- Comp-neuro - lists.cnsorg.org

Postdoc position on Biological Deep Learning

by Walter Senn

Dear all One postdoc position devoted to learning in deep cortical networks is available in the Computational Neuroscience labs at the University of Bern, Switzerland. Our research is focussed on biologically realistic models of spatio-temporal processing in recurrent cortical networks and their relation to reinforcement learning, Bayesian computing, and neuromorphic implementations. The position is focussed on formalizing the dendritic processing of cortical pyramidal neurons, in particular on combining top-down and bottom-up information streams within pyramidal neurons, and in integrating these neurons in deep networks. The position is part of a collaboration with Profs Fritjof Helmchen and Giacomo Indiveri (UniZH / ETHZ) supported by the Swiss National Science Foundation and is available from January 1st, 2021, for 2 years (extendable). We offer a stimulating environment with three research groups in theoretical and computational neuroscience, along with experimental neuroscience at the same Department of Physiology (physio.unibe.ch/gruppen.aspx <file:///Users/walter/Documents/Walter_Physio/admin/ownPositionAnnouncments/HBP_PosAnnouncments2020/physio.unibe.ch/gruppen.aspx>), as well as close collaborations with other labs in neuroscience, artificial intelligence and neuromorphic engineering. Ideal candidates should have a strong background in computational neuroscience, machine learning, applied mathematics and/or physics. Please send your CV, publication list, letter of motivation and contact information for at least two references to Walter Senn (walter.senn(a)unibe.ch <mailto:walter.senn@unibe.ch>) and Mihai Petrovici (mihai.petrovici(a)unibe.ch <mailto:mihai.petrovici@unibe.ch>), with cc to Virginie Sabado (virginie.sabado(a)unibe.ch <mailto:virginie.sabado@unibe.ch>). The first evaluation round will begin on November 8, 2020. The positions will remain open until filled. With best regards, Mihai Petrovici and Walter Senn

Oct. 15, 2020

postdoc on computational modelling of perceptual inference and psychophysics (Hyafil lab, CRM, Barcelona)

by Alexandre Hyafil

A postdoc position is available under the supervision of Alexandre Hyafil in the group of Computational Neuroscience at the *Center for Research in Mathematics (CRM),* Barcelona, Spain ( http://www.crm.cat/en/Research/ResearchGroups/Neuroscience/Pages/default.as…) The project will combine modelling and psychophysics (possibly neuroimaging) to study the mechanisms of propagation of belief in human perception. The candidate will benefit from the stimulating environment of Barcelona area in Theoretical and Systems Neuroscience and will have the opportunity of enjoying a lively city (should the pandemics permit). Our lab forms part of a larger interacting network of neuroscience labs in Barcelona ( http://www.barccsyn.org) Candidates should have a PhD in computational cognitive neuroscience or a related field. Prior experience with psychophysics, neuroimaging, machine learning and/or computational modelling will be valued. Financial support is provided by the Spanish Ministry of Science. Initial appointment: two years. *APPLICATION:* Send a curriculum and motivation letter with a list of two contacts for recommendation letter to alexandre.hyafil(a)gmail.com. Informal enquiries are welcome. *DEADLINE:* until the position is filled *STARTING DATE:* anytime before summer 2021

Oct. 15, 2020

PhD/Postdoc position in Tübingen, Deep nets + human neurophysiology data

by Jakob Macke

Dear colleagues, We have a position for a Ph.D. Student or Postdoctoral Researcher (m/f/d, E13 TV-L) in `Deep learning for studying population codes in the human brain’, starting as soon as possible. The initial fixed-term contract will be for 3 years with possible extension. Details at https://uni-tuebingen.de/en/196976. How do neural circuits in the human brain recognize objects, persons and actions from complex visual stimuli? To address these questions, we will develop deep convolutional neural networks for modelling how neurons in high-level human brain areas respond to complex visual information. We will make use of a unique dataset of neurophysiological recordings of single-unit activity and field potentials recorded from the medial temporal lobe of epilepsy patients. Our tools will open up avenues for a range of new investigations in cognitive and clinical neuroscience, and may inspire new artificial vision systems. The position is part of the BMBF-funded project DeepHumanVision in collaboration with the `Dynamic Vision and Learning’ Group at TU Munich (Prof. Dr. Laura Leal-Taixé) and the Cognitive and Clinical Neurophysiology Group at University Hospital Bonn (Prof. Dr. Dr. Mormann). Our group develop computational methods that help scientists interpret empirical data, with a focus on basic and clinical neuroscience research. We want to understand how neuronal networks in the brain process sensory information and control intelligent behaviour, and use this knowledge to develop methods for the diagnosis and therapy of neuronal dysfunction. We aim to work in an interdisciplinary, collaborative and supportive work environment which emphasizes diversity and inclusion. Tübingen has an internationally renowned research community in artificial intelligence, machine learning and computational neuroscience, including the Cyber Valley Initiative, the Tübingen AI Center, the Excellence Cluster Machine Learning, and the new MSc Program Machine Learning. We are situated in the AI Research Building, in close proximity to the Max Planck Institutes for Intelligent Systems and Biological Cybernetics, and participate in the two International Max Planck Research Schools (IMPRS) `Intelligent Systems’ and `Mechanisms of Mental Function and Dysfunction’. The position is open to candidates who have a PhD or Master’s in in a quantitative discipline (e.g. computer science, maths, statistics, physics, electrical engineering, computational neuroscience), a genuine interest in interdisciplinary work at the interface of machine learning and neuroscience, and strong programming skills (ideally Python/PyTorch). Prior experience in deep learning, and/or in analysing neurophysiological data with statistical methods is advantageous. The University seeks to raise the number of women in research and teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference. The employment will be carried out by the central administration of the University of Tübingen. PhD applicants are also expected to apply to the IMPRS `Intelligent Systems’ https://imprs.is.mpg.de, Deadline also November 2. Please submit your application materials to mls-sekretariat(a)inf.uni-tuebingen.de, with subject `Application: Postdoc/PhD DeepHumanVision‘. Please include a CV, a brief statement of research interests, contact details of two referees and a work sample - anything that is genuinely your own work, e.g. a thesis, computer code, a research manuscript, an essay, or a publication. For postdoc applicants, we expect relevant prior publications. Application deadline: November 02, 2020. Best, Jakob Macke Prof. Dr. Jakob Macke Chair of Machine Learning in Science Excellence Cluster `Machine Learning: New Perspectives for Science’ Department of Computer Science University of Tübingen Adjunct Senior Research Scientist, Department of Empirical Inference Max Planck Institute for Intelligent Systems Tübingen Jakob.Macke(a)uni-tuebingen.de Office: Franziska Weiler, mls-sekretariat(a)inf.uni-tuebingen.de www.mackelab.org/tuebingen

Oct. 15, 2020

Positions in Probabilistic Data Science / Machine Learning Lab, Oldenburg University, Germany

by Jörg Lücke

Dear list, The Machine Learning Lab at the University of Oldenburg, Germany, is seeking to fill the position of a Researcher in Probabilistic Data Science. We look for somebody who has already obtained a PhD degree or is close to obtaining one. The only definitive source of information is here: https://uol.de/stellen/?stelle=67593 The application deadline is Oct 20 but we very likely also accept applications until the end of next week. We are seeking somebody with knowledge on probabilistic generative modeling. Best wishes, Jörg Lücke -- Jörg Lücke (PhD) Professor and Head of the Machine Learning Lab Department of Medical Physics and Acoustics School of Medicine and Health Sciences University of Oldenburg 26111 Oldenburg Germany www.uol.de/ml

Oct. 14, 2020

COSYNE 2021: Abstract submission is now open

by Tomas Hromadka

==================================================== Computational and Systems Neuroscience 2021 (Cosyne) MAIN MEETING ONLINE 24 - 26 February 2021 www.cosyne.org ==================================================== IMPORTANT DATES Abstract submission is now open Abstract submission deadline: 12 November 2020 ---------------------------------------------------- MEETING ANNOUNCEMENT ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. Cosyne 2021 will take place online, February 24 - 26, 2021. Please note that the dates have changed slightly from the initial announcement. The goal of this year’s meeting is to promote early stage investigators. Therefore, there are no invited talks from established researchers. The format will include featured contributed talks chosen from submitted abstracts, and interactive poster-like presentations (short recorded presentation + live interactions). More details to follow. All abstract submissions will be reviewed as in previous years, but reviewing will be fully double blind. The deadline for Abstract submission will be November 12, 2020. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, and computation with spiking networks. When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. ---------------------------------------------------- COSYNE 2021 TUTORIAL ---------------------------------------------------- Cosyne 2021 main meeting will be preceded by an online Cosyne Tutorial Session led by Kanaka Rajan (Icahn School of Medicine at Mount Sinai) on 23 February 2021. More details will be posted on www.cosyne.org. ORGANIZING COMMITTEE General & Program Chairs: Anne-Marie Oswald (U Pittsburgh) and Srdjan Ostojic (Ecole Normale Superieure Paris) Diversity Chairs: Eva Dyer (Georgia Tech, Emory) and Eric Shea-Brown (U Washington) Publicity Chair: Adam Calhoun (Princeton) Tutorial Chair: Il Memming Park (Stony Brook) Development Chair: Michael Long (NYU) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) PROGRAM COMMITTEE Athena Akrami (UCL) Demba Ba (Harvard) Omri Barak (Technion) Brice Bathellier (Paris) Yoram Burak (Hebrew University) Christine Constantinople (NYU) Saskia De Vries (Allen Institute) Victor de Lafuente (UNAM Mexico) Jan Drugowitsch (Harvard) Tatiana Engel (CSHL) Annegret Falkner (Princeton) Kevin Franks (Duke) Tim Hanks (UC Davis) Ann Hermundstad (Janelia) Andrew Leifer (Princeton) Sukbin Lim (Shanghai) Scott Linderman (Stanford) Mackenzie Mathis (EPFL Lausanne) Ida Momennejad (Microsoft) Cris Niell (U Oregon) Il Memming Park (Stony Brook) Adrien Peyrache (McGill Montreal) Kanaka Rajan (Icahn School of Medicine at Mount Sinai) Robert Rosenbaum (Notre Dame) Christina Savin (NYU) Marshal Shuler (Johns Hopkins) Daniela Vallentin (Max Planck Munich) CONTACT meeting [at] cosyne.org COSYNE MAILING LISTS Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> Mailing lists for details.

Oct. 14, 2020

Online Mentoring Job Offer

by Maryam

WE WANT YOU ! ScienceBeam, which is a designer and manufacturer of neuroscience applications and organizer of neuroscience educational courses, is looking for professional, experienced and authentic mentors from all around the world for online courses. Required fields: ➢ Neuroscience ➢ Neuro-Biofeedback ➢ EEG/ERP/QEEG ➢ Cognitive Science ➢ Programming (MATLAB, Bio-Signal processing, etc.) If you are as passionate about mentoring as you are about the above-mentioned fields, and can give a few hours per week in return for an honorarium, we would love to hear from you. Apply now and send your resumes to: workshop(a)sciencebeam.com WhatsApp No: +8613380781282

Oct. 13, 2020

Ph.D. program (with details) in Computational/Experimental Neuroscience in Tuebingen, Germany

by Zhaoping Li

(I apologize for a previous message sent without details): Join our interdisciplinary PhD program and experience a vibrant and international training environment in Neuroscience! see https://www.kyb.tuebingen.mpg.de/imprs-mmfd for more details. Application deadline 30th Nov. 2020 More details International Max Planck Research School The Mechanisms of Mental Function and Dysfunction The ‘International Max Planck Research School (IMPRS) for The Mechanisms of Mental Function and Dysfunction’ (MMFD) provides state-of-the-art training and research under the guidance of leading neuroscientists, psychologists, psychiatrists and computational scientists in Tübingen. Excellent graduates with a Bachelor´s degree will enjoy an unparalleled opportunity to start their research career in neuroscience. What´s it all about? The IMPRS is a joint project of the Max Planck Institute for Biological Cybernetics <https://www.kyb.tuebingen.mpg.de/2549/en> and the University of Tübingen <https://uni-tuebingen.de/en/>. It is embedded in the Graduate Training Centre of Neuroscience (GTC) <https://www.neuroschool-tuebingen.de> and thus benefits from more than 20 years of successful cooperation in the training of young neuroscientists. The IMPRS-MMFD offers a combined MSc/PhD program to outstanding BSc graduates. IMPRS students will not only receive an admission to one of the GTC´s regular MSc programs, but additionally a commitment of the IMPRS faculty to offer them a PhD position after their successful MSc graduation. The direct access to the IMPRS doctoral program for those students who are already holding a MSc degree and have already been admitted by the Graduate Training Centre is also possible. Prerequisite is the primarily supervision by one of the IMPRS faculty members (see: Application). Teaching and research in the IMPRS and at the GTC of Neuroscience are conducted entirely in English. The IMPRS MMFD was launched in January 2020 and is one of about sixty International Max Planck Research Schools <https://www.mpg.de/en/imprs> run by the Max Planck Society <https://www.mpg.de/en> in partnership with various universities and research institutions. IMPRS programs provide an extraordinary framework and working environment for graduate students, and they provide unique opportunities for interdisciplinary research projects.

Oct. 9, 2020

postdoc position in dynamical models of learning in working memory (Kilpatrick, CU Boulder)

by Zachary Kilpatrick

We are seeking a postdoctoral fellow to work on a BRAIN/NIMH/NIBIB funded project developing and validating neural circuit models of experience-driven computations in working memory. Our group is in the Department of Applied Mathematics at the University of Colorado Boulder, and we have affiliations with the Institute of Cognitive Science and School of Medicine. The start date would likely be in Spring or Summer 2021. The position is fully funded till September 2023, with a possible extension contingent on funding. Interested applicants should contact Zack Kilpatrick (zpkilpat(a)colorado.edu <mailto:zpkilpat@colorado.edu>), along with a CV and list of 3 or more references. The aim of this project is to understand how task-relevant experience is encoded in neuronal circuits through plasticity-driven changes to network architecture (building off ideas in Kilpatrick (2018) Sci Rep <https://www.nature.com/articles/s41598-018-25958-9>). Our mechanistic neural circuit models will be validated using data from humans (psychophysical response) and non-human primates (response + large-scale neural recordings) from the Gold (Penn), Buschman (Princeton), and Bays (Cambridge) labs. Candidates must have a strong background developing, simulating, and mathematically analyzing dynamical/mechanistic neural network models. We will build and analyze neural field models of large-scale activity using a combination of methods from stochastic processes, asymptotics, Bayesian inference, and numerical PDEs. Experience working with psychophysics and/or neural recording data is a plus but not required. Models will be fit using Bayesian parameter estimation and model comparison. Within our group, you could also work on a side project or two in decision-making, stochastic dynamics, social networks, and/or social foraging. Outside of work, the great outdoors in and around Boulder can’t be beat with over 40,000 acres of public open space, 1hr to skiing at Eldora Mtn Resort, 1hr to Rocky Mtn Natl Park, and tons of hiking and climbing. Boulder is consistently rated one of the most bike-able cities in the nation. We also have a very active local food scene with multiple restaurants receiving James Beard nominations this year. Non-stop international flights to Germany, Italy, France, Switzerland, the UK, Japan, Mexico, and Canada are a 45 minute bus ride away at Denver Airport. ---------- Zachary P Kilpatrick, PhD (he/him/his) Associate Professor University of Colorado Boulder Department of Applied Mathematics http://www.colorado.edu/amath/zpkilpat <http://www.colorado.edu/amath/zpkilpat>

Oct. 8, 2020

Postdoctoral position in Computational Neuroscience, Italian Institute of Technology

by Stefano Panzeri

A postdoctoral position in computational neuroscience is available at Istituto Italiano di Tecnologia in Italy to work with Stefano Panzeri ( https://www.iit.it/people/stefano-panzeri) The successful candidate will conduct research in the laboratory of Neural Computation of Prof. Panzeri and in collaboration with Prof. Christopher Harvey at Harvard Medical School. We investigate, by developing and using advanced data analysis methods and neural network models, how circuits of neurons in the brain encode information and use it to produce appropriate behaviors. The Neural Computation laboratory offers a wide range of interdisciplinary expertise in computational neuroscience, including both advanced neural analysis techniques and neural network modeling. The laboratory also offers a thriving, ambitious research environment which is well funded (including several grants from the NIH Brain Initiative). This gives successful candidates ample opportunities for advanced training and personal scientific growth. We seek candidates holding a PhD in a numerate or neuroscientific discipline, with a solid computational background and a keen interest in neuroscience. They must be highly motivated and creative individuals who want to work in a dynamic, multi-disciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists. For recent publications relevant to this project, see: Runyan C. A., et al (2017) Distinct timescales of population coding across cortex, *Nature*: 548: 92-96. G. Pica, et al (2017) Quantifying how much sensory information in a neural code is relevant for behavior, *Neural Information Processing Systems (NIPS 2017)* Panzeri S., et al (2017) Cracking the neural code for sensory perception by combining statistics, intervention and behaviour. *Neuron* 93: 491-507 Chettih and Harvey (2019) Single-neuron perturbations reveal feature-specific competition in V1. *Nature* 567, 334 Chong, E. et al (2020) Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception. *Science* 368, 1329. The deadline for applications is *Oct. 27th, 2020*. Applications will be examined as soon as they are received and until the position is filled. Interested applicants are strongly encouraged to email Stefano Panzeri ( stefano.panzeri(a)iit.it) as soon as possible, to informally inform him of their interest for the position and initiate a discussion about research projects. Formal applications should be submitted, before the deadline, through the following web site: https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=en&job=20000039 Thanks Stefano Panzeri

Oct. 8, 2020

Two research fellow positions in Neuromorphic Olfaction

by Michael Schmuker

We have two Research Fellow positions available, funded through the NSF/MRC NeuroNex grant “Odor to Action”, an international consortium of 16 world-leading research groups from the US, Canada, and the UK. The consortium will apply their joint expertise in computational and experimental neuroscience, behavioural studies, fluid dynamics, and fragrance chemistry to unlock how brains use natural stimuli to generate adaptive natural behaviours. Apply to join an interdisciplinary team of computational neuroscientists, AI researchers and computer scientists to investigate the neuro-computational principles of the sense of smell and translate them into approaches for machine and robot olfaction. Our team will investigate real-time machine olfaction using biologically realistic spiking networks, on neuromorphic hardware, embodied in robots, performing olfactory navigation in real time. We will also use machine learning to analyse experimental data provided by collaborators and to gain a deeper insight into fragrance space. For more information and to apply, please head to https://www.jobs.herts.ac.uk <https://www.jobs.herts.ac.uk/> , search for job vacancy 029755. Informal inquiries via email are welcome! — Dr Michael Schmuker AFHEA Professor of Neural Computation Biocomputation Group University of Hertfordshire https://biomachinelearning.net

Oct. 6, 2020