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Call for papers: Biological Cybernetics Special Issue: What can Computer Vision learn from Visual Neuroscience?
by Jeffrey Krichmar Aug. 26, 2022

Aug. 26, 2022

Dear Colleagues, Please consider submitting your work to this special issue of Biological Cybernetics. Call for papers: Biological Cybernetics Special Issue: What can Computer Vision learn from Visual Neuroscience? Submission deadline: September 30, 2022 https://www.springer.com/journal/422/updates/20421374 This special issue invites original research and review articles related to topics in biological vision that can potentially benefit computer vision systems. The following is a non exhaustive list of topics in biological vision that can also benefit computer vision systems. • Active vision’s role in visual search, scene understanding, social interactions, etc. • Learning in the visual system. Learning in biology is continual, few-shot, and adversarially robust. • The roles of recurrent and top-down connections in the visual cortex. • Spike based spatiotemporal processing and its implications for neuromorphic vision. • Motion perception in dynamic environments. • Neural coding schemes in the visual system (e.g., sparse coding, predictive coding, and temporal coding.) • The roles of attention mechanisms in biological vision. How to submit: Please submit your manuscript using the journal online submission system following the Biological Cybernetics submission guidelines. Guest Editors: Kexin Chen - Department of Cognitive Sciences, University of California, Irvine Hirak J. Kashyap - Department of Computer Science, University of California, Irvine Jeffrey L. Krichmar - Department of Cognitive Sciences, Department of Computer Science, University of California, Irvine Xiumin Li - College of Automation, Chongqing University, Chongqing, China If you have any questions, please reach out to one of the guest editors. Best regards, Jeff Krichmar Department of Cognitive Sciences 2328 Social & Behavioral Sciences Gateway University of California, Irvine Irvine, CA 92697-5100 jkrichma(a)uci.edu http://www.socsci.uci.edu/~jkrichma

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Open PhD position at the Goethe University Frankfurt / Germany
by Claudius Gros Aug. 24, 2022

Aug. 24, 2022

I would like to bring your attention our PhD-program in Computational Neurosciences / Complex Dynamical Systems at the Institute of Theoretical Physics, Goethe University Frankfurt, Germany Field(s): computational neurosciences, complex systems, theory neural networks, simulated robotics, game theory, dynamical systems. Application deadline: October 30, 2022 Contact: Prof. Claudius Gros, cgr[(a)]itp.uni-frankfurt.de We are developing new models and generative principles for complex systems, using a range of toolsets from dynamical systems theory, game theory, and the neurosciences. Examples are self-generated gaits for animals and robotic systems, criticality in autonomous networks, as well as investigations of the 'tragedy of the commons'. Several subjects are available for the announced PhD thesis, depending on the background of the successful candidate. The work will include analytical investigations and numerical simulations. The candidate must have a Diploma/Master in physics, an excellent academic track record and good computational skills. Experience or strong interest in the fields of complex systems, computational neurosciences and dynamical systems theory is expected. The degree of scientific research experience needs to be on the level of a German Diploma/Master The appointment will start late 2022 / early 2023, for up to three years. Interested applicants must submit a curriculum vitae, a list of publications and copies of the academic record. Name, affiliation and email of one or more potential references are to be given. Claudius Gros http://www.itp.uni-frankfurt.de/~gros ------------------------------------- The Johann Wolfgang Goethe University Frankfurt am Main is with over 46,000 students and around 4,600 employees one of the largest universities in Germany. Founded in 1914 by Frankfurt citizens and again in the legal form of a foundation since 2008, the Goethe University has a high level of independence, modernity and professional diversity. As a comprehensive university, the Goethe University Frankfurt offers and has 100 degree programs on five campuses in a total of 16 departments an outstanding research strength. The time limit for academic staff is based on the provisions of the Academic Term Contract Act in conjunction with the Hessian Higher Education Act. The university advocates equal rights for women and men and therefore encourages women to apply. Disabled applicants with equal qualification will be given preferential consideration. ### ### Prof. Dr. Claudius Gros ### http://itp.uni-frankfurt.de/~gros ### ### Complex and Adaptive Dynamical Systems, A Primer ### A graduate-level textbook, Springer (2008/10/13/15) ### ### Life for barren exoplanets: The Genesis project ### https://link.springer.com/article/10.1007/s10509-016-2911-0 ###

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Several Ph.D. positions at SFU, Vancouver (clinical EEG recordings and medical texts)
by Vasily Vakorin Aug. 22, 2022

Aug. 22, 2022

Several Ph.D. positions at SFU, Vancouver (clinical EEG recordings and medical texts). Several fully-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. One of the large-scale projects is based on an extensive dataset of routine clinical EEG recorded and evaluated in the process of a diagnostic workup at four local public hospitals. The data include EEG scans and corresponding EEG reports (written impressions of the visual analysis of the EEG, which was done by neurologists). One Ph.D. project will use EEG recordings to predict clinically-relevant labels. The other project will apply Natural Language Processing (NLP) tools to develop models for extracting labels from EEG reports. For more information, please contact Dr. Sam Doesburg or 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

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PhD position feelSpace/Cognitive Science University Osnabrück
by Peter König Aug. 19, 2022

Aug. 19, 2022

PhD opportunity feelSpace GmbH/University Osnabrück in the EU Marie-Curie project OptiVis. Work in a great team and make blind people grasp. https://euraxess.ec.europa.eu/jobs/826171 The webpage states "filled", but it is not. https://optivist.eu/project-10 For more information contact Peter König pkoenig(a)uos.de -- Prof. Dr. Peter König, Institute of Cognitive Science, University Osnabrück

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A postdoc position in image processing, machine learning, and neuroscience
by Hideaki Shimazaki Aug. 18, 2022

Aug. 18, 2022

(Posted on behalf of Prof. Shin Ishii, Kyoto University, Japan) *Call for a postdoctoral researcher* A postdoc position is available in image processing, machine learning, and neuroscience. The objective of the new multi-year project is to understand the neural basis of behavior changes in humans/animals. We shall tackle the AI-based image processing technology for capturing body movements and characterizing possible changes in behaviors. We may also develop methods of analyzing neuronal co-activation from large-scale Ca imaging data or capturing brain waves from multichannel ECoG data. We are looking for a young researcher interested in working on one or some of these topics. The contract is yearly-basis and renewable *until March 31, 2027*. Workplace: Kyoto University, Kyoto, Japan A successful applicant should have a Ph.D. in computational neuroscience, machine learning, physics, applied mathematics, or engineering, but not limited to these. The applicant should demonstrate research experiences with a strong publication record. Programming skills in Python or willingness to learn it, will be valued. To apply, please send a CV with a publication list, a statement of research interests (maximum two pages), and contact information of one or two reference(s) to ishii-sec(a)sys.i.kyoto-u.ac.jp. Either English or Japanese is accepted. The starting date is flexible, while earlier arrival is appreciated. The salary and title follow the university rule and depend on the record/expertise of an appointed researcher. Please feel free to send me any informal questions regarding this post. Sincerely, Shin Ishii, Ph.D. Professor with Kyoto University, Kyoto, Japan Director with Advanced Telecommunication Research Institute International (ATR), Kyoto, Japan Email: ishii-sec(a)sys.i.kyoto-u.ac.jp Webpage: https://ishiilab.jp

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FSL course 2022 in Oxford, registration open!
by Rezvan Farahibozorg Aug. 17, 2022

Aug. 17, 2022

Dear all, We are pleased to announce that FSL course 2022 will be held in-person, Sept 19th - 23rd, in Oxford, UK. You can find details and registration info here: https://open.win.ox.ac.uk/pages/fslcourse/website/upcoming.html This intensive course covers the *theory and practice of functional, structural, diffusion and resting state brain imaging analysis*. New and existing users of FSL are welcome on the course, as it aims to cover both basic and more advanced topics. Background concepts and practicalities of the analyses are taught in detailed lectures. These lectures are interleaved with hands-on practical sessions, where attendees learn how to carry out analysis for themselves on real data. The contents covered in the course are primarily aimed at applications in basic neuroscience and clinical research. Please note that the course will be in-person only, with no online or remote attendance option. For COVID safety, including masking, policy please refer to the link above. Looking forward to seeing you then, The FSL Course team ------------------------------------------------------------------------- Rezvan Farahibozorg Senior postdoctoral researcher, FMRIB Analysis Group, WIN, NDCN University of Oxford https://www.ndcn.ox.ac.uk/team/rezvan-farahibozorg -------------------------------------------------------------------------

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Workshop on Attention - Call for Papers
by Grace Lindsay Aug. 17, 2022

Aug. 17, 2022

On behalf of the co-organizers, we would like to invite you to submit your work to our NeurIPS workshop on “All things Attention: Bridging Different Perspectives on Attention”. The details of the workshop and submission instructions are as follows: The Thirty Sixth Conference on Neural Information Processing Systems (NeurIPS) Dec 2, 2022 NeurIPS 2022 is a hybrid Conference https://attention-learning-workshop.github.io/ The All Things Attention workshop aims to foster connections across disparate academic communities that conceptualize "Attention" such as Neuroscience, Psychology, Machine Learning, and Human-Computer Interaction. Workshop topics of interest include (but are not limited to): 1. Relationships between biological and artificial attention 1. What are the connections between different forms of attention in the human brain and present deep neural network architectures? 2. Can the anatomy of human attention models provide useful insights to researchers designing architectures for artificial systems? 3. Given the same task and learning objective, do machines learn attention mechanisms that are different from humans? 1. Attention for reinforcement learning and decision making 1. How have reinforcement learning agents leveraged attention in decision making? 2. Do decision-making agents today have implicit or explicit formalisms of attention? 3. How can AI agents build notions of attention without explicitly baked in notions of attention? 4. Can attention significantly enable AI agents to scale e.g. through gains in sample efficiency, and generalization? 2. Benefits and formulation of attention mechanisms for continual / lifelong learning 1. How can continual learning agents optimize for retention of knowledge for tasks that it already learned? 2. How can the amount of interference between different inputs be controlled via attention? 3. How does the executive control of attention evolve with learning in humans? 4. How can we study the development of attentional systems in infancy and childhood to better understand how attention can be learned? 3. Attention as a tool for interpretation and explanation 1. How have researchers leveraged attention as a visualization tool? 2. What are the common approaches when using attention as a tool for interpretability in AI? 3. What are the major bottlenecks and common pitfalls in leveraging attention as a key tool for explaining the decisions of AI agents? 4. How can we do better? 4. The role of attention in human-computer interaction and human-robot interaction 1. How do we detect aspects of human attention during interactions, from sensing to processing to representations? 2. What systems benefit from human attention modeling, and how do they use these models? 3. How can systems influence a user’s attention, and what systems benefit from this capability? 4. How can a system communicate or simulate its own attention (humanlike or algorithmic) in an interaction, and to what benefit? 5. How do attention models affect different applications, like collaboration or assistance, in different domains, like autonomous vehicles and driver assistance systems, learning from demonstration, joint attention in collaborative tasks, social interaction, etc.? 6. How should researchers thinking about attention in different biological and computational fields organize the collection of human gaze data sets, modeling gaze behaviors, and utilizing gaze information in various applications for knowledge transfer and cross-pollination of ideas? 5. Attention mechanisms in Deep Neural Network (DNN) architectures 1. How does attention in DNN such as transformers relate to existing formalisms of attention in cogsci/psychology? 2. Do we have a concrete understanding of how and if self-attention in transformers contributes to its vast success in recent models such as GPT2, GPT3, DALLE.? 3. Can our understanding of attention from other fields inform the progress we have achieved in recent breakthroughs? SUBMISSION INSTRUCTIONS We invite you to submit papers (up to 9 pages for long papers and up to 5 pages for short papers, excluding references and appendix) in the NeurIPS 2022 format. <https://neurips.cc/Conferences/2022/PaperInformation/StyleFiles> All submissions will be managed through OpenReview (submission website <https://openreview.net/group?id=NeurIPS.cc/2022/Workshop/Attention>). The final submission including main paper, references and appendix should not exceed 12 pages. Supplementary Materials uploads are to only be used optionally for extra videos/code/data/figures and should be uploaded separately in the submission website. The review process is double-blind so the submission should be anonymized. Accepted work will be presented as posters during the workshop, and select contributions will be invited to give spotlight talks during the workshop. Each accepted work entering the poster sessions will have an accompanying pre-recorded 5-minute video. Please note that at least one coauthor of each accepted paper will be expected to have a NeurIPS conference registration and participate in one of the poster sessions. Submissions will be evaluated based on novelty, rigor, and relevance to the theme of the workshop. Both empirical and theoretical contributions are welcome. Submissions should not have previously appeared in a journal or conference (including accepted papers to NeurIPS 2022) and should not be submitted to another NeurIPS workshop. Submissions must adhere to the NeurIPS Code of Conduct. The focus of the work should relate to the list of the topics specified below. The review process will be double-blind and accepted submissions will be presented as virtual talks or posters. There will be no proceedings for this workshop, however, authors can opt to have their abstracts/papers posted on the workshop website. We encourage submissions on the following topics from the focus of bridging different perspectives on attention: - Relationships between biological and artificial attention - Attention for reinforcement learning and decision making - Benefits and formulation of attention mechanisms for continual / lifelong learning - Attention as a tool for interpretation and explanation - The role of attention in human-computer interaction and human-robot interaction - Attention mechanisms in Deep Neural Network (DNN) architectures Please submit your papers via the following link: submission website <https://openreview.net/group?id=NeurIPS.cc/2022/Workshop/Attention> IMPORTANT DATES * Submission deadline: Sep 15, 2022 at 11:59PM (AOE) submission website <https://openreview.net/group?id=NeurIPS.cc/2022/Workshop/Attention> * Accept/Reject Notification: Oct 12, 2022 * Camera-ready (final) paper deadline: Nov 25, 2022 at 11:59PM (Anywhere on earth) * Workshop: Dec 2, 2022 CONFIRMED SPEAKERS & PANELISTS Speakers: Pieter Roelfsema (Netherlands Institute for Neuroscience) James Whittington (University of Oxford) Ida Momennejad (Microsoft Research) Erin Grant (UC Berkeley) Henny Admoni (Carnegie Mellon University) Tobias Gerstenberg (Stanford University) Vidhya Navalpakkam (Google Research) Shalini De Mello (NVIDIA) Panelists: David Ha (Google Brain) Pieter Roelfsema (Netherlands Institute for Neuroscience) James Whittington (University of Oxford) Ida Momennejad (Microsoft Research) Henny Admoni (Carnegie Mellon University) Tobias Gerstenberg (Stanford University) Shalini De Mello (NVIDIA) Ramakrishna Vedantam (Meta AI Research) Megan deBettencourt (University of Chicago) Cyril Zhang (Microsoft Research) ORGANIZERS Akanksha Saran (Microsoft Research, NYC) Khimya Khetarpal (McGill University, Mila Montreal) Reuben Aronson (Carnegie Mellon University) Abhijat Biswas (Carnegie Mellon University) Ruohan Zhang (Stanford University) Grace Lindsay (University College London, New York University) Scott Neikum (University of Texas at Austin, University of Massachusetts) REGISTRATION Participants should refer to the NeurIPS 2022 website ( https://neurips.cc/Conferences/2022/Dates) for information on how to register. CONTACT Please reach out to us at attention-workshop(a)googlegroups.com if you have any questions. We look forward to receiving your submissions! Kind Regards, Workshop Organizers All things Attention- Bridging different perspectives on attention

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Postdoctoral fellowships at the Gatsby Unit
by I-Chun Aug. 16, 2022

Aug. 16, 2022

The Gatsby Computational Neuroscience Unit invites applications for postdoctoral fellowships in theoretical neuroscience. Successful applicants will carry out original research under the guidance of a faculty member, primarily on one of these research themes: - How dynamical computation in neural systems underlies functions ranging from perceptual inference to deliberation, action selection and execution (mentor: Maneesh Sahani). - Deep learning theory (mentor: Andrew Saxe). Applications close at the end of August 2022. For detailed information on the roles and how to apply, please visit www.ucl.ac.uk/gatsby/vacancies About the Gatsby Unit Established in 1998 through a generous grant from the Gatsby Charitable Foundation, the Gatsby Unit has been a pioneering centre for research in theoretical neuroscience and machine learning. The Unit provides a unique multidisciplinary research environment with strong links to the Sainsbury Wellcome Centre for Neural Circuits and Behaviour, the ELLIS Unit at UCL, and other neuroscience and machine learning groups at UCL and beyond. -- I-Chun Lin, PhD Scientific Programme Manager Gatsby Computational Neuroscience Unit, UCL i.lin(a)ucl.ac.uk | www.ucl.ac.uk/gatsby | @GatsbyUCL

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2 fully funded PhD positions in Groningen
by Michael Biehl Aug. 16, 2022

Aug. 16, 2022

Please excuse multiple postings Two fully funded PhD positions (4 years) are available at the University of Groningen within the project "Robust Learning of Sparse Representations in Neural Networks". The official job announcement including more details and contact information is now available at https://www.rug.nl/about-ug/work-with-us/job-opportunities/?details=00347-0… All applications should be submitted through this website before September 30, 2022. One PhD (PP1) will address the study of "push-pull inhibition" in Deep Learning, supervised by Dr. George Azzopardi (www.cs.rug.nl/~george) Candidates should have a strong background in brain inspired computing and deep learning. The second position (PP2) will be devoted to the statistical physics based analysis of model situations. Candidates for PP2 should have a strong background in (theoretical) physics, ideally with experience in the statistical physics based theory of neural networks and learning. Both positions will be fully funded (4 years) by the Groningen Cognitive Systems and Materials Center https://www.rug.nl/research/fse/cognitive-systems-and-materials/?lang=en -- --------------------------------------------------- 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

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Two postdoc positions
by Benjamin Dunn Aug. 16, 2022

Aug. 16, 2022

We have two open postdoctoral positions in projects to develop methods for large population neural data. We are looking for good people with backgrounds in statistics, statistical physics, machine learning, topological data analysis, etc., with experience developing and applying methods within neuroscience – ideally with a desire to figure out how the brain works. Many benefits: vacation, parental leave, socialized medicine (it’s Norway), good salary, supportive environment, trees, great science/math, fjords, etc. It’s nice here. Apply and get info more here: https://www.jobbnorge.no/en/available-jobs/job/229369/2-postdoctoral-fellow… And additional questions to benjamin.dunn(a)ntnu.no Benjamin Dunn Associate professor in neural data science Department of Mathematics & Kavli Institute for Systems Neuroscience, NTNU

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