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The interplay of complex and coherent dynamics in brain function; Cergy (France) May 18-22 2022

by bgutkin

The HYBRID workshop The interplay of complex and coherent dynamics in brain function https://complexityparisseine.wordpress.com/ <https://complexityparisseine.wordpress.com/> will take place at Cy Advanced Studies , Neuville sur Oise (France) from 18-20 May 2022. This international workshop is the final act of the ANR Project Exact Reduction of Multiscale Neural Dynamics ERMUNDY involving CY Cergy Paris Université, École Normale Supérieure in Paris and Institut de Neurosciences des Systèmes in Marseille. Our aim is to bring in Neuville-sur-Oise scientists working in different disciplines ranging from applied mathematics to neuroscience, from physics to biology in order to address a topic of general interest as the emergence of complex and coherent dynamics in the brain. If you are interested to follow the workshop via ZOOM you should register here: https://univ-amu-fr.zoom.us/meeting/register/tZEuceypqjItE9ASdbQAOwoovh7EJc… <https://univ-amu-fr.zoom.us/meeting/register/tZEuceypqjItE9ASdbQAOwoovh7EJc…> In case you would like to come (even for 1 single day) and eventually present a poster, you should register here : https://complexityparisseine.wordpress.com/contact/ <https://complexityparisseine.wordpress.com/contact/> due to COVID restrictions only 20 places are left and they will be reserved in priority for those presenting a poster. The organizing committee A. Torcini, B. Gutkin, D. Battaglia, M. di Volo

April 4, 2022

Coordinator position 'Diversity Internship Programme', Tuebingen, Germany

by Susan Fischer

---- Apologies for cross-posting ---- In an exciting venture, the Max Planck Institute for Biological Cybernetics has created a new internship programme, targeting students from currently underrepresented communities. The Institute investigates information processing in the brain for which it uses experimental, theoretical and computational methods to study perception, memory, decision-making, motor performance and more, and to develop appropriate recording and imaging techniques. We now invite applications for a part-time position for a Coordinator of the Computation and Cognition Tübingen Summer Internship (CaCTüS internship) (m/f/d;). This position is limited until 31 October 2023 in the first instance. The internship aims to improve diversity, equity and inclusion in animal, human and machine intelligence research by offering paid research stays to students from currently underrepresented groups to work on projects suggested and supervised by early career researchers. By providing hands-on research experience, access to first-class research facilities and scientific networks at the start of the students’ careers, the initiative counteracts systemic disadvantages and empowers students to continue their academic career and to develop their full potential. Key Duties & Responsibilities: In your role as CaCTüS Coordinator you will be responsible for the implementation and the overall management of the internship. You will contribute to the planning, organisation, implementation and maintenance of the programme’s activities, systems and processes and serve as the point of contact for potential candidates/enrolled interns. You will also identify and assess further potential external funding opportunities and contribute to the strategic development and promotion of the initiative. Full job description and detailed information about the position can be found on our website at: https://jobs.tue.mpg.de/jobs/168 ************************************************ Susan Fischer Coordinator Alexander von Humboldt Professorship Prof Peter Dayan & Department for Sensory and Sensorimotor Systems, Prof Zhaoping Li Eberhard Karls Universität Tübingen & Max Planck Institute for Biological Cybernetics AI Research Building R 20-7/A21 Maria-von-Linden-Str. 6 72076 Tübingen Germany susan.fischer(a)tue.mpg.de ************************************************

April 4, 2022

Postdoctoral Scholar in Computational/Theoretical Neuroscience (Western University)

by Lyle Muller

The lab of Lyle Muller (http://mullerlab.ca<http://mullerlab.ca/>) at the Department of Mathematics and the Western Institute for Neuroscience (Western University, London, Ontario) has an open postdoctoral position in computational and theoretical neuroscience. This scientist will work with an international NeuroNex consortium (http://nxwm.io) studying the transcriptomic, cellular, and network basis of working memory. The project will incorporate analysis of multichannel neural data and computational models ranging from single neurons to spiking neural networks and machine learning algorithms. The researcher will work within a dynamic team and with data at multiple scales (transcriptomics, intracellular patch clamp, and extracellular spiking data). Research in this project utilizes a combination of large-scale numerical simulations, supervised/unsupervised learning, and analytical approaches. Prior experience with scientific computing languages (MATLAB, Julia, or Python) and/or low-level programming (C/C++) is preferred. Prior experience with computational modeling, signal processing, or random graph theory is also preferred. Western University offers an excellent research environment and support. Both our group and the University are deeply committed to fostering diversity in the sciences, and applications from underrepresented groups are strongly encouraged. Interested candidates can write to lmuller2(a)uwo.ca<mailto:lmuller2@uwo.ca> with a CV and statement of interest. Review of applications will begin on 18 April 2022. -- Lyle Muller http://mullerlab.ca

April 4, 2022

Deadline extension - 31st International Conference on Artificial Neural Networks ICANN 2022, Sept 6-9, Bristol, UK

by Paolo Masulli ENNS

31st International Conference on Artificial Neural Networks ICANN 2022 https://e-nns.org/icann2022 *Submission deadline extended to: 13 April 2022* Bristol, United Kingdom - *Hybrid event* 6 - 9 September 2022 ============================================================= The International Conference on Artificial Neural Networks (ICANN) is the annual flagship conference of the European Neural Network Society (ENNS). In 2022 the Department of Computer Science and Creative Technologies of the University of the West of England, in Bristol, United Kingdom will organise ICANN 2022. This will be held at Frenchay Campus from 6 to 9 September 2022. The conference is currently planned as a *hybrid event* with some presence and some online participation if possible. We will continuously monitor the situation in the next few months according to the overall health developments. * **CONFERENCE TOPICS* ICANN 2022 is a conference featuring tracks in Brain-inspired Computing and Machine Learning in Artificial Neural Networks, with strong cross-disciplinary interactions and applications. All research fields dealing with Neural Networks will be present at the conference. A non-exhaustive list of topics includes: *Machine Learning*: Deep Learning, Neural Network Theory, Neural Network Models, Graphical Models, Bayesian Networks, Kernel Methods, Generative Models, Information-theoretic Learning, Reinforcement Learning, Relational Learning, Dynamical Models, Recurrent Networks, Ethics of AI. *Brain-inspired Computing*: Cognitive models, Computational Neuroscience, Self-organisation, Bioinspired Learning, Neural Control and Planning, Hybrid Neural-Symbolic Architectures, Neural Dynamics, Cognitive Neuroscience, Brain Informatics, Perception and Action. *Neural Applications for*: Bioinformatics, Biomedicine, Intelligent Robotics, Neurorobotics, Language Processing, Speech and Image Processing, Sensor Fusion, Pattern Recognition, Data Mining, Neural Agents, Brain-Computer Interaction, Neural Hardware, Evolutionary Neural Networks. *CALL FOR CONTRIBUTED SCIENTIFIC COMMUNICATIONS* All scientific communications presented at ICANN 2022 will be reviewed and scientifically evaluated by a panel of experts. The conference will feature two categories of communications: - oral communications (15'+5') - poster communications. *Call for Special Sessions and Workshops* ICANN 2022 organizers cordially invite internationally recognised experts to organise Special sessions and Workshops within the general scope of the conference. Proposals should be sent to ICANN2022(a)uwe.ac.uk *CALL FOR PAPERS* Authors willing to present original contributions in either the oral or poster category may submit: - A full paper of maximum 12 pages (including references) to be published in Springer-Verlag Lecture Notes in Computer Science (LNCS) series with individual DOI. - An extended abstract of maximum 4 pages to be published in Springer-Verlag Lecture Notes in Computer Science (LNCS) series, without indexing. The number of oral slots is limited. In case the number of requested oral presentations is larger than the available slots, the ICANN scientific committee will select which papers will be reassigned to a poster session. This selection will be based on the coherence of the programme and is totally independent of the category of submission. Submission of communications will be on the conference website: https://e-nns.org/icann2022/ *IMPORTANT DATES* Deadline for special session and workshop proposals: 28 Feb 2022 Opening of contribution submissions: 21 Feb 2022 Deadline for full paper and extended abstract submission: 13 Apr 2022 Notification of acceptance: 20 Jun 2022 Camera-ready paper upload: 30 June 2022 Deadline for author registration and early registration at early rate: 30 June 2022 *BEST PAPER AWARDS* ENNS will sponsor a maximum of four best paper awards. All awards will be presented during the final ceremony. *TRAVEL GRANTS* The European Neural Network Society sponsors a number of Student Travel Grants covering part of the costs for attending ICANN. Details will be provided on the conference website. *ORGANISATION* *General Chairs* Elias Pimenidis – UWE Bristol, UK Angelo Cangelosi – University of Manchester, UK *Organising Committee Chairs* Tim Brailsford – UWE Bristol, UK Larry Bull – UWE Bristol, UK *Honorary Chairs* Stefan Wermter – University of Hamburg, Germany (ENNS President) Igor Farkaš – FMPI, Comenius University in Bratislava, Slovakia *Programme Committee Chairs* Plamen Angelov – Lancaster University, UK Mehmet Aydin – UWE Bristol, UK Chrisina Jayne – Teesside University, UK Elias Pimenidis – UWE Bristol, UK *Communication Chairs* Paolo Masulli – ENNS, Technical University of Denmark Kristína Malinovská – FMPI, Comenius University in Bratislava, Slovakia Antonios Papaleonidas – Democritus University of Thrace, Greece

April 3, 2022

FACM-22 Conference 'New Perspectives in Math Biology' May 20-21 (2022) NJIT, Newark NJ

by Victor Matveev

On May 20 and 21, 2022, the 17th Annual Conference on Frontiers in Applied and Computational Mathematics (FACM '22) will be held at the New Jersey Institute of Technology (NJIT) in Newark, New Jersey. The theme of FACM '22 Conference is "New Perspectives in Mathematical Biology." https://sites.google.com/njit.edu/facm2022/home Confirmed plenary speakers are: Carina Curto (Pennsylvania State University) Anita Layton (University of Waterloo) Grzegorz Rempala (Ohio State University) Corina Tarnita (Princeton University) FACM '22 will feature 4 minisymposia that cover a wide range of topics in math biology: (1) *learning paradigms in real and artificial neuronal networks,* (2) collective behavior in biological populations, (3) stochastic modeling at different scales, and (4) biofluids: machine learning and data-driven approaches. A poster session will run concurrently over the 2 days of the meeting. Pending NSF support, funds to cover all or part of the travel costs and local accommodation costs may be available for students, postdocs, and junior faculty. Applications by members of underrepresented groups, minorities and women are particularly encouraged. A combined poster abstract submission, travel award application and registration form (due April 15, 2022) is available at the conference homepage: https://sites.google.com/njit.edu/facm2022/home There is no registration fee for this conference. NJIT campus is located in close proximity to two train stations, the Newark Liberty International airport, and is accessible by public transportation from New York City: https://www.njit.edu/about/maps-directions FACM'22 Organizing Committee: Amitabha Bose (co-Chair), Casey Diekman, Simon Garnier, Enkeleida Lushi, James MacLaurin, Victor Matveev (co-Chair), Peter Thomas, Yuan-Nan Young -- ----------------------------------------------- Victor Matveev, Professor Applied Math, Biophysics, Neuroscience Department of Mathematical Sciences Graduate Faculty, Dept of Biological Sciences New Jersey Institute of Technology Newark, NJ 07102-1982 matveev(a)njit.edu

April 1, 2022

INCF/OCNS Software WG session on NetPyNE (4th April: 1600 UTC)

by Ankur Sinha

Dear all, Apologies for the cross post. Please join us for the next INCF/OCNS Software working group "dev session" where Joe Graham will speak to us about NetPyNE: https://ocns.github.io/SoftwareWG/2022/04/04/dev-session-joe-graham-netpyne… - Date: April 4, 2022, 1600 UTC (Click here[1] to see your local time). - Location (Zoom): (login to Zoom required): https://ucl.zoom.us/j/99620419452?pwd=SkZlQnJmWWZVczNURkp2azVOZkhzUT09 Abstract: NetPyNE is an open-source Python package to facilitate the development, parallel simulation, analysis, and optimization of biological neuronal networks using the NEURON simulator. The NetPyNE GUI is available from a variety of resources: Neuroscience Gateway Portal (NSG); Open Source Brain (OSB) ; Human Brain Project (HBP) EBRAINS; and the NIH SPARC initiative. The NetPyNE source code is available on GitHub. More information is available on the NetPyNE website. During this dev session, I will give an overview of NetPyNE, go through an interactive demo using the NetPyNE GUI, describe my personal development workflow using virtual environments, and then go through two big dev projects I worked on: (1) documenting code inline and online using docstrings, Sphinx, Napoleon, and autodocsumm, and (2) separating and standardizing analysis and plotting. --------- The aim of these sessions is to stimulate discussion of the development practices and tools used by different teams to improve the software we use while also improving our knowledge of these practices and tools. We also hope to encourage more users of these tools to contribute to their development to ensure their longevity. If you develop software for neuroscience, we would love to hear about your development pipeline. Please get in touch with the Software WG on our GitHub repository[3]. The WG is a community based group that is open to everyone at all levels of their careers (academic or otherwise). Please introduce yourself to the community on our channels to get involved. [1] https://www.timeanddate.com/worldclock/fixedtime.html?msg=Dev+session%3A+Jo… [2] https://github.com/OCNS/SoftwareWG/issues -- Thanks, Regards, Ankur Sinha (He / Him / His) | https://ankursinha.in Research Fellow at the Silver Lab, University College London | http://silverlab.org/ Free/Open source community volunteer at the NeuroFedora project | https://neuro.fedoraproject.org Time zone: Europe/London

April 1, 2022

Postdoctoral position in computational neuroscience

by Maxim Bazhenov

Applications are invited for NIH funded post-doctoral research position in the laboratory of Dr. Maxim Bazhenov at the University of California, San Diego to study role of sleep in memory and learning using sophisticated computer models of brain dynamics. This project involves close collaboration with experimental laboratories. The ultimate goal of the work is to understand how sleep rhythms contribute to consolidation of memory for recent learning and how sensory or electrical stimulation during sleep can enhance memory consolidation (see, e.g., 10.7554/eLife.51005; 10.1093/cercor/bhaa228; 10.1523/JNEUROSCI.1427-19.2019). Our lab research interests also include other topics in neuroscience (e.g., olfaction, epilepsy) and artificial intelligence (e.g., lifelong learning, generalization, adversarial robustness) and lab members are encouraged to participate in multiple projects. The successful candidate will be responsible for the design of the anatomically realistic brain network models based on experimental data. These models will be used to understand network dynamics that are involved in the processes of memory consolidation during sleep, as well as guide data analysis and produce novel experimental predictions. Qualified applicants are expected to have background and experience in neuroscience, computational neuroscience, physics/engineering and/or mathematics. Programming experience with C/C++ is required. Knowledge of PYTHON, PyTorch or MATLAB is a plus. The University of California offers excellent benefits. Salary is based on research experience. Applicants should send a brief statement of research interests, a CV and the names of three references to Maxim Bazhenov at mbazhenov(a)ucsd.edu -- Maxim Bazhenov, Ph.D. Professor, Department of Medicine, Neurosciences Graduate Program, UCSD, School of Medicine http://www.bazhlab.ucsd.edu/

March 31, 2022

Google Summer of Code: model and experimental data sharing on Open Source Brain

by Padraig Gleeson

--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 -----------------------------------------------------

March 31, 2022

Postdoc in Computer Vision / Machine Learning / Applied Mathematics

by Tony Lindeberg

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/

March 31, 2022

brain waves and topology

by Yuri Dabaghian

NIH-funded postdoctoral position is available in the group of Dr. Yuri Dabaghian at McGovern Medical School of the University of Texas, Houston. We are looking for scientists with research interests in neuroscience and mathematical physics, network dynamics, and topological data analyses. Some projects are based on studying electrophysiological data, some are theoretically motivated. We are specifically interested in circuit mechanisms of learning and memory and their involvement in neurological disorders, notably Alzheimer's Disease. Successful candidate will develop data-driven hippocampal neuronal network models, develop and creatively apply novel tools for the brain wave (EEG) analyses, Topological Data Analysis of spiking data, etc. Strong background in quantitative disciplines (a PhD and ongoing interest in computational neuroscience, physics or mathematics), plus willingness to do programming and to analyze experimental data is required. All appointments are renewable for at least four years given satisfactory performance. The salary is competitive. The postdoc will be integrated into the large, vibrant neuroscience community of the Texas Medical Center, participate in collaborations with groups at Baylor College of Medicine, Rice University, University of Houston. To apply, please send application materials including a detailed CV, a brief statement of research interests, and contact information of 3 references to Dr. Yuri Dabaghian at [Yuri.A.Dabaghian [at] uth.tmc.edu) The position is available immediately, until filled. For Additional information and informal inquiries, please contact Dr. Dabaghian. We strive for a diverse and inclusive environment, and encourage applications from members of any identity.

March 30, 2022