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Tenure-track Assistant Professor position in Mathematical and Statistical Foundations of Big Data at Georgia State University
by Yaroslav Molkov Oct. 3, 2023

Oct. 3, 2023

The Department of Mathematics and Statistics at Georgia State University invites applications to fill a tenure-track Assistant Professor position in Mathematical and Statistical Foundations of Big Data with a start date of August 2024. Candidates in all areas of mathematics and statistics related to big data analysis and processing are encouraged to apply. Essential Qualifications: - Ph.D. in Mathematics, Statistics, Data Science, or a closely related field; - Ability to teach core undergraduate and graduate mathematics and/or statistics courses; - Experience in research and teaching in the field of mathematical and statistical foundations of big data. Preferred Qualifications: - Strong desire to work in a cross-disciplinary, collaborative environment; - An experience in supervising undergraduate and graduate students. The Department offers BS in Mathematics, MS in Mathematics with no concentration or concentrations in Bioinformatics, Biostatistics, Discrete Mathematics, Scientific Computing, Statistics, Applied Mathematics, as well as Statistics and Allied Fields, and Ph.D. in Mathematics and Statistics with concentrations in Mathematics, Applied Mathematics, Bioinformatics, and Biostatistics. Faculty members in the department have established nationally and internationally recognized research programs in both mathematics and statistics, including applied statistics, biostatistics, data science, dynamical systems, complex networks, machine learning, inverse problems, mathematical biology, optimization, computational mathematics, systems biology, modeling neural, cardiovascular, and multi-organ systems, physical and biomedical image analysis. Additionally, the Department collaborates with other GSU departments in epidemiology, pathogen genetics, immunology, inflammation, and translational biomedical sciences. For more information, please visit our website at https://www.mathstat.gsu.edu/. GSU, the largest university in Georgia, is an enterprising urban R1 research university located in downtown Atlanta and home to one of the most diverse student bodies in the country. It is a national leader in applying innovative measures to drive student success and research growth, as well as generating innovative research. Applicants should submit: 1) a cover letter outlining qualifications and research interests, 2) a curriculum vitae with a publication list and (optional) a teaching and funding list, 3) a research statement, including current and future research agenda, and 4) a teaching statement with evidence of aptitude or ability to teach at the undergraduate and graduate levels. All materials should be submitted online at http://www.mathjobs.org. Applicants should also arrange for three letters of recommendation to be submitted online at http://www.mathjobs.org. A formal review of applications will begin on November 15, 2023, and will continue until the position is filled. An offer of employment will be conditional upon background verification. Georgia State University is an Equal Opportunity Employer and does not discriminate against applicants due to race, ethnicity, gender, veteran status, or on the basis of disability or any other federal, state, or local protected class.

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lecture notes published
by Michael Biehl Oct. 3, 2023

Oct. 3, 2023

Dear colleagues. My lecture notes "The Shallow and the Deep - A biased introduction to neural networks and old school machine learning" have been published by University of Groningen Press: https://books.ugp.rug.nl/index.php/ugp/catalog/book/130 The book is available as open access e-pub (pdf) and non-profit print-on-demand (softcover) from various sources, see https://www.cs.rug.nl/~biehl/mpubl.html for some links. Best wishes, Michael -- --------------------------------------------------- Prof. Dr. Michael Biehl Bernoulli Institute for Mathematics, Computer Science & Artificial Intelligence P.O. Box 407, 9700 AK Groningen, NL https://www.cs.rug.nl/~biehl m.biehl(a)rug.nl

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Call for Participation COMPLEX NETWORKS 2023 Menton France November 28 - 30, 2023
by Hocine Cherifi Oct. 3, 2023

Oct. 3, 2023

*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/ Early registration deadline: *October 13, 2023* *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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COSYNE 2024: Meeting announcement; Call for Abstracts
by Tomas Hromadka Sept. 30, 2023

Sept. 30, 2023

==================================================== Computational and Systems Neuroscience 2024 (Cosyne) MAIN MEETING 29 February - 03 March 2024 Lisbon, Portugal WORKSHOPS 04 March - 05 March 2024 Cascais, Portugal www.cosyne.org ==================================================== ---------------------------------------------------- MEETING ANNOUNCEMENT ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks is selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. All abstract submissions will be reviewed double blind. The deadline for Abstract submission will be 19 November 2023. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, neuromodulation, and computation with spiking networks. We would like to foster increased participation from experimental groups as well as computational ones. Please circulate widely and encourage your students and postdocs to apply. IMPORTANT DATES Abstract submission opens: 04 October 2023 Abstract submission deadline: 19 November 2023 When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. ORGANIZING COMMITTEE General Chairs: Jessica Cardin (Yale) and Blake Richards (McGill) Program Chairs: Bing Brunton (U Washington) and Chandramouli Chandrasekaran (Boston U) Workshop Chairs: SueYeon Chung (NYU) and Andrew Saxe (Oxford) Tutorial Chair: Il Memming Park (Champalimaud) DEIA Committee: Hysell Oviedo (Washington U) and Luke Sjulson (Albert Einstein) Fundraising Chair: Michael Long (NYU) Social Media Chair: Sabera Talukder (Caltech) Audio-Video Media Chair: Carlos Stein Brito (EPFL) Poster Design: Maja Bialon PROGRAM COMMITTEE Bing Brunton (U Washington) Co-chair Chandramouli Chandrasekaran (Boston U) Co-chair Alex Cayco Gajic (Ecole Normale Superieure) Hannah Choi (Gatech) Brian DePasquale (Boston U) Sridhar Devarajan (Indian Inst Sci) Laura Driscoll (Stanford) Ann Duan (UCL) Lea Duncker (Stanford) Annegret Falkner (Princeton) Juan Gallego (Imperial) Matthew Golub (U Washington) Kameron Harris (W Washington U) Santiago Jaramillo (U Oregon) Jonathan Kao (UCLA) Ann Kennedy (Northwestern) Guillaume Lajoie (MILA) Camilo Libedinsky (National U Singapore) Scott Linderman (Stanford) Ashok Litwin-Kumar (Columbia) Emily Mackevicius (Basis) Leenoy Meshulam (U Washington) Jonathan Michaels (York U) James Murray (U Oregon) Hendrikje Nienborg (NIH) Gouki Okazawa (Chinese Acad Sci) Chethan Pandarinath (Emory) Il Memming Park (Champalimaud) Hannah Payne (Columbia) Talmo Pereira (Salk) Supratim Ray (Indian Inst Sci) Erin Rich (Mount Sinai) Ben Scott (Boston U) Alireza Soltani (Dartmouth) Nicholas Steinmetz (U Washington) Marie Suver (Vanderbilt) Aparna Suvrathan (McGill) John Tuthill (U Washington) Ali Weber (Bryn Mawr) Brady Weissbourd (MIT) Alex Williams (NYU) Klaus Wimmer (CRM) Brad Wyble (Penn State) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Anne-Marie Oswald (U Pittsburgh) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT meeting [at] cosyne.org ----------------------------------------------------- COSYNE MAILING LISTS ----------------------------------------------------- Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> About-> Mailing lists for details.

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Open PhD position - Spiking Neural Networks for scalable learning neuromorphics
by Robert Legenstein Sept. 29, 2023

Sept. 29, 2023

The Lab of Robert Legenstein at Graz University of Technology (Austria) is offering a funded PhD position in the areas Spiking Neural Networks/Machine Learning/Brain Models/Neuromorphic Hardware. A background in Machine Learning, Computer Science, or Mathematics is desirable, as well as evidence for excellent prior performance as a student. The successful candidate will work on learning algorithms for spiking neural networks in the international consortium of the international project "Scalable Learning Neuromorphics". We will develop in this project learning algorithms for spiking neural networks for memristive hardware implementations. Please send your application including a CV, any prior thesis and/or work by October 20 to robert.legenstein(a)igi.tugraz.at Scalable Learning Neuromorphics project description: This project aims to develop scalable Spiking Neural Networks (SNNs) by leveraging the integration of 3D memristors, thereby overcoming limitations of conventional Artificial Neural Networks (ANNs). Positioned at the intersection of artificial intelligence and brain-inspired computing, the initiative focuses on innovative SNN training methods, optimizing recurrent connections, and designing dedicated hardware accelerators. These advancements will uniquely contribute to scalability and energy efficiency. The endeavor addresses key challenges in event-based processing and temporal coding, aiming for substantial performance gains in both software and hardware implementations of artificial intelligence systems. Expected research outputs include novel algorithms, optimization methods, and memristor-based hardware architectures, with broad applications and potential for technology transfer. -- Dr. Robert Legenstein Univ.-Professor Institute of Theoretical Computer Science Graz University of Technology Inffeldgasse 16b/I, 8010 Graz, Austria https://www.tugraz.at/institute/igi/people/prof-legenstein/ Follow @CompLegenstein on Twitter. ++43/316/873-5824 ----------------------------------

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Postdoc position on signal processing, AI and software for a closed-loop epilepsy, CLINATEC, Grenoble, France
by COSTECALDE Thomas Sept. 29, 2023

Sept. 29, 2023

We are seeking a highly motivated Postdoc to join the Epilepsy<https://www.cimec.unitn.it/en/929/action-recognition-and-concepts-group> program at Clinatec, France (Grenoble). The fellowship will investigate algorithmic approaches to detecting pre-ictal phenomena (interictal spikes) associated with the occurrence of seizures, using the PNH-penicillin model or other acute models. Seizure prediction is an essential part of the cooling approach-maximizing efficacy while reducing technical constraints. PhD or equivalent with strong knowledge in time-series, machine learning, signal processing, with strong skills in Python. Some experience in manipulating large data and working on clusters (slurm) is an advantage. Otherwise, a basic knowledge of the Unix command line basics is required. Ability to work autonomously. The position will be for 3 years and open now. Please send your expression of interest to malvina.billeres(a)cea.fr<mailto:malvina.billeres@cea.fr> and get in touch if you have any questions. We look forward to hearing from you! Thanks Dr Costecalde Thomas Here is the full description : Title: Post-doctoral fellow (H/F) signal processing, AI and software for a closed-loop epilepsy treatment application using focal cooling, seizure prediction and detection. Context: Epilepsy remains one of the most common neurological disease. This pathology has an incidence of 50 to 100 000 new cases per year and affects around 50 million people worldwide.Antiepileptics drugs are currently the gold treatment but they are effective only in 60-70% of patients. For several years, nonpharmacological potential new treatments have been investigated including an interesting new approach using focal cooling. In the literature, some results in preclinical models have shown that a cooling at 21°C can reduce the frequency of epileptic seizures. The postdoctoral fellowship will be carried out at Clinatec, in Grenoble, France. We have started a programme focused on focal cooling treatment. Our aim is to develop a medical device delivering a focal cooling to deep brain regions such as the hippocampus to treat epilepsy. We have therefore developed a preclinical implantable device to deliver this cooling in order to obtain information concerning the parameters needed to reduce seizures (target temperature, duration...). The fellowship will investigate algorithmic approaches to detecting pre-ictal phenomena (interictal spikes) associated with the occurrence of seizures, using the PNH-penicillin model or other acute models. Seizure prediction is an essential part of the cooling approach-maximizing efficacy while reducing technical constraints. The candidate will work closely with a neurosurgeon, who will provide neuroscientigic expertise, as well as a PhD student (biology). The laboratory also includes engineers, clinicians and a signal processing team. Missions will include, * Labelling of the different brain signals occurring in epilepsy (seizure, pre-ictal, interictal, post-ictal...). * Statistical analysis and hypothesis testing of the data. * Online closed loop optimization of seizure prediction/forecasting algorithms. * Detection of anomalies (HFO, fast ripples, phase coupling) for prediction and forecasting. * Testing of adaptive algorithms for prediction and forecasting (preclinical/clinical database): effects of cooling on algorithm performance. * Integration of other measurements (temperature...) in algorithm prediction. * Maintenance and improvement of experiment software Profil of candidate: PhD or equivalent with strong knowledge in time-series, machine learning, signal processing, with strong skills in Python. Some experience in manipulating large data and working on clusters (slurm) is an advantage. Otherwise, a basic knowledge of the Unix command line basics is required. Ability to work autonomously.

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The Purdue CCNLAB is recruiting a new graduate student for Fall 2024!
by Helie, Sebastien Sept. 29, 2023

Sept. 29, 2023

Dr. Sébastien Hélie is looking for new graduate students interested in problem solving, decision-making, or cognitive control. Dr. Hélie supervises students in the Mathematical & Computational Psychology (MCP) program, the Cognitive Psychology program, and the Neuroscience and Behavior program. This year, priority will be given to applications in the MCP program, but my interest is to recruit the best applicant regardless of which program the applicant is from. The Department of Psychological Sciences at Purdue University is consistently ranked among the top 50 in the US, and the CCNLAB has been doing cutting-edge research using various behavioral, neuroscientific, and computational methodologies. Interested students should contact Prof. Hélie at shelie(a)purdue.edu. ----------------------------------------------------------------- Sébastien Hélie, Ph.D. Professor of Psychological Sciences Director of CEREBBRAL -- Offices: PRCE 359 Phone: (765) 496-2692 Website: http://ccn.psych.purdue.edu/ -----------------------------------------------------------------

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Postdoc position on predictive representation / dynamic RSA, CIMeC, Uni Trento, Italy
by Moritz Wurm Sept. 29, 2023

Sept. 29, 2023

We are seeking a highly motivated Postdoc to join the Action Recognition and Concepts Group <https://www.cimec.unitn.it/en/929/action-recognition-and-concepts-group> at CIMeC (Center for Mind/Brain Sciences), University of Trento, Italy. The research project will focus on a MEG-based dynamic extension to representational similarity analysis (dynamic RSA <https://www.nature.com/articles/s41467-023-39355-y>) that we have recently developed in our lab to investigate predictive representations of dynamic events. The successful candidate should have a background in cognitive neuroscience (preferably in action and/or perception, M/EEG or fMRI, MVPA/RSA) and strong programming skills (preferably Matlab). The position will be for 2 years and probably open in beginning of 2024. Please send your expression of interest to moritz.wurm(a)unitn.it <mailto:moritz.wurm@unitn.it> and get in touch if you have any questions. We look forward to hearing from you! Best wishes, Moritz Wurm

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Modellers Workshop for the Brain Dynamics Toolbox (Final Call)
by Stewart Heitmann Sept. 29, 2023

Sept. 29, 2023

Final call for the Modeller’s Workshop for the Brain Dynamics Toolbox. The Modeller’s Workshop is an online course for researchers, students and instructors who wish to build custom dynamical models using the Brain Dynamics Toolbox. Topics include programming Ordinary Differential Equations, Partial Differential Equations, Delay Differential Equations, Stochastic Differential Equations, Auxiliary Plot Functions and command-line tools. Example code is provided in all cases. Study time is 8 hours. Course Website https://bdtoolbox.teachable.com/p/modellers-workshop Toolbox Website https://bdtoolbox.org Important Information Enrolments close Sat 30th Sep 2023. Disclaimer The information contained in this communication from the sender is confidential. It is intended solely for use by the recipient and others authorized to receive it. If you are not the recipient, you are hereby notified that any disclosure, copying, distribution or taking action in relation of the contents of this information is strictly prohibited and may be unlawful. This email has been scanned for viruses and malware, and may have been automatically archived by Mimecast Ltd, an innovator in Software as a Service (SaaS) for business. Providing a safer and more useful place for your human generated data. Specializing in; Security, archiving and compliance. To find out more visit the Mimecast website.

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Organization for Computational Neurosciences - call for self-nominations to the Board of Directors
by Rubchinsky, Leonid L Sept. 28, 2023

Sept. 28, 2023

Dear Colleagues, The Organization for Computational Neurosciences is inviting self-nominations for the OCNS Board of Directors election. New Directors will serve a three-year term from January 2024 through December 2026. Candidates are required to be an OCNS members for at least a year or to attend an on-site annual CNS meeting in the past. More information about the new Directors’ election can be found at https://www.cnsorg.org/election-procedures The deadline for application is October 11, 2023. Best regards, OCNS Board of Directors

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