October 2023 - Comp-neuro - lists.cnsorg.org

Python Package: SER model
by Fabrizio Damicelli 08 Aug '24

08 Aug '24

Dear Computational Neuroscience Community, I would like to point you to a potentially useful Python Package that might be of interest for your research, especially in the realm dynamical models and spreading dynamics on networks. "ser": S(usceptible)E(xcited)R(efractory) model on graphs, a dynamical model of spreading excitations. Code Repository: https://github.com/fabridamicelli/ser As of today, a few people already trust it and the package registers >11K total downloads, ~500/month (pypi.org) and has been used already in a few research projects. A few interesting features: - It is light-weight and fast (`numba` accelerated), i.e. many experiments can be simply run on a laptop - Installation and getting started is easy: `pip install ser` - Example notebooks: https://github.com/fabridamicelli/ser/blob/main/examples The SER model is a classical cellular automaton model used to study all sorts of complex systems, ranging from forest fire dynamics to self-organized criticality in the brain. Despite of the simplicity of its setup, it is capable of generating complex emergent dynamics with absolutely non-trivial higher-order statistical properties. To learn more about the SER model and its applications, you might want to check out these references: - Messe et al. (2018). Toward a theory of coactivation patterns in excitable neural networks. doi.org/10.1371/journal.pcbi.1006084 - Haimovici et al. (2013). Brain Organization into Resting State Networks Emerges at Criticality on a Model of the Human Connectome. doi.org/10.1103/PhysRevLett.110.178101 - Damicelli et al. (2019). Topological reinforcement as a principle of modularity emergence in brain networks. doi.org/10.1162/netn_a_00085 Check it out and any feedback/suggestions/bug reports are more than welcome (simply open an issue: https://github.com/fabridamicelli/ser/issues) All the best, Fabrizio Damicelli

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Late-breaking poster abstract submission for the 32nd Annual Computational Neuroscience Meeting ends on June 15
by Rubchinsky, Leonid L 31 May '24

31 May '24

Dear Colleagues, We would like to remind that the late-breaking poster abstracts submission at CNS*2023 ends on June 15. CNS*2023, 32nd Annual Computational Neuroscience Meeting, will be in Leipzig, Germany, on July 15-19, 2023. The information about the meeting and abstract submission can be found here: Registration: https://ocns.memberclicks.net/cns-2023-registration Abstract submission: https://www.cnsorg.org/cns-2023-abstract-submission CNS*2023 information: https://www.cnsorg.org/cns-2023 With kind regards, Leonid Rubchinsky OCNS Vice President *********************** Leonid Rubchinsky, PhD Professor Department of Mathematical Sciences, Indiana University Purdue University Indianapolis Stark Neurosciences Research Institute, Indiana University School of Medicine 402 N. Blackford St Indianapolis, IN 46202-3216 lrubchin(a)iupui.edu http://www.math.iupui.edu/~lrubchin ***********************

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Postdoctoral Research Fellow in Biocomputation at the University of Hertfordshire, UK
by Volker Steuber 02 Apr '24

02 Apr '24

Post Title: Research Fellow in Biocomputation SBU/Department: School of Physics, Engineering and Computer Science ________________________________ FTE: 1 FTE (working 37 hours per week) Duration of Contract: Fixed term Contract (3 years) Salary: UH7 £36,333 pa with potential to progress to £43,155 pa on achieving designated skills and experience Annual Leave: 35 days plus standard public holidays and an additional 4 days including the closure of our office between Christmas and New Year Location: College Lane Campus, Hatfield, UK Closing Date: 14th June 2023 Interview Date: To be confirmed Reference Number: 048016 Date advert placed: 17th May 2023 Main duties and responsibilities We are seeking a full-time Research Fellow to join the Biocomputation Research Group in the School of Physics, Engineering and Computer Science at the University of Hertfordshire to conduct high-quality research in Computational Neuroscience. The successful candidate’s research will involve synergistic collaborations with a multidisciplinary team to investigate brain processes using methodologies such as computational modelling, machine learning and AI. Research to be conducted could, e.g., comprise modelling brain circuits like the olfactory bulb or the cerebellum and simulating and analysing their function. Additional impact could arise in machine learning, AI, data science, neurorobotics and neuromorphic computing. The successful candidate will be expected to establish a programme of research in collaboration with colleagues at UH and partner organisations in the UK and abroad. Leading the preparation and publication of research manuscripts is a key aspect of the role. Contributions to the preparation of research proposals and applications for funding to external bodies, such as the European Commission and the UK Research and Innovation (UKRI) are expected. The postholder will create opportunities to maximise research activities, capturing relevant evidence to support impact and engaging with external partners and stakeholders. Skill and experience required * Strong theoretical, computational and programming background in computational modelling and/or machine learning and/or data science and/or AI. * Background and expertise in computational neuroscience (e.g. spiking neural networks, brain function and anatomy, analysis of brain data). * Demonstrated experience to conduct independent research in computational neuroscience or a related field, e.g., through published research papers or monographs. * Applicants must be proficient in both written and oral English * The applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills. Qualifications required • An undergraduate honours degree (or equivalent) in Computer Science, Physics, Mathematics, Neuroscience, or a related discipline and a PhD (or expectation that one will soon be awarded) in a relevant discipline. An appointment to this role may require an Academic Technology Approval Scheme (ATAS) certificate. Contact Details/Informal Enquiries: Professor Volker Steuber, v.steuber(a)herts.ac.uk Professor Michael Schmuker, m.schmuker(a)herts.ac.uk Apply through: https://www.jobs.herts.ac.uk/go/048016 Our vision is to transform lives: UH is committed to Equality, Diversity and Inclusion and building a diverse community. We welcome applications from suitably qualified and eligible candidates regardless of their protected characteristics and recognise there are different ways applicants may achieve the criteria in this document. We offer a range of employee benefits including generous annual leave, flexible location opportunities within the UK, discounted Sports Village memberships and free Active Staff sessions, personal and professional development and family-friendly policies. Volker Steuber Professor of Computational Neuroscience Biocomputation Research Group School of Physics, Engineering and Computer Science University of Hertfordshire College Lane, Hatfield, AL10 9AB, UK biocomputation.herts.ac.uk<http://biocomputation.herts.ac.uk>

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Postdoc Position in Moral Artificial Intelligence (Jointly sponsored by Duke and CMU)
by Dr Jana Schaich Borg, Ph.D. 11 Mar '24

11 Mar '24

Postdoc available in our interdisciplinary Moral AI group! Description: We have an opening for a joint two-year postdoctoral position at the School of Computer Science at Carnegie Mellon University and the Social Science Research Institute, Duke Institute for Brain Sciences, and Kenan Institute for Ethics at Duke University (with the possibility of renewal for a third year). The postdoc can be employed through any of these departments in either University, depending on their preference. The candidate is expected to live in either Pittsburgh or Durham depending on their chosen home department, but will be asked to travel occasionally to the other location. The focus of the position is on conducting impactful research on moral artificial intelligence, addressing problems such as: Designing artificial intelligence systems to model and predict human moral judgments Designing effective elicitation mechanisms and interfaces to capture moral preferences Developing techniques for implementing and evaluating AI systems that are based on these modeled preferences, and assessing the dynamic impact of these systems on the preferences and behavior of users who interact with them Qualifications: Applicants should hold a Ph.D. in computer science, statistics, mathematics, computational neuroscience, computational cognitive science, or related technical fields and have expertise in Machine Learning and AI / statistics / data science. Additional background in moral psychology, moral philosophy, (AI or other) ethics, HCI, social decision-making and/or social science is preferred, but not required. Interested applicants should apply online <https://apply.interfolio.com/113237> <https://apply.interfolio.com/113237> (https://apply.interfolio.com/113237) or contact Dr. Jana Schaich Borg via email (js524(a)duke.edu) including a CV and statement of research interests, and the name of three referees that can provide letters of recommendation. We are strongly committed to a diverse academic environment and place high priority on attracting underrepresented candidates.

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MindCORE Fellow applications at Penn due Dec. 3
by Maria Geffen 01 Nov '23

01 Nov '23

MindCORE Research Fellowship for Postdoctoral Scholars MindCORE <https://mindcore.sas.upenn.edu/> (Mind Center for Outreach, Research, and Education) seeks to recruit outstanding postdoctoral researchers for our Postdoctoral Fellowship. Housed within the School of Arts & Sciences of the University of Pennsylvania, MindCORE is an interdisciplinary effort to understand human intelligence and behavior. Designed for individuals who have recently obtained a PhD degree in neuroscience, psychology, linguistics, philosophy, computer science, or other cognitive science discipline, the MindCORE Fellowship is a springboard for early researchers as they establish their own research program. Fellows are expected to pursue collaborative relationships with faculty working across disciplines at Penn, including faculty in computational neuroscience <https://cni.upenn.edu/people>. These collaborations may take different forms from engaging in research projects with multiple faculty independently, to generating new collaborative research that brings multiple faculty together, to contributing to interdisciplinary discussion and reading groups. Find a list of current and former MindCORE Fellows here <https://mindcore.sas.upenn.edu/people/>. MindCORE awards ~2 postdoctoral Fellowships per year. Positions may start as early as July 1, 2023. Benefits Fellows receive a competitive salary, relocation allowance, health insurance, plus a $20,000 research budget. Fellows also benefit from access to the greater community of academics including visiting scholars plus leading research facilities equipped with cutting-edge instrumentation all on an urban campus in a vibrant city. Fellows are invited to join regular working group meetings within their field plus career development workshops aimed at young researchers, and will be provided with a mentoring committee. Funding is provided in one-year terms renewable for up to three years. This is campus-based (not remote) position. Eligibility & Application · Applicants must have formally completed all requirements of the PhD degree and provide a copy of their diploma at the time of appointment. Penn has a five-year term limit for postdocs, so candidates ideally have 0-2 years of previous postdoc time. · Candidates must submit 1-2 page research statement that identifies at least three MindCORE faculty at Penn(https://mindcore.sas.upenn.edu/people/faculty-and-associates/ <https://mindcore.sas.upenn.edu/people/faculty-and-associates/>) with whom the applicant would be interested in collaborating, along with a CV, contact information for two referees, and a cover letter with a 1-2 paragraph diversity statement that includes past experiences and activities, and future plans to advance diversity, equity, and inclusion at Penn. Applicants should be mindful of the interdisciplinary backgrounds of the reviewers and make the proposals clear to readers. · Application documents should be saved with candidate’s Lastname_Firstname.pdf in one PDF file in this order: cover letter, research statement, CV, referees (name, affiliation, email address). Complete applications should be submitted through the form on our website:https://web.sas.upenn.edu/mindcore/post-doctoral-research-fellowshi… <https://web.sas.upenn.edu/mindcore/post-doctoral-research-fellowship/>. Questions not answered on our FAQ <https://urldefense.com/v3/__https:/bpb-us-w2.wpmucdn.com/web.sas.upenn.edu/…>, can be emailed to pennmindcore(a)sas.upenn.edu <mailto:pennmindcore@sas.upenn.edu>. · Applications due December 3, 2023. Selection All eligible and complete applications will be evaluated by the Selection Committee and are judged on the following criteria: · Scientific excellence · Potential to contribute to or lead within diverse community · Scientific match and interdisciplinarity · Career potential ______________________________ Maria N. Geffen, Ph.D. (she/her) Professor Department of Otorhinolaryngology Department of Neuroscience Department of Neurology Co-Director, Computational Neuroscience Initiative Stemmler Hall G14 3450 Hamilton Walk Philadelphia PA 19104 (215)898-0782 mgeffen(a)pennmedicine.upenn.edu <mailto:mgeffen@pennmedicine.upenn.edu> My zoom room <https://pennmedicine.zoom.us/my/mgeffen?pwd=eWVFbUJFUGRJZ3g1eU9YZEZic2VwZz09> Follow me @geffenlab@mastodon.world <https://mastodon.world/@geffenlab> http://hosting.med.upenn.edu/hearing <http://hosting.med.upenn.edu/hearing> Twitter: @neimarkgeffen <http://twitter.com/neimarkgeffen>

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Tenure-track position at UT Austin
by Weatherly, Christopher J 31 Oct '23

31 Oct '23

The Department of Neuroscience<https://neuroscience.utexas.edu/> at The University of Texas at Austin invites applications for a tenure-track faculty position at the rank of Assistant Professor. We seek outstanding candidates with innovative research proposals in all areas of neuroscience to build upon existing strengths in the fields of learning and memory, computational and theoretical neuroscience, cellular and sensory systems, addiction, developmental neuroscience, biophysics, and synaptic plasticity. This position comprises a highly competitive salary and start-up funds. We expect new faculty to develop and maintain an ambitious research program within a vibrant and collegial academic environment. The department values candidates who have demonstrated a commitment to student and trainee mentorship. Ranked among the top ten public universities and the flagship campus of The University of Texas System, UT Austin is distinguished by a world-class faculty engaged in highly collaborative and interdisciplinary research among programs in Neuroscience, Psychology, Computer Science, Statistics, Mathematics, Engineering, Physics, Chemistry, and Molecular Biosciences. Close ties with the new Dell Medical School provide additional opportunities for collaboration with translational researchers in Neurology, Neurosurgery, and Psychiatry. Full job posting: https://faculty.utexas.edu/career/122847 --- Christopher Weatherly Executive Assistant to Robert Messing, MD Department of Neuroscience - The University of Texas at Austin

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Call for Participation COMPLEX NETWORKS 2023 Menton France November 28 - 30, 2023
by Hocine Cherifi 31 Oct '23

31 Oct '23

*12th** International Conference on Complex Networks & Their Applications* *Menton Riviera* <https://www.menton-riviera-merveilles.co.uk/>*, France *November 28 - 30, 2023 COMPLEX NETWORKS 2023 <http://www.complexnetworks.org/> *Registration:* https://complexnetworks.org/registration/ *See the detailed program at :* https://complexnetworks.org/program/ *KEYNOTE SPEAKERS* Michael Bronstein <https://www.cs.ox.ac.uk/people/michael.bronstein/>* - *Univ. of Oxford UK - *Physics-inspired Graph Neural Networks* <https://complexnetworks.org/keynote-speakers-3/> Kathleen Carley <https://www.cylab.cmu.edu/directory/bios/carley-kathleen.html> - Carnegie Mellon Univ. USA - *Coupling in High Dimensional Networks* <https://complexnetworks.org/keynote-speakers-3/> Manlio De Domenico <https://manliodedomenico.com/> Univ. of Padua Italy: *An Emerging Framework for the Functional Analysis of Complex* <https://complexnetworks.org/keynote-speakers-3/>* Interconnected Systems* Danai Koutra <http://web.eecs.umich.edu/~dkoutra/> - Univ. of Michigan USA - *Advances in Graph Neural Networks: Heterophily and Beyond* <https://complexnetworks.org/keynote-speakers-3/> Romualdo Pastor-Satorras <http://www.fen.upc.edu/~romu/> - UPC Spain - *Opinion Depolarization in Interdependent Topics and the Effects of Heterogeneous Social Interactions* <https://complexnetworks.org/keynote-speakers-3/> Tao Zhou <https://scholar.google.com/citations?user=MXgWgmEAAAAJ&hl=en> - USTC China - *Recent Debates in Link Prediction* <https://complexnetworks.org/keynote-speakers-3/> *TUTORIALS (November 27, 2023)* Tiago de Paula Peixoto <https://skewed.de/tiago> - CEU Vienna Austria - *Network Inference and Reconstruction* <https://complexnetworks.org/tutorials/> Maria Liakata <https://www.turing.ac.uk/people/researchers/maria-liakata> - Queen Mary University of London UK - *Longitudinal language processing from user generated content* <https://complexnetworks.org/tutorials/> Best regards, and looking forward to seeing you at COMPLEX NETWORKS 2023. Hocine Cherifi, Luis M. Rocha COMPLEX NETWORKS 2023 General Chairs Join us at COMPLEX NETWORKS 2023 <https://www.complexnetworks.org/> *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comté Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Editor in Chief Applied Network Science <https://appliednetsci.springeropen.com/> Plos Complex Systems <https://plos.org/complex-systems-research-journal/#:~:text=PLOS%20Complex%2….> Editorial Board member PLOS One <https://journals.plos.org/plosone/>, IEEE ACCESS <https://ieeeaccess.ieee.org/?http%3A%2F%2Fieeeaccess_ieee_org%2F>, Scientific Reports <https://www.nature.com/srep/>, Journal of Imaging <https://www.mdpi.com/journal/jimaging>, Quality and Quantity <https://www.springer.com/journal/11135/>, Computational Social Networks <https://computationalsocialnetworks.springeropen.com/>, Complex Systems <https://www.complex-systems.com/>

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faculty position in Computational Cognitive Neuroscience at UC Davis (Applications due Oct. 1)
by Mark Steven Goldman 31 Oct '23

31 Oct '23

We are pleased to announce a faculty position in Computational Cognitive Neuroscience, to reside in the Department of Psychology. This hire continues our major expansion in Computational Neuroscience, with the hire joining the 6 current computational/theoretical neuroscience faculty at UC Davis. The application deadline (strict!) is Sunday, October 1. More information is provided in the advertisement below: https://recruit.ucdavis.edu/JPF05981 We look forward to your applications, Randy O'Reilly Rishi Chaudhuri Mark Goldman

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Workshop at CNS2023: Neuroscience Gateway Enabling Neuroscience Software Dissemination and Large-Scale Neuronal Modeling and Data Processing on Supercomputers
by Majumdar, Amitava 31 Oct '23

31 Oct '23

Please join us at the workshop titled: "Neuroscience Gateway Enabling Neuroscience Software Dissemination and Large-Scale Neuronal Modeling and Data Processing on Supercomputers " at CNS 2023, on July 19th, 2023, in Leipzig, Germany. Speakers include neuroscientists who are using the Neuroscience Gateway as well as Software developers whose software is disseminated via the Neuroscience Gateway. Detailed description of the workshop with list of speakers, title and abstract of the talks are available here: https://www.nsgportal.org/CNS2023NSGWorkshopWebPage.htm Best regards. Workshop Organizers Amit Majumdar, Subha Sivagnanam, Kenneth Yoshimoto, San Diego Supercomputer Center, University of California San Diego Ted Carnevale, Yale University

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SNUFA 2023 program now online
by Friedemann Zenke 30 Oct '23

30 Oct '23

Dear all, The SNUFA 2023 workshop program is now online (https://snufa.net/2023/) Like every year, we look forward to two afternoons packed with "spiking networks as universal function approximators." Date and time: Tue, 7 Nov 2023 15:00 - Wed, 8 Nov 2023 18:30 CET Location: online Details: https://snufa.net/2023/ Register (for free) for the online event: https://www.eventbrite.co.uk/e/snufa-2023-tickets-675972952297 Program: November 7th (Times in CET) 14:00 Welcome by the organizers Session 1 (Chair: Charlotte Frenkel) 14:10 Rodolphe Sepulchre, KU Leuven and University of Cambridge (invited) 14:55 Veronika Koren -- Efficient computing of high-dimensional neural representations with biologically plausible E-I spiking networks 15:15 Alessio Quaresima, Hartmut Fitz, Renato Duarte, Peter Hagoort, Karl Magnus Petersson -- Dendrites support formation and reactivation of sequential memories through Hebbian plasticity 15:35 Break (30mins) Session 2 (Chair: Friedemann Zenke) 16:05 Gabriel Ocker, Boston University (invited) 16:50 Maayan Levy & Tim P. Vogels -- Capacity of a spiking network with preserved weight distribution: a game-theory-inspired study 17:10 Flash talks by selected poster presenters 17:30 Break (30mins) 18:00 Poster session (Zoom) November 8th (Times in CET) 14:00 Welcome to day two Session 3 (Chair: Dan Goodman) 14:05 Melika Payvand, INI, Zurich (invited) 14:50 Ilyass Hammouamri -- Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings 15:10 Justus Huebotter, Pablo Lanillos, Serge Thill, Marcel van Gerven -- Training Spiking Neural Networks for Continuous Control with Surrogate Gradients 15:30 Break (30mins) Session 4 (Chair: Emre Neftci) 16:00 Jeff Krichmar, UC Irvine (invited) 16:45 Alexander Efremov, Martino Sorbaro, Pau Vilimelis Aceituno, Benjamin Grewe -- Training fast spiking networks through STDP and control feedback 17:05 Antony W. N’dri, Céline Teulière and Jochen Triesch -- Combining various types of spike timing-dependent plasticity to learn efficient neural codes 17:25 Closing remarks Best wishes from your friendly organizers, Emre Neftci, Charlotte Frenkel, Dan Goodman, and Friedemann Zenke

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