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Google Summer of Code: model and experimental data sharing on Open Source Brain
by Padraig Gleeson March 31, 2022

March 31, 2022

--Apologies for cross-posting-- Google Summer of Code <https://summerofcode.withgoogle.com/> is a global, online program focused on bringing new contributors into open source software development. Generous stipends are provided for successful applicants to work on these projects for a number of months over the summer. The INCF <http://incf.org/> has been a GSoC mentoring organisation for the past number of years, and has helped link up students with mentors to advance various projects in the wider neuroinformatics and computational neuroscience areas. The Open Source Brain initiative <http://www.opensourcebrain.org> is encouraging students to apply to be part of this. The successful candidate(s) for our 2 proposals will take published computational models and experimental datasets and convert them into open, standardised formats (e.g. NeuroML and NWB) and share them on the OSB platform as a resource for the wider community. The two projects are: *Open source, cross simulator, large scale cortical models in NeuroML and PyNN* <https://neurostars.org/t/gsoc-2022-project-idea-9-1-open-source-cross-simul…> These can be models where code is available in simulator specific formats on ModelDB, or classic models from the literature which would benefit from curating/updating/documenting. Making models available in these formats will allow them to be used & tested across multiple simulators, make the physiological properties of the models more accessible and facilitate reuse of model components. *Conversion of public neurophysiology datasets to Neurodata Without Borders (NWB) format* <https://neurostars.org/t/gsoc-2022-project-idea-9-2-conversion-of-public-ne…> This project will involve converting a number of publicly available datasets to NWB format, adding structured metadata to ensure maximal readability and reusability of the data. The converted datasets will be made available through the new NWB Explorer on the Open Source Brain repository (http://nwbexplorer.opensourcebrain.org) which allows visualisation of the data as well as interactive analysis through an inbuilt Jupyter notebook. *This opportunity is particularly relevant for Masters & PhD students currently working in model development/data analysis in neuroscience. Many students **are already reusing/converting/updating existing models and data as part of their work and this is a great opportunity to get paid extra to do this! *** Closing date for student applications: *19 April 2022* Period of working on projects: *13 June - ***12 *September 2022* Please get in contact if you have any questions. -- ----------------------------------------------------- Padraig Gleeson Room 321, Anatomy Building Department of Neuroscience, Physiology& Pharmacology University College London Gower Street London WC1E 6BT United Kingdom +44 207 679 3214 p.gleeson(a)ucl.ac.uk -----------------------------------------------------

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Postdoc in Computer Vision / Machine Learning / Applied Mathematics
by Tony Lindeberg March 31, 2022

March 31, 2022

Postdoc in Computer Vision / Machine Learning / Applied Mathematics Job description The Division of Computational Science and Technology at KTH Royal Institute of Technology in Stockholm, Sweden is seeking a Postdoc in Computer Vision / Machine Learning / Applied Mathematics to handle scale-dependent image information in deep networks. In our research, we develop deep networks for processing image data that handle scaling transformations and other image transformations in a theoretically well-founded manner. Our research in this area comprises both theoretical modelling of the influence of image transformations on different architectures for deep networks and the experimental evaluation of such networks on benchmark datasets to explore their properties. The work also comprises the creation of new benchmark datasets, to enable characterization of properties of deep networks that are not covered by existing datasets. For examples of our previous work in this area, see https://www.kth.se/profile/tony/page/deep-networks Within the scope of this postdoc position, you are expected to work on and contribute to the research frontier regarding scale-covariant or scale-equivariant deep networks and/or deep networks parameterized in terms of Gaussian derivatives, on specific research topics that we choose together. The selected candidate will work closely together with the project leader Tony Lindeberg. Qualifications requirements * A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline * We are seeking a candidate with a PhD in Computer Vision, Machine Learning, Applied Mathematics or a related discipline dealing with automated analysis of image information. * Previous experience with experimental evaluations using deep learning architectures applied to image data is necessary, preferably PyTorch. * A theoretical background in continuous mathematics for modelling convolutions and the influence of image transformations on image data is also necessary. Preferred qualifications As a person you have excellent scientific and collaborative skills, in combination with independence, with very good ability to get into new scientific theories and conduct implementations and experimental evaluations in close collaboration with the research environment you are working in. The preferred candidates should have demonstrated expertise (through publications) in any one of the following: * Deep networks that handle image information for computer vision tasks, including experimental evaluation using modern architectures for deep networks. * Continuous models for deep networks applied to image information. * Theoretical modelling of scaling transformations or other image transformations applied to automated processing of image information. For further information and information about to how to apply, see https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:490734/ Application deadline: May 2, 2022 The position is offered for a period of two years. [cid:FD2B374F-C472-4895-ADA7-B3CD5419FD22@csc.kth.se] Tony Lindeberg Professor of Computer Science — Computational Vision KTH Royal Institute of Technology Computational Brain Science Lab Division of Computational Science and Technology, CST SE-100 44 Stockholm, Sweden Phone: +46 8 790 6205 https://www.kth.se/profile/tony/

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Cerebellar computation postdoc
by Nicolas Brunel March 30, 2022

March 30, 2022

A postdoc position is available to build and analyze network models of cerebellar cortex that incorporate the diversity of cell types and synaptic connections observed in this structure. The goal of this research is to better understand the functions of these diverse cell types and connections. Approaches from statistical physics, nonlinear dynamics and machine learning will be used, and models will be constrained by new electrophysiological, transcriptomic and connectomic data. The postdoc will be jointly supervised by Wade Regehr (Department of Neurobiology at Harvard Medical School) and Nicolas Brunel (Duke University). The position will be based in Wade Regehr's lab, but with frequent visits to the Brunel lab at Duke. Applicants should have a strong background in computational/theoretical neuroscience, machine learning, theoretical physics, and/or applied mathematics. We are committed to building a diverse intellectual community, and particularly encourage women and members of underrepresented groups to apply to this position. For more information on the labs: Regehr Lab: https://urldefense.com/v3/__https://regehrmedharvard.wordpress.com/__;!!OTo… Brunel Lab: https://www.neuro.duke.edu/research/faculty-labs/brunel-lab Please email a cover letter explaining background and interest in the position, a curriculum vitae, and names & email addresses of two references to: Kim McDaniels Kimberly_Mcdaniels(a)hms.harvard.edu<mailto:Kimberly_Mcdaniels@hms.harvard.edu> Please have the subject of the email: “Computational Postdoc Applicant:” Your Name

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IMRF abstract submission deadline extended to April 07
by Marc Ernst March 30, 2022

March 30, 2022

Dear friends of IMRF, upon multiple request, we decided to extend the abstract submission deadline for the International Multisensory Research Forum 2022 (IMRF2022) by some days to April 07th. You can submit new abstracts for talks and posters until that date (here <https://www.conftool.net/imrf2020>). In case you submitted an abstract already previously for 2020 or 2021, please make sure to verify that your abstract and information is still up-to-date. To do so, you can log into the system (here <https://www.conftool.net/imrf2020>) and update your abstract information at any time until the deadline. In case you will not be able to make it to IMRF this year, which I would deeply regret, but you submitted an abstract earlier in the past two years, please make sure to withdraw your abstract (here <https://www.conftool.net/imrf2020>). In case you submitted an already accepted symposium in 2020, these symposia will keep their accepted status. But please as organiser of the symposium verify that all presenters of the symposia are still on board (here <https://www.conftool.net/imrf2020>). In cases where this is necessary please update the symposium information - abstracts of the symposia can be updated by the organiser of the symposium. In case you have a drop out of one or two speakers it is best to exchange them by new speakers. As for registration, I would recommend to register early (here <https://www.conftool.net/imrf2020>). At the moment it seems like the spatial restrictions may be loosened. But with this virus you never know. Also, please start looking for a hotel room early. There is the Danube Festival the same week of IMRF - a nice festival along the Danube river. We reserved some rooms but only until a month prior to the meeting. When booking, please refer to “IMRF” to get our conference rates. Looking forward to finally seeing you in Ulm in summer 2022. Best, Marc --------------------------------------------------------- Prof. Dr. Marc Ernst Applied Cognitive Psychology Faculty for Computer Science, Engineering & Psychology Ulm University Albert-Einstein-Allee 43 89081 Ulm room nr.: 43.3.103 mail: marc.ernst(a)uni-ulm.de <mailto:marc.ernst@uni-ulm.de> phone int.: +49-(0)731-50 320 50 phone ext.: +49-(0)731-50 356 27 sekr: +49-(0)731-50 320 51 mobile: +49-(0)152-22 543 156

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Workshop: The interplay of complex and coherent dynamics in brain function. May 18-20, Cergy
by boris gutkin March 29, 2022

March 29, 2022

Interplay of complex and coherent dynamics in brain function will take place at CY Advanced Studies at Neuville-Sur-Oise from 18th to 20th May 2022 thanks to the support of CY Cognition, CYAS, Labex MME-DII. More information can be found here: https://complexityparisseine.wordpress.com/ The workshop will take place in a hybrid form, with a group of participants (at most 50) in presence at CYAS and the rest connected via Zoom. There will be the possibility to present posters of your research activity up to a maximum of 20 posters, There are no costs, but if you are interested you should register in both cases either in presence or in remote (Zoom) by April 30th. Organisers: Alessandro Torcini (CYU), Demian Battaglia (INS marseille), Boris Gutkin (ENS, Paris) and Matteo di Volo (University of Parma, Italy)

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additional 2 postdoc positions (4 in total) at Imperial College
by Schultz, Simon R March 29, 2022

March 29, 2022

Dear all, In addition to the previously advertised two experimental positions, we have two theoretical postdoc positions available: Four post-doc positions in the Statistical Physics of Cognition Two theoretical and two experimental postdoctoral positions each for a duration of up to 36 months starting as soon as possible after 1st April 2022. All four post-docs will form a collaborative team, will be affiliated with the Departments of Mathematics and Bioengineering at Imperial College London, and will work together with a core team consisting of Simon R Schultz, Henrik Jeldtoft Jensen, Fernando Rosas, Mauricio Barahona, Lucilla de Arcangelis, Ann Go and Amanda Foust. As for the two theoreticians we are looking for people familiar with statistical mechanics of complex systems, including SOC, network theory and information theory. The theory positions can be found here: https://www.imperial.ac.uk/jobs/description/NAT01116/research-associate-mat… The details for the experimental positions are here: https://www.imperial.ac.uk/jobs/description/ENG02064/postdoctoral-research-… To discuss the theoretical positions, please contact Henrik Jensen (h.jensen(a)imperial.ac.uk<mailto:h.jensen@imperial.ac.uk>) To discuss the experimental positions, please contact Simon Schultz (s.schultz(a)imperial.ac.uk<mailto:s.schultz@imperial.ac.uk>) Best wishes Simon -- Prof Simon Schultz Dept of Bioengineering, Imperial College London http://www.schultzlab.org Director, Imperial College Centre for Neurotechnology http://www.imperial.ac.uk/neurotechnology For Centre admin, email: Dr Kate Hobson, k.hobson(a)imperial.ac.uk

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Atsushi IRIKI speaking on March 31 in Developing Minds global online lecture series
by Jochen Triesch March 28, 2022

March 28, 2022

Dear colleagues, On March 31, the Developing Minds global online lecture series will feature Atsushi IRIKI, RIKEN Japan: "Self-in-the-world map evolved in the primate brain as a basis of civilized Homo sapiens“ The live event will take place via zoom at: 22:00 JST (Japan Standard Time) 15:00 CET (Central European Time) 13:00 UTC (Universal Coordinated Time) 9:00 EST (Eastern Standard Time) To participate please register here: https://sites.google.com/view/developing-minds-series/home Abstract After a specific point in history, hominin evolution accelerated to a level that could not be accounted for by natural selection alone, but an alternative mechanism has been proposed based on mutual interaction among neural, cognitive, and ecological niches in a positive feedback loop (triadic niche construction; TNC). Nevertheless, the trigger events for the cognitive revolution of Homo sapiens as well as the reasons for this event being limited to a single species remain unknown. Using a multidisciplinary approach involving psychology, neurobiology, and phenomenology, I will propose a shift in the mechanisms underlying TNC, from TNC- 1 in primates/hominids to TNC-2 in Homo sapiens, to answer these questions. As the primates and hominin brain expanded during TNC-1, latent cognitive capabilities were incubated within its neural framework to be expressed with a simple rewiring among brain areas in TNC-2, a quick and inexpensive process but one that requires a unique set of preconditions to commence. This process was bootstrapped by the advanced function of “projection,” which enabled humans to recognize the “self” in particular time and space in the world, allowing the manipulation of this world (in both physical and symbolic dimensions) again in a positive feedback loop. Based on these, a new concept of a somatocentric holistic self will be proposed, represented as a more comprehensive body-in-the-world map in the primate brain, taking into account evolutionary aspects that characterize the human cognition and its implication in the emergence of self-consciousness. Paper: Iriki A, Suzuki H, Tanaka S, Bretas R, Yamazaki Y. (2021). The sapient paradox and the great journey: Insights from cognitive psychology, neurobiology and phenomenology. Psychologia, https://doi.org/10.2117/psysoc.2021-B017. Bio Atsushi IRIKI received his Ph.D. in Neuroscience from Tokyo Medical and Dental University in 1986. He held research associate positions at the Tokyo Medical and Dental University and then at The Rockefeller University (USA). He joined the faculty of Toho University Medical School as an assistant professor and then as an associate professor in Physiology (1991-1999). In 1999, he returned to Tokyo Medical and Dental University as a full professor and chairman of Cognitive Neurobiology. In 2004, Atsushi IRIKI was appointed a head of Laboratory for Symbolic Cognitive Development at RIKEN Institute (first at its Brain Science Institute and then 2018 onward at Center for Biosystems Dynamics Research). He is currently a visiting professor of University College London (UK) and Nanyang Technological University (NTU, Singapore), an adjunct professor of Keio University, a research professor of Kyoto University, a senior fellow of the Canadian Institute for Advanced Research (Canada), founding co-director of RIKEN-NTU Research Centres (Singapore & Japan). Web: https://www.riken.jp/en/research/labs/bdr/symbol_cogn_dev/index.html Best regards, Jochen Triesch -- Prof. Dr. Jochen Triesch Johanna Quandt Chair for Theoretical Life Sciences Frankfurt Institute for Advanced Studies and Goethe University Frankfurt http://fias.uni-frankfurt.de/~triesch/ Tel: +49 (0)69 798-47531 Fax: +49 (0)69 798-47611

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Postdoc in Computational Neuroscience and/or Machine Learning at the University of Calgary, Canada
by Joern Davidsen March 26, 2022

March 26, 2022

Dear colleagues, We are recruiting a postdoctoral researcher in Computational Neuroscience and/or Machine Learning to study network neural dynamics of brain function and psychedelics to participate in a cutting-edge International Network for Brain-Inspired Computation<https://www.nsf.gov/awardsearch/showAward?AWD_ID=2019976&HistoricalAwards=f…> (AcelNet) that includes nodes in Montreal, Paris, and the Pacific Northwest of the US and Canada (e.g. University of Washington, Allen Brain Institute). The project is at the intersection of mathematics, physics, and neuroscience in the general area of complex network dynamics and representations that drive biological computation. The objective is to understand how the brain develops generative cognitive models to organize perception and behaviour, and the effects of psychedelic drugs. This project involves both analysis of large-scale ensemble neural data collected in our labs, and computational and/or analytical work to develop theories of core function. Please forward to anyone who you think might be interested. For more info (review of applications will begin on May 1st), please see below or https://www.ucalgary.ca/complexity/positions or reach out to Dr. Jörn Davidsen (davidsen(a)phas.ucalgary.ca<mailto:davidsen@phas.ucalgary.ca>) and Dr. Aaron Gruber (aaron.gruber(a)uleth.ca<mailto:aaron.gruber@uleth.ca>). Best wishes, Joern. --- Dr. Jörn Davidsen Professor of Physics & Humboldt Research Fellow University of Calgary www.ucalgary.ca/davidsen<http://www.ucalgary.ca/davidsen> ************************************************************************************ Postdoc in Computational Neuroscience and/or Machine Learning at the University of Calgary, Canada We are recruiting a talented postdoctoral researcher in Computational Neuroscience and/or Machine Learning to study network neural dynamics of brain function and psychedelics to participate in a cutting-edge International Network for Brain-Inspired Computation<https://www.nsf.gov/awardsearch/showAward?AWD_ID=2019976&HistoricalAwards=f…> (AcelNet) that includes nodes in Montreal, Paris, and the Pacific Northwest of the US and Canada (e.g. University of Washington, Allen Brain Institute). The project is at the intersection of mathematics, physics, and neuroscience in the general area of complex network dynamics and representations that drive biological computation. The objective is to understand how the brain develops generative cognitive models to organize perception and behaviour, and the effects of psychedelic drugs. This project involves both analysis of large-scale ensemble neural data collected in our labs, and computational and/or analytical work to develop theories of core function. The ideal candidate will have a quantitative background (e.g. PhD in mathematics, physics, computer science) along with experience in applying this background to neuroscience. Specifically, we are looking for a postdoctoral candidates interested in what mathematical principles predict (1) how the connectivity structure of neural networks – their connectomes – combine with the dynamics of nodes and edges to control the dynamics and statistics of the network, (2) how the brain learns these connectomes to produce generative models predictive of their environment, and (3) how such models are affected by psychedelic drugs. The overarching aim of the project is to understand how mental models become corrupted in depression/anxiety, and how psychedelics appear to reverse the corruption. A variety of world-class data sets on the structure and function of the brain are available to guide theoretical advances in the understanding of underlying brain computation, particularly in learning, perception, and decision making. The position is open immediately with a primary location in Calgary. It is partially funded by the Pacific Institute for Mathematical Sciences<https://www.pims.math.ca/> and is aimed to strengthen the link between the computational neuroscience community at the University of Calgary (Complexity Science Group<https://www.ucalgary.ca/complexity/>, Hotchkiss Brain Institute<https://hbi.ucalgary.ca/>) and the University of Lethbridge (Canadian Center for Behavioural Neuroscience<https://www.uleth.ca/artsci/neuroscience/about>) with the other network members including the Computational Neuroscience Center<https://cneuro-web01.s.uw.edu/> at the University of Washington, and centers in Montreal and Paris. The specific start date has to be within five years of being awarded a PhD degree. The position is funded for at least two years and includes an annual stipend in the range of CAD$42,000 – $50,000 plus benefits. Opportunities for brief residences in partner nodes (Montreal, Seattle, or Paris) are also available. Interested candidates should submit their application package including a cover letter, their CV with a list of publications, brief statement of research interests and their possible start dates in PDF format to Dr. Jörn Davidsen (davidsen(a)phas.ucalgary.ca<mailto:davidsen@phas.ucalgary.ca>) and Dr. Aaron Gruber (aaron.gruber(a)uleth.ca<mailto:aaron.gruber@uleth.ca>). Applicants should arrange for at least two letters of reference to be sent as well. Review of applications will begin May 1st, 2022, and continue until the position is filled. For additional information and informal inquiries, please contact Dr. Davidsen or Dr. Gruber. We strive for a diverse and inclusive environment, and encourage applications from members of any identity. --- Dr. Jörn Davidsen Professor of Physics & Humboldt Research Fellow University of Calgary www.ucalgary.ca/davidsen<http://www.ucalgary.ca/davidsen>

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PostDoc positions on neuromorphic sensing for condition monitoring
by Fredrik Sandin March 26, 2022

March 26, 2022

The Embedded Intelligent Systems Lab (EISLAB) at the Luleå University of Technology in Sweden is inviting applications for two 2-year PostDoc positions focusing on neuromorphic sensing for condition monitoring. The scholarships are intended for research that aims to develop knowledge about neuromorphic and event-driven sensor systems for advanced condition monitoring, e.g. investigating filterbanks, charge amplifier designs, event-based sampling, and machine learning based signal processing methods suitable for implementation with spiking neural networks and neuromorphic processors. The project is a collaboration between EISLAB and the division of Machine Elements and is funded by The Kempe Foundations. By taking part in this collaboration you will work in an international, creative resourceful environment with an extensive international contact network. Further information about the positions, requirements and how to apply is available here: - https://www.ltu.se/ltu/stipendier-priser/postdoc-stipendier?l=en - https://web103.reachmee.com/ext/I003/583/main?site=14&validator=47967adc563… ========================= Professor Fredrik Sandin EISLAB, Machine Learning Luleå University of Technology 971 87 Luleå, Sweden www.ltu.se/staff/f/fresan-1.10646?l=en

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MBL Methods in Computational Neuroscience Course - Deadline March 30
by Stephen A. Baccus March 25, 2022

March 25, 2022

Applications are open for the Methods in Computational Neuroscience course at the Marine Biology Laboratory in Woods Hole, MA. The course will run from July 28 to August 24, 2022, and the online application form can be found at: https://www.mbl.edu/education/advanced-research-training-courses/course-off… The course application deadline is *March 30*. The course covers a range of topics in computational neuroscience including neuronal biophysics, neural coding & information processing, circuit dynamics, learning & memory, motor control, and cognitive processing & disease. In addition, numerous tutorials and problem sets will cover a broad range of computational and mathematical modeling methods. The course strongly emphasizes the collaboration between theory and experiment in solving neuroscience problems, and lectures will be given by a mixture of theorists and experimentalists. The final weeks of the course are primarily reserved for work on projects that students design in collaboration with the resident faculty. Further information can be found on the MCN website: http://www.mbl.edu/mcn/ 2022 Course Directors: Stephen Baccus, Stanford University Xiao Jing Wang, New York University 2022 Faculty: Larry Abbott, Columbia University Tim Behrens, Univ. College London Emery Brown, MIT Randy Buckner, Harvard University Anne Churchland, UCLA Claudia Clopath, Imp. College London Albert Compte, IDIBAPS Shaul Druckmann, Stanford University Uri Eden, Boston University Bard Ermentrout, U. of Pittsburgh Adrienne Fairhall, U. of Washington Michale Fee, MIT James Fitzgerald, Janelia Res., HHMI Loren Frank, UCSF Stefano Fusi, Columbia University Surya Ganguli, Stanford University Paul Glimcher, New York University Mark Goldman, UC Davis Nancy Kopell, Boston University Eve Marder, Brandeis University Yiota Poirazi, IMBB-FORTH David Redish, U. Minnesota Terry Sejnowski, Salk Institute Reza Shadmehr, Johns Hopkins Univ. Sara Solla, Northwestern University Haim Sompolinsky, Hebrew University Nelson Spruston, Janelia Res., HHMI Josh Tenenbaum, MIT Nao Uchida, Harvard University Greg Wayne, DeepMind

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