- Comp-neuro - lists.cnsorg.org

Endowed Professorship "Machine Learning for Clinical Neuroscience"
by Philipp Berens 10 Jul '23

10 Jul '23

Dear all, we are currently advertising an Endowed professorship "Machine Learning for Clinical Neuroscience" (https://www.academics.com/jobs/w3-stiftungsprofessur-fuer-maschinelles-lern…) at the University of Tübingen. We are looking for candidates that perform innovative research on the application and development of new machine learning methods in clinical neuroscience, in particular for early detection and prediction of disease progression. This can include work on topics such as explainability, safety and robustness of machine learning methods in clinical settings. It would be great if candidates had worked with multimodal data with clinical relevance (e. g. MRI, fMRI, EEG, electrophysiology, omics data, data from sensors of wearables) as well as cohort data (UKBiobank, NAKO, etc.). Tübingen offers a first-rate environment at the intersection of neuroscience and AI/ML research with the Excellence Cluster for Machine Learning in Science, the Tübingen AI Center, the Max Planck Institutes for Intelligent Systems and Biological Cybernetics, the Hertie Institute for Clinical Brain Research and many other institutions! We are looking forward to your application by July 20th. Best Philipp -- Professor of Data Science, Director Hertie Institute for AI in Brain Health Medical Faculty of the University of Tübingen www.berenslab.org

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Workshop on Neuro-Inspired Topology and Machine Learning at CNS 2023
by Neymotin, Samuel (NKI) 08 Jul '23

08 Jul '23

We invite the computational neuroscience community to join us at our workshop on Neuro-inspired topology and machine learning at CNS 2023, on July 19th, 2023 in Leipzig, Germany. Workshop Description: Mathematics, machine learning, and computational neuroscience have long been intertwined. Mathematical tools such as graph theory, information theory and dynamical systems have been used to model neural activity. Similarly, modern machine learning approaches have been inspired by neuroscience and have been used to better understand brain connectivity and dynamics. These three research facets play off of each other to advance each field individually and concurrently. The goal of this workshop is to bring computational neuroscientists, mathematicians, and computer scientists together to communicate research around their expertise. Additionally, it will serve as a venue to discuss avenues of future research impacting computational neuroscience and mathematics while advancing machine learning and artificial intelligence methods. Speakers include: Max Bazhenov, Vasileios Christopoulos, Claudia Clopath, Salvador Dura-Burnal, Daniela Egas-Santander, Celia Hacker, Erik Hermansen, Bill Lytton, Robert McDougal, Aitor Morales-Gregorio, Manish Saggar, Brittany Story, and Nick Tolley Full details including schedule are available here: https://sites.google.com/view/nitmlcns2023/home The organizers, Brittany Story, Vasileios Maroulas, Sam Neymotin ________________________________ IMPORTANT NOTICE: This e-mail is meant only for the use of the intended recipient. It may contain confidential information which is legally privileged or otherwise protected by law. If you received this e-mail in error or from someone who was not authorized to send it to you, you are strictly prohibited from reviewing, using, disseminating, distributing or copying the e-mail. PLEASE NOTIFY US IMMEDIATELY OF THE ERROR BY RETURN E-MAIL AND DELETE THIS MESSAGE FROM YOUR SYSTEM. Thank you for your cooperation.

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Comp. Neurosci. postdoc - NY
by Neymotin, Samuel (NKI) 07 Jul '23

07 Jul '23

Postdoctoral scientist positions are available at the Nathan Kline Institute (NKI) for Psychiatric Research (https://www.nki.rfmh.org/) to work on computational neuroscience research funded by NIH and DoD grants. Applicants should have a PhD in computational neuroscience (or a related field), strong background in multiscale modeling using NEURON/NetPyNE, Python software development, neural/electrophysiology data analysis, machine learning, and writing/presenting research. Applicants should send the following information to the computational neuroscience lab PI (Sam Neymotin; samuel.neymotin(a)nki.rfmh.org) 1. Curriculum vitae (.pdf, required) 2. Cover letter describing your research interests, relevant experience, and career goals 3. At least one academic writing sample 4. Referrer's Contact Information/Recommendation Letter Applications will be considered and interviews offered (for qualified applicants) as they are received. ________________________________ IMPORTANT NOTICE: This e-mail is meant only for the use of the intended recipient. It may contain confidential information which is legally privileged or otherwise protected by law. If you received this e-mail in error or from someone who was not authorized to send it to you, you are strictly prohibited from reviewing, using, disseminating, distributing or copying the e-mail. PLEASE NOTIFY US IMMEDIATELY OF THE ERROR BY RETURN E-MAIL AND DELETE THIS MESSAGE FROM YOUR SYSTEM. Thank you for your cooperation.

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Workshop on neuronal optimality and trade-offs at CNS*2023
by Jedlicka, Peter 07 Jul '23

07 Jul '23

Dear all, Join us at CNS*2023 in Leipzig on July 18th and 19th for the workshop W06: Optimality, evolutionary trade-offs, Pareto theory and degeneracy in neuronal modelling<https://www.treestoolbox.org/CNS2023_pareto_workshop/program.html>. Nervous systems, like any evolved structure, encounter unavoidable trade-offs between multiple tasks. They must fulfil their fundamental computational functions whilst consuming as little energy as possible and remaining robust to potential environmental changes. These tasks are often in direct opposition to one another, and a general quantification of the relative importance of individual optimisation targets is non-trivial. The problem is complicated by the degeneracy seen across neurons and circuits, where multiple different combinations of components can lead to similar functional behaviours. Pareto optimality might provide a useful framework to analyse neurobiological systems from biophysically detailed cells to large-scale network structures that combine high-dimensional parameter spaces with high-dimensional objective spaces. Pareto, or multi-objective, optimality can, for example, help to identify geometrically simple subspaces of neuronal models that cannot be improved upon for all relevant objectives. This workshop aims to discuss applications of Pareto optimality to the trade-offs encountered by diverse nervous systems. The talks and discussions will also address the trade-off between functional effectiveness and energetic efficiency and the concept of metabolically efficient information processing. Registration for the workshops at CNS 2023 is required and can be done at: https://ocns.memberclicks.net/cns-2023-registration Speakers include: Astrid Prinz, Anna Levina, Timothy O'Leary, Marcel Oberländer, Arnd Roth, Rishikesh Narayanan, Suhita Nadkarni, Albert Gidon, Zahid Padamsey, Wiktor Mlynarski, Dylan Festa Full details are available at: https://www.treestoolbox.org/CNS2023_pareto_workshop/index.html and https://cns2023.sched.com/event/1O0MO/w06-optimality-evolutionary-trade-off… Hope to see you there! Alex Bird, Philipp Norton, Peter Jedlicka, and Susanne Schreiber -- Prof. Dr. Peter Jedlicka Computer-Based Modelling in the field of 3R Animal Protection Faculty of Medicine Justus Liebig University Giessen Rudolf-Buchheim-Straße 6 35392 Gießen Phone: ++49 (0)641 9941387 Fax: ++49 (0) 641 9941359 Email: Peter.Jedlicka(a)informatik.med.uni-giessen.de 3R Centre of Justus Liebig University Giessen Interdisciplinary Centre for 3Rs in Animal Research (ICAR3R) Frankfurter Straße 104 35392 Giessen (Germany) www.ICAR.de<https://www.uni-giessen.de/de/fbz/fb11/institute/computerbasiertes-modellin…>

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2 Fully funded PhD positions in testing of AI-based systems at Università della Svizzera italiana (Switzerland)
by Nargiz Humbatova 07 Jul '23

07 Jul '23

Dear All, The TAU (Testing AUtomated) research group at the Software Institute <https://www.si.usi.ch/> of Università della Svizzera italiana (USI) <https://www.usi.ch/> investigates novel testing techniques to improve the robustness and security of systems based on deep learning. We offer two PhD positions in the following topics: 1. Search-based test case generation for vulnerability exposure in deep learning based systems and creation of a robustness assessment benchmark. The position is funded by the Horizon <https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/…> European project Sec4AI4Sec <https://search.usi.ch/en/projects/3018/cybersecurity-for-ai-augmented-syste…> which aims to support security testing of AI-based systems; 2. Automated partition of a complex input space into a topographical map consisting of regions that maximise the likelihood of fault exposure when test cases are sampled from unexplored or boundary map regions. This position is funded by the SNSF <https://snf.ch/en> project TopoScope <https://search.usi.ch/en/projects/3030/toposcope-a-topographical-approach-t…>, aiming at redefining the testing activities as the exploration of a topographical map of the input space. We are scouting excellent applicants for these two PhD positions. Successful candidates will work at the Software Institute of Università della Svizzera italiana (USI) in Lugano, Switzerland, under the supervision of Prof. Paolo Tonella <http://inf.usi.ch/faculty/tonella> and the co-supervision of Dr. Nargiz Humbatova <http://usi.to/pio> and Dr. Jinhan Kim. At USI, PhD salaries are highly competitive (around 50 kCHF), in accordance with the Swiss standards. Ideally, the selected candidates are expected to start on October 1st, 2023, but later starts can also be considered. The duration of the PhD contract will be 4 years. How to apply? Applications for PhD positions should include a curriculum vitae and the exam transcripts. PhD candidates should hold an MSc degree in Computer Science by Fall 2023. Applications can be sent to paolo.tonella(a)usi.com. The call will remain open until all positions are filled, but *priority will be given to earlier applications*. Best Regards, Nargiz

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Master of Science "Modeling for Neuronal and Cognitive Systems" at Université Côte d'Azur - Apply until the 20th of July!
by Chloe Bourgeois 07 Jul '23

07 Jul '23

The M.Sc. program "Modeling for Neuronal and Cognitive Systems" at Université Côte d'Azur is still recruiting its new students! This international Master of science is interdisciplinary and related to computational approaches in neuroscience/cognitive science. Check our website for eligibility criteria and more info about the program: https://univ-cotedazur.eu/msc/modeling-for-neuronal-and-cognitive-systems Applications must be submitted via the online platform ecandidat<https://ecandidat-uca1.univ-cotedazur.fr/#!accueilView>, until the 20th of July 2023. Thanks for sharing this announcement as widely as possible. Contact: msc-mod4neucog(a)univ-cotedazur.fr<mailto:msc-mod4neucog@univ-cotedazur.fr> Kind regards, -- Chloé Bourgeois Responsable Administrative Institut NeuroMod<https://neuromod.univ-cotedazur.eu/> 2004 Route des Lucioles 06902 Sophia-Antipolis Tel. : +33 (0)4 89 73 24 99

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CNS 2023 Tutorial on Dynamical Systems Methods
by Richard Gast 06 Jul '23

06 Jul '23

Dear members of the computational neuroscience community, I would like to draw your attention to a tutorial that Hil G.E. Meijer, Bastian Pietras, and I will offer at the first day of CNS 2023: "Applied Dynamical Systems Methods in Neuroscience''. In this tutorial, we will explain basic dynamical systems concepts and analysis methods at the example of single neurons, neural networks, and mean-field equations of neural networks. The main goals of the tutorial are (i) to provide the audience with an intuition of how neural systems can be studied via mathematical models, (ii) to explain how we can analyze parameter dependencies of these mathematical models, and (iii) to provide numerical recipes, and software solutions to carry out these analysis methods. For more details on the tutorial, have a look at our website: https://cns2023.sched.com/event/cbd810bd0ffd6a59869a5f89fbf17b58 If you are planning to participate in the hands-on sessions, I advise you to follow the preparation instructions on that website! See you in Leipzig, Richard Gast

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SUBMIT YOUR WORK TO COMPLEX NETWORKS 2023 BEFORE SEPT. 02, 2023
by Hocine Cherifi 06 Jul '23

06 Jul '23

*12* *th **International Conference on Complex Networks & Their Applications* Menton Riviera <https://www.menton-riviera-merveilles.co.uk/>, France November 28 - 30, 2023 COMPLEX NETWORKS 2023 <https://complexnetworks.org/> You are cordially invited to submit your contribution until *September 02, 2023*. *SPEAKERS* · Michael Bronstein <https://www.cs.ox.ac.uk/people/michael.bronstein/> University of Oxford UK · Kathleen Carley <https://www.cylab.cmu.edu/directory/bios/carley-kathleen.html> Carnegie Mellon University USA · Manlio De Domenico <https://manliodedomenico.com/> University of Padua Italy · Danai Koutra <http://web.eecs.umich.edu/~dkoutra/> University of Michigan USA · Romualdo Pastor-Satorras <http://www.fen.upc.edu/~romu/> Univ. Politècnica de Catalunya Spain · Tao Zhou <https://scholar.google.com/citations?user=MXgWgmEAAAAJ&hl=en> USTC China *TUTORIALS* · Tiago de Paula Peixoto <https://skewed.de/tiago> CEU Vienna Austria · Maria Liakata <https://www.turing.ac.uk/people/researchers/maria-liakata> Queen Mary University of London UK *PUBLICATION* Full papers (not previously published up to 12 pages) and Extended Abstracts (about published or unpublished research up to 4 pages) are welcome. · *Papers *will be included in the conference *proceedings edited by Springer* · *Extended abstracts* will be published in the *Book of Abstracts (with ISBN)* Extended versions will be invited for publication in *special issues of international journals:* o Applied Network Science <https://appliednetsci.springeropen.com/> edited by Springer o Advances in Complex Systems <https://www.worldscientific.com/toc/acs/24/02> edited by World Scientific o Complex Systems <https://www.complex-systems.com/about/> o Entropy <https://www.mdpi.com/journal/entropy> edited by MDPI o PLOS <https://journals.plos.org/plosone/> one <https://journals.plos.org/plosone/> o Social Network Analysis and Mining <https://link.springer.com/journal/13278> edited by Springer *SUBMISSION* https://complexnetworks.org/submission/ *TOPICS* *Topics include, but are not limited to: * o Models of Complex Networks o Structural Network Properties and Analysis o Epidemics o Community Structure o Motifs o Network Mining o Network embedding o Machine learning with graphs o Dynamics and Evolution Patterns of Complex Networks o Link Prediction o Multilayer Networks o Controllability o Synchronization o Visual Representation o Large-scale Graph Analytics o Social Reputation, Influence, and Trust o Information Spreading in Social Media o Rumour and Viral Marketing in Social Networks o Recommendation Systems o Financial and Economic Networks o Mobility o Biological and Technological Networks o Mobile call Networks o Bioinformatics o Earth Sciences Applications o Resilience and Robustness of Complex Networks o Networks for Physical Infrastructures o Networks, Smart Cities and Smart Grids o Political networks o Supply chain networks o Complex networks and information systems o Complex networks and CPS/IoT o Graph signal processing o Cognitive Network Science o Network Medicine o Network Neuroscience o Quantifying success through network analysis o Temporal and spatial networks o Historical Networks o Graph-Based Natural Language Processing *GENERAL CHAIRS* Hocine Cherifi (University of Burgundy, France) Luis M. Rocha (Binghamton University, USA)

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Announcing the fourth Canadian Computational Neuroscience Spotlight!
by Scott Rich 05 Jul '23

05 Jul '23

Dear Comp-Neuro mailing list members, We are pleased to announce the fourth edition of the Canadian Computational Neuroscience Spotlight (CCNS) <https://www.crowdcast.io/c/ccnsv4> will take place this fall, October 5 and 6. The meeting will once again take place entirely virtually using the Crowdcast platform, and parlay the savings from this virtual setting into no registration fees for attendees. CCNS was created in the immediate aftermath of the initial COVID-19 lockdowns, which caused the cancellation of multiple conferences within the Canadian neuroscience community. As one of the first brand-new meetings created with the virtual space in mind <https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008…>, CCNS distinguished itself by exploiting the online setting to engage an international audience, increase content accessibility through no registration fees and permanently available replays, and place an added spotlight on trainee contributions. Two successful follow-up editions of the meeting took place in 2021 and 2022. CCNSv4 will highlight three fantastic keynote speakers: Dr. Rick Adams <https://www.ucl.ac.uk/mental-health/mental-health-awareness-week/meet-dr-ri…>, Dr. Jeremie Lefebvre <https://www.uottawa.ca/brain/people/lefebvre-jeremie>, and Dr. Sarah Muldoon <https://www.buffalo.edu/cas/math/people/faculty/muldoon.html>. The keynote talks will be complemented by interactive workshop sessions led by our organizing committee. The remainder of the program will highlight trainee contributions, both through spotlighted talks and parallel sessions. The preliminary program can be seen after registration through the Crowdcast platform <https://www.crowdcast.io/c/ccnsv4>, and further details will be added to our homepage (ccnsmeeting.ca) in the coming weeks. Trainees interested in presenting are encouraged to first register for the conference via Crowdcast (crowdcast.io/c/ccnsv4 <https://www.crowdcast.io/c/ccnsv4>) and then complete this Google Form <https://docs.google.com/forms/d/e/1FAIpQLSeev-EA5ccwKapzRV43xD4NfDYGyDeAiWp…>. Submissions received by 5 p.m. EDT on September 1 will be considered for longer “spotlight” presentations. We anticipate all submissions that reasonably fall under the broad banner of “computational neuroscience” will be accepted unless demand far exceeds our expectations. A final schedule for the meeting, including the schedule of trainee talks, will be made available no later than September 18. Please feel free to reach out to the organizing committee if you have any questions about this meeting, and we look forward to seeing you at CCNSv4! Sincerely, The CCNS Organizing Committee: Scott Rich <http://scottrich.strikingly.com/>, Ph.D. Research Fellow, SickKids Research Institute. Andreea Diaconescu <https://cognemo.com/>, Ph.D. Independent Scientist, Krembil Center for Neuroinformatics at CAMH. John Griffiths <https://t.co/AlUQymEUae?amp=1>, Ph.D. Independent Scientist, Krembil Center for Neuroinformatics at CAMH. Milad Lankarany <https://sites.google.com/view/lnsbsp/home>, Ph.D. Scientist, Krembil Research Institute.

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Invitation for Hands-on Tutorial on PyNN at CNS*2023 Inbox
by CHITARANJAN MAHAPATRA 05 Jul '23

05 Jul '23

*Dear all,* *We are delighted to announce that a half-day tutorial titled "Hands-on Tutorial on PyNN: A Simulator-Independent Language for Building Neuronal Network Models" will be held at the 32nd Annual Computational Neuroscience Meeting (CNS*2023 conference) in Leipzig, Germany. We invite all registered participants to join the tutorial, which will take place on the first day of the meeting, 15 July 2023, just before the main event.* *Computational neuroscientists have developed a diversity of software platforms for simulating neural network models at different scales. However, each simulator has its own programming or configuration language, leading to considerable difficulty in porting models from one simulator to another. A common programming interface to multiple simulators would help to reduce or eliminate the problems of simulator diversity while retaining the benefits. PyNN is such an interface, making it possible to write a simulation script once, using the Python programming language, and run it without modification on any supported simulator (currently including NEURON, NEST, Brian, and the SpiNNaker and BrainScaleS neuromorphic hardware systems).* *Prerequisites:* *Basic familiarity with the Python programming language* *Useful links:* *Main website: https://ebrains.eu/service/pynn/ <https://ebrains.eu/service/pynn/>* *Documentation: http://neuralensemble.org/docs/PyNN/ <http://neuralensemble.org/docs/PyNN/>* *Download: https://pypi.org/project/PyNN/ <https://pypi.org/project/PyNN/>* *Organizers:* *Chitaranjan Mahapatra (Neuroinformatics Group, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, France)* *Shailesh Appukuttan (Neuroinformatics Group, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, France)* *Andrew Davison (Neuroinformatics Group, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, France)* *Speakers/Instructors:* *Chitaranjan Mahapatra, Speaker (Paris-Saclay Institute of Neuroscience, France)* *Nitin Anisetty, Instructor (Indian Institute of Technology Bombay, India)* *We also invite all tutorial participants to create a free EBRAINS account using an institutional email address. By doing so, you will gain complete access to EBRAINS tools and services.* *Best regards,* *Chitraranjan* ------------------------------------------------------------------------------------------------- Chitaranjan Mahapatra

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