoring cluster usage and resolving problems. Job Requirements: Bachelor’s degree (advanced degree preferred) in a scientific field or computer science; at least four years’ experience in scientific high-performance (cluster) computing; familiarity with Slurm and Lustre; broad computational background with knowledge of Unix, HPC algorithms, GPU computing, programming models, debuggers, and performance tools; software development experience, especially Python and MATLAB, but also R, Lua, JavaScript, etc.; knowledge of high-level APIs for HPC computing; expertise installing and maintaining third-party software in an HPC environment and with container technology, especially in the context of computational reproducibility; familiarity with mathematical algorithms for high-performance computing, use or design of HPC profiling or optimization tools, and deep neural networks; ability to work effectively with scientists and engineers; initiative, tact, and judgment in developing solutions for users; excellent interpersonal skills and ability to communicate effectively, orally, in writing, and via live presentations; demonstrated ability to assume leadership roles, grasp complex problems, and develop solutions; and extensive background in high-performance computing. MIT is an equal employment opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, sex, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, ancestry, or national or ethnic origin.

Oct. 5, 2017