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DeepMath 2022 Submission Deadline

by Ahmed El Hady

** *Dear all,* * We are pleased to announce our confirmed lineup of invited speakers for DeepMath 2022: * Francis Bach (INRIA) * Anima Anandkumar (CalTech) * Sara Solla (Northwestern) * Berk Ustun (UCSD) * Yisong Yue (Caltech) * Courtney Paquette (McGill) We are now accepting abstract submissions to the 2022 Conference on mathematical theory of deep neural networks (DeepMath; see https://deepmath-conference.com <https://deepmath-conference.com>for more information). DeepMath is a highly interdisciplinary conference focused on understanding fundamental theory driving the success of Deep Learning. A principal goal of this conference is to bring together theoreticians working on deep learning from various disciplines and perspectives. We therefore encourage submissions from researchers from diverse disciplines including, but not limited to * Statistics * Physics * Computer science * Neuroscience * Mathematics * Psychology * Engineering Topics may address any area of deep learning research such as * Expressivity * Generalization * Optimization * Representations * Computation * Network architectures * Recurrent networks. To complement the many conferences with applications andtheory the focus for DeepMath 2022 will be exclusively on thetheoretical and mechanistic understandingof the underlying properties of neural networks. Abstracts will not be made public (i.e., no official proceedings), and will be doubly-blind reviewed and selected for quality. All poster submissions should be properly anonymized in order to allow for blind refereeing. Submissions should be no more than 1 pagealthough a second page may be used for references. Authors should submit a pdf file prepared using the Latex style file available here <https://drive.google.com/file/d/1dkDhgVN5SHphwQKNLnQiDzkgbp0NFyNT/view?usp=…>and should adopt all formatting, subject headings, font sizes, etc. defined therein. Submissions that fail to meet the format requirements will not be reviewed. The first author listed on the abstract is considered to be the presenting author. Each presenting author may submit only one abstract. Investigators interested in having their abstracts considered for presentation should submit their abstracts no later than August 14, 2022 AOE. Authors may submit their abstracts at: https://cmt3.research.microsoft.com/DEEPMATH2022/ == Location == DeepMath 2022 will be held in San Diego, CA, USA. We anticipate requiring proof of full vaccination as a condition of attendance, and plan on having masking and other requirements equal or more stringent than local and national public health guidelines. Stay tuned to the DeepMath website (www.deepmath-conference.com <http://www.deepmath-conference.com>) for more details on venue and hotels. As with all prior years, all talks will be freely live-streamed over YouTube and subsequently posted on the DeepMath YouTube channel == Registration == DeepMath 2022 registration will open late summer. As with previous DeepMath conferences, all talks will be live-streamed for free and uploaded for later viewing subject to presenter approval. All the best, Ahmed El Hady On behalf of the DeepMath 2022 Organizational Committee *

Aug. 1, 2022

EBRAINS Workshop 14-16 March 2023, Paris FR - Anatomy and function of the prefrontal cortex across species

by Zélie Tournoud

Dear colleagues, Please find below the announcement of the EBRAINS Workshop "Anatomy and function of the prefrontal cortex across species" taking place 14-16 March 2023 in Paris, France. Registration is currently open with an early bird pricing. Kind regards, *Zélie Tournoud*/ EITN Communication manager/ *European Institute for Theoretical Neuroscience (EITN)* UMR 9197 – *NeuroPSI*(Institut des Neurosciences Paris-Saclay) CNRS – Université Paris-Saclay Centre CEA Paris-Saclay Bâtiment 151 91400 Saclay https://www.eitn.org <https://www.eitn.org> _____ EBRAINS Workshop Anatomy and function of the prefrontal cortex across species *14 – 16 March 2023 | Paris, France* Program, information and registration: https://www.humanbrainproject.eu/en/education-training-career/workshops/pfc/<https://www.humanbrainproject.eu/en/education-training-career/workshops/pfc/> *Early Bird Registration Deadline: 21 November 2022 * *Late Registration Deadline: 28 February 2023* About Understanding the human brain relies for a large part on work in animal models, which necessitates a careful *cross-species comparison*. The *prefrontal cortex* (PFC) is particularly relevant in this regard as its function is poorly understood and potential cross-species differences remain highly debated. This workshop brings together experimental and computational**scientists whose work allows a comparison of the *anatomy* and *function* of the PFC between species (in particular between humans, monkeys and mice). EBRAINS <http://ebrains.eu/> is uniquely suited to provide a platform to compare anatomy, physiology and behaviour between species, due to its atlases, numerous datasets, as well as the whole brain models from different species. The *interactive format* of the workshop will allow speakers as well as participants from largely separated fields to interact and discuss, which is expected to create novel insights as well as lead to more coherence and clarity in the relevant terminology, formats and important research directions in the field. Confirmed speakers *Day 1* *Anatomy:* *Javier DeFelipe* | Cajal Institute, Madrid, Spain *Huib Mansvelder* | Vrije Universiteit Amsterdam, Amsterdam, The Netherlands *Chet Sherwood* | GW Mind-Brain Institute, Washington, USA *Suzana Herculano-Houzel *| Vanderbilt University, Nashville, USA *Henry Kennedy* | Stem Cell and Brain Research Institute, Lyon, France *Marie Carlén* | Karolinska Institute, Stockholm, Sweden *Physiology:* *Wim Vanduffel* | KU Leuven, Leuven, Belgium *Mark Laubach* | American University, Washington, USA *Stefan Everling* | Western University, London, Canada *Hendrikje Nienborg* | National Eye Institute, Bethesda, USA *Martha Havenith* | Ernst Strüngmann Institute for Neuroscience, Frankfurt, Germany *Yang Dan* | University of California, Berkeley, USA *Day 2* *Behavior & physiology:* *Pieter Roelfsema* | Netherlands Institute for Neuroscience, Amsterdam, The Netherlands *Andreas Nieder* | University of Tübingen, Tübingen, Germany *Sandra Reinert* | Max Planck Institute for Biological Intelligence, Martinsried, Germany *Ann Duan* | Sainsbury Wellcome Centre, London, UK *Stanislas Dehaene* | NeuroSpin, Gif-sur-Yvette, France *Jessica Cantlon* | Carnegie Mellon University, Pittsburgh, USA *Computational modelling:* *Idan Segev* | Edmond & Lily Safra Center for Brain Sciences, Jerusalem, Israel *Rodrigo Cofre* | NeuroPSI, Gif-sur-Yvette, France *Rubén Moreno Bote* | University Pompeu Fabra, Barcelona, Spain *Jorge Mejias* | Universiteit van Amsterdam, Amsterdam, The Netherlands *Adrienne Fairhall* | University of Washington, Seattle, USA *Xiao-Jing Wang *| New York University, New York, USA Scientific Chairs & Local hosts *Timo van Kerkoerle**|***CEA Saclay, France *Alain Destexhe* *|*** CNRS, France *Ruth Benavides-Piccione* *|***Spanish National Research Council & Universidad Politécnica de Madrid, Spain

Aug. 1, 2022

2 fully funded PhD positions at the Univ. of Groningen

by Michael Biehl

Two fully funded (4 years) PhD positions in Neural Networks / Machine Learning / Deep Learning are available at the University of Groningen / NL within the project: "*Robust Learning of **Sparse Representations: * *Brain-inspired Inhibition and **Statistical Physics* *Analysis*". Main supervisors and sub-projects: George Azzopardi (https://www.cs.rug.nl/~george/) "*Push-pull inhibition in deep, convolutional * *(spiking) neural networks*" Michael Biehl (https://www.cs.rug.nl/~biehl/) "*Statistical physics analysis of learning processes * *in model situations*" For details and your expression of interest please visit https://t.co/VLjgKzPxJp *Apologies for multiple postings.* *Please circulate and distribute further.* -- --------------------------------------------------- Prof. Dr. Michael Biehl Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence P.O. Box 407, 9700 AK Groningen The Netherlands https://www.cs.rug.nl/~biehl m.biehl(a)rug.nl

July 29, 2022

Preparatory workshop for shaping funded research teams in neuromorphic and unconventional computing (Europe only)

by Herbert Jaeger

The Volkswagen Foundation -- Germany's largest private research funding organization -- launches an initiative for the development of neuromorphic and other non-digital approaches to analyse and engineer computing systems. One action within this initiative is to support the formation of INTERDISCIPLINARY, possibly multi-national research teams. In a preparatory "Ideation" workshop, to be held in Einbeck (Germany) in December 5-8, 2022, European researchers interested in non-digital computing are invited to exchange views and ideas and start networking. The target audience is open-minded postdocs and assistant/junior professors with backgrounds in relevant areas - including but not restricted to materials and devices, microchip technology, optical computing, neuroscience, cognitive modeling, theory of computing, machine learning, complex dynamical systems, or philosophy of computing. The aim of the workshop is the nucleation of research teams who subsequently submit funding proposals for large-scale interdisciplinary research projects. More information can be found at https://www.volkswagenstiftung.de/en/funding/our-funding-portfolio-at-a-gla…. -- Dr. Herbert Jaeger Professor of Computing in Cognitive Materials Rijksuniversiteit Groningen Faculty of Science and Engineering - CogniGron Bernoulliborg Nijenborgh 9, 9747 AG Groningen office: Bernoulliborg 402 phone: +31 (0) 50-36 32473 COVID home office phone: +49 (0) 4209 930403 web: www.ai.rug.nl/minds/

July 29, 2022

Workshop on Big Data Neuroscience UT Austin

by Franco Pestilli

Dear Colleagues, We are excited to announce the 7th annual Big Data Neuroscience (BDN) workshop organized by the Advanced Computational Neuroscience Network <https://neurosciencenetwork.org/ACNN_Workshop_2022.html#home>. The BDN workshop brings together researchers in neuroscience, computer science, statistics, computer engineering, structural biology, neuroinformatics, and related disciplines. The BDN workshop will be held in Austin, Texas, September 15-16, 2022. The themes of the workshops will be on the following topics: (1) Data Governance and Infrastructure, (2) Measurements and Acquisition, (3) Advanced Analysis and Applications, (4) Software, Sharing and Publication, (5) Standards and Validation. We have an exciting line-up of speakers spanning multiple disciplines of science and engineering: James Carson (Kristen Harris’ NeuroNex, UT Austin), Dan Stanzione (TACC), Damian Eke (De Montfort University), Axel Brunger (Stanford University), Martin Paulus (Laureate Institute), Jason McLellan (UT Austin), Jingyu Liu (Georgia State), Jessica Church-Lang (UT Austin), Chen Yu (UT Austin), Angie Laird (Florida International University), Maryann Martone (University of California San Diego), Laura Colgin (The University of Texas at Austin), Franco Pestilli (UT Austin), Piotr Sliz (Harvard University), Yaroslav Halchenko (Dartmouth), Dora Hermes (Mayo Clinic), and David Kennedy (UMass Medical School). In addition to science and engineering, the workshop will host a panel discussion on “Challenges and opportunities for international-scale infrastructure to advance data sharing and equity” with representatives from the National Science Foundation, the National Institutes of Health, Kavli Foundation, Nature Publishing Group, and Wellcome Trust. Registration You can register for the workshop using this form <https://forms.gle/xkAv9dgErAGzXPodA>. The deadline is September 1st, 2022. Call for Posters and Lightning Talks You can submit your abstract here <https://forms.gle/uyBRgaJb91CjoSUr9>. The deadline is August 18, 2022. Travel Scholarships A few travel scholarships for trainees with underrepresented backgrounds and diverse geographical locations are available. Use the abstract submission form to apply for a travel scholarship <https://forms.gle/uyBRgaJb91CjoSUr9>. The deadline is August 18, 2022. Please visit www.neurosciencenetwork.org for more information. Best regards, Franco Pestilli, The University of Texas at Austin Susanne Ressl, The University of Texas at Austin Josiah Leong, University of Arkansas Sharlene Newman, University of Alabama Jessica Turner, Georgia State Ivo Dinov, University of Michigan *FRANCO PESTILLI*, *Ph.D.* | *Associate Professor* Department of Psychology <https://liberalarts.utexas.edu/psychology/index.php> | College of Liberal Arts <https://liberalarts.utexas.edu/> | The University of Texas at Austin <https://www.utexas.edu/> he/him | pestilli(a)utexas.edu | web <https://liberalarts.utexas.edu/psychology/faculty/fp4834> | GitHub <https://github.com/francopestilli> | brainlife.io CONFIDENTIALITY NOTICE: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message.

July 27, 2022

Post-doc in Neurophysiology: Cortical control of free viewing eye movements

by Bisley, James

Apologies for cross-posting We invite applications for a post-doc position studying the cortical control of free viewing eye movements at UCLA. The work will include recording from the frontal eye field and superior colliculus as well as inactivation experiments in LIP and FEF. For more information about the sort of work done in the lab, check out our publications at https://www.ncbi.nlm.nih.gov/myncbi/james.bisley.1/bibliography/public/. UCLA is growing its visual neuroscience footprint and now is an exciting time to be in Los Angeles. Applicants should have a strong background in systems neurophysiology, behavioral training or computational neuroscience and be comfortable working independently on all aspects of the project. Previous experience with NHP recording, the use of open source recording systems and data analysis is desirable. Candidates should hold a PhD in neuroscience, psychology or a related discipline. The position is initially for 12 months with the possibility of renewal. Compensation will be commensurate with relevant experience. Candidates should send a CV, a brief statement of research experience and interests, expected date of availability, and the contact information for two references to James Bisley (jbisley(a)mednet.ucla.edu) Cheers, James ________________________________ UCLA HEALTH SCIENCES IMPORTANT WARNING: This email (and any attachments) is only intended for the use of the person or entity to which it is addressed, and may contain information that is privileged and confidential. You, the recipient, are obligated to maintain it in a safe, secure and confidential manner. Unauthorized redisclosure or failure to maintain confidentiality may subject you to federal and state penalties. If you are not the intended recipient, please immediately notify us by return email, and delete this message from your computer.

July 27, 2022

Postdoc and grad student positions at intersection of AI and Neuroscience

by Luczak, Artur

Dear All, We are looking for postdocs and graduate students (Master’s and/or Ph.D. levels) to use inspirations from neuroscience to make better AI and conversely to apply AI to better understand brain function and behaviour. Projects will be related to our recent work: Neurons learn by predicting future activity. Nature Machine Intelligence 2022 https://www.nature.com/articles/s42256-021-00430-y Predictive neuronal adaptation as a basis for consciousness. Front in Sys Neurosci 2022 https://www.frontiersin.org/articles/10.3389/fnsys.2021.767461/full Miniaturized head-mounted microscope for whole-cortex mesoscale imaging in freely behaving mice. Nature Methods 2021 https://www.nature.com/articles/s41592-021-01104-8 A Matlab-based toolbox for characterizing behavior of rodents engaged in string-pulling. Elife 2020 https://elifesciences.org/articles/54540 Challenges of a small world analysis for the continuous monitoring of behavior in mice. Neuroscience and Behavioral Reviews 2022 https://www.sciencedirect.com/science/article/pii/S0149763422001105 Data-driven analyses of motor impairments in animal models of neurological disorders. PLoS Biology 2019 https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.30005… The project is a collaborative effort between the research groups of Majid Mohajerani (http://lethbridgebraindynamics.com/majid-mohajerani/) and Artur Luczak (http://lethbridgebraindynamics.com/artur-luczak/) Successful candidates will join the highly collaborative and interdisciplinary Canadian Centre for Behavioural Neuroscience and Brain Dynamics group. We are located close to Rocky Mountains, Lethbridge has the largest number of sunny days in Canada, and it is the most affordable city for young people in Canada (https://dailyhive.com/calgary/alberta-city-most-affordable-young-people ). The applications review will start on Aug 15th till the positions are filled. Interested applicants must send an email to Dr Mohajerani (mohajerani(a)uleth.ca<mailto:mohajerani@uleth.ca>) and Dr. Luczak (luczak(a)uleth.ca<mailto:luczak@uleth.ca>) and include a cover letter, curriculum vitae, a brief statement of research interests, and contact information of three references. Cheers, Artur

July 27, 2022

Several PhD positions in clinical EEG and MEG at SFU, Vancouver

by Vasily Vakorin

Dear moderators, Can you please post this ad? Thank you. Several PhD positions in clinical EEG and MEG at SFU, Vancouver Several funded Ph.D. positions are available at Simon Fraser University (Vancouver, Canada), at the Department of Biomedical Physiology and Kinesiology and the School of Engineering Science. Ph.D. candidates will focus on research in neurophysiology, such as electroencephalography (EEG) and magnetoencephalography (MEG), and machine learning to study clinical populations. Two Ph.D. projects will use clinical routine EEG recorded and evaluated in public hospitals in the process of neurological evaluation to predict patients’ clinical profiles. The other project will apply MEG to explore cortico-cerebellar brain networks in children with autism. Ph.D. candidates are expected to get experience with digital signal processing, multivariate statistics, predictive analytics (deep learning and classical machine learning) and data analysis with applications in clinical and cognitive neuroscience, and further develop scientific programming skills (Python). The ideal start date is September 2022, but in general it is flexible. For more information, please contact Dr. Sam Doesburg, Dr. Teresa Cheung, and Dr. Vasily Vakorin: https://www.bcni-sfu.net . If you are interested, please send your cover letter and CV to vvakorin(a)sfu.ca . Please name the attached files according to the format: Lastname_Firstname_cv.pdf and Lastname_Firstname_coverletter.pdf . Thank you, Vasily Vakorin, Ph.D. Scientist & NeuroInformatics Lead - Behavioral & Cognitive Neuroscience Institute Adjunct Professor - Biomedical Physiology & Kinesiology Simon Fraser University, British Columbia, Canada Affiliated Researcher - Fraser Health Authority, British Columbia email: vvakorin(a)sfu.ca

July 26, 2022

AMALEA workshop September 12-16

by Michael Biehl

On behalf of Prof. Dr. Nicolai Petkov (www.cs.rug.nl/~petkov) *International workshop on Applications of Machine Learning and Neural Networks* *AMALEA, 12-16 Sept 2022, Cetraro, Calabria, Italy* Dear colleagues and friends, There are a few rooms still available for AMALEA - APPLICATIONS OF MACHINE LEARNING International Workshop, Cetraro, Italy, September 12-16, 2022 http://amalea.web.rug.nl/index.html Venue: Grand Hotel San Michele on the West, Tyrrhenian sea coast of Southern Italy with a surrounding own land estate, golf course, private beach and a conference center. Photo gallery Aim: to provide a discussion forum for scientists from different disciplines where they can inspire and learn from each other, meet new people and form new research alliances. Format: a single track for talks from 10:00-12:30H and 17:00-19:30H in the conference center. Enough time for discussions outside the conference room: during breakfast on the terrace overlooking the Tyrrhenian sea, at lunch in the private beach restaurant, in the afternoon break on the private beach, at dinner on the hotel terrace and after dinner listening to the life piano music in the grand salon. Please visit the workshop website for further information and contact. -- --------------------------------------------------- Prof. Dr. Michael Biehl Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence P.O. Box 407, 9700 AK Groningen The Netherlands https://www.cs.rug.nl/~biehl m.biehl(a)rug.nl

July 26, 2022

Sergey Levine speaking on July 28 in Developing Minds global online lecture series

by Jochen Triesch

Dear colleagues, On July 28, the Developing Minds global online lecture series will feature Sergey Levine, UC Berkeley, USA: "From Reinforcement Learning to Embodied Learning“ https://sites.google.com/view/developing-minds-series/home The live event will take place via zoom at: 09:00 PDT (Pacific Daylight Time) 16:00 UTC (Universal Coordinated Time) 18:00 CEST (Central European Summer Time) 01:00 JST, July 29 (Japan Standard Time) To participate please register here: https://sites.google.com/view/developing-minds-series/home Abstract Reinforcement learning provides one of the most widely studied abstractions for learning-based control. However, while the RL formalism is elegant and concise, real-world embodied learning problems (e.g., in robotics) deviate substantially from the most widely studied RL problem settings. The need to exist in a real physical environment challenges RL methods in terms of generalization, robustness, and capacity for lifelong learning -- all aspects of the RL problem that are often neglected in commonly studied benchmark problems. In this talk, I will discuss how we can devise a framework for learning-based control that is at its core focused on generalization, robustness, and continual adaptation. I will argue that effective utilization of previously collected experience, in combination with multi-task learning, represents one of the most promising paths for tackling these challenges, and present recent research in RL and robotics that studies this perspective. Bio Sergey Levine received a BS and MS in Computer Science from Stanford University in 2009, and a Ph.D. in Computer Science from Stanford University in 2014. He joined the faculty of the Department of Electrical Engineering and Computer Sciences at UC Berkeley in fall 2016. His work focuses on machine learning for decision making and control, with an emphasis on deep learning and reinforcement learning algorithms. Applications of his work include autonomous robots and vehicles, as well as computer vision and graphics. His research includes developing algorithms for end-to-end training of deep neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, deep reinforcement learning algorithms, and more. Web: https://people.eecs.berkeley.edu/~svlevine/ The talk will also be recored and the recording made available via the web page: https://sites.google.com/view/developing-minds-series/home Stay healthy, 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

July 26, 2022