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The Journal of Mathematical Neuroscience - recent articles
by Stephen Coombes July 17, 2020

July 17, 2020

The Journal of Mathematical Neuroscience publishes research articles on the mathematical modelling and analysis of all areas of neuroscience. The current list of journal articles is available at http://www.mathematical-neuroscience.com/ : Methods to assess binocular rivalry with periodic stimuli Authors: Farzaneh Darki and James Rankin https://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-… Understanding the dynamics of biological and neural oscillator networks through exact mean-field reductions: a review Authors: Christian Bick, Marc Goodfellow, Carlo R. Laing and Erik A. Martens https://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-… Spatially extended balanced networks without translationally invariant connectivity Authors: Christopher Ebsch and Robert Rosenbaum https://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-… Geometry of color perception. Part 1: structures and metrics of a homogeneous color space Authors: Edoardo Provenzi https://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-… Mesoscopic population equations for spiking neural networks with synaptic short-term plasticity Authors: Valentin Schmutz, Wulfram Gerstner and Tilo Schwalger https://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-… All articles are Open Access. The Impact Factor of the journal is 2.091 ------------------------------------------------------- Stephen Coombes Professor of Applied Mathematics School of Mathematical Sciences Nottingham, UK Tel: 0115 846 7836 http://www.maths.nott.ac.uk/~sc/ ------------------------------------------------------- This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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3 PhD/MSc Positions at the University of Calgary
by Wilten Nicola July 17, 2020

July 17, 2020

The Nicola Computational Neuroscience lab at the University of Calgary in the Hotchkiss Brain Institute is looking for three talented researchers at the PhD/Masters level. *PhD/MSc Position 1: Analysis and Modelling of Trained Recurrent and Spiking Neural Networks * The Nicola Lab is looking for a talented Master's or PhD candidate with a strong background in pure or applied mathematics, or physics. The project will involve analyzing the structure and operation of trained spiking and recurrent neural networks to determine how these trained networks perform dynamics, solve tasks, and emulate behaviours. The ideal candidate will have a background in dynamical systems theory, functional analysis, and some statistical analysis, and have a BSc in pure or applied mathematics. Some knowledge of numerical methods and neuroscience is beneficial, but not required. *PhD/MSc Position 2: Modelling Spatiotemporal dynamics in whole-brain imaging* We are looking for a talented Master's or PhD candidate with a background in computational neuroscience, mathematics, or physics. The project will involve analyzing the emergent spatiotemporal dynamics of whole-brain Calcium imaging data obtained in the McGirr Lab for mice undergoing experimentally induced stress paradigms. The ideal candidate will have a background in dynamical systems theory, statistical analysis, and a particular focus on spatial models (Partial Differential Equations), or Markov Processes. The ideal candidate will have a background in scientific programming and numerical methods for the simulation and analysis of these models. *PhD/MSc Position 3: Investigating Synchrony in Spiking Neural Networks * The Nicola Lab is looking for a talented Master's or PhD candidate with a strong background in Applied or Pure mathematics with an emphasis on dynamical systems theory. The project will involve analyzing the synchronizability of non-smooth, integrate-and-fire type spiking neural networks under a variety of conditions. The ideal candidate will have a background in dynamical systems theory, functional analysis, and some statistical analysis, and have a BSc in pure or applied mathematics. The ideal candidate will have a background in scientific programming and numerical methods for conducting simulations. Interested candidates should clarify which position they are applying for in an email to wilten.nicola(a)ucalgary.ca and attach to this email their CV, undergraduate/master's degree transcripts, a letter of research interests, and the contact information for 2 referees. The start-dates are flexible. The University of Calgary is a global intellectual hub located in Canada’s most enterprising city. In our spirited, high-quality learning environment, students thrive in programs made rich by research, hands-on experiences and entrepreneurial thinking. Our strategy drives us to be recognized as one of Canada’s top five research universities, engaging the communities we both serve and lead. This strategy is called Eyes High, inspired by the university's Gaelic motto, which translates as 'I will lift up my eyes.' For more information, visit ucalgary.ca/eyeshigh.

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Scientific software developer position at the SimLab Neuroscience, Juelich, Germany
by Charl Linssen July 16, 2020

July 16, 2020

(with apologies for any cross-posting) Dear colleagues, We have a Scientific software developer position available in the SimLab Neuroscience at the Jülich Supercomputing Centre, Jülich Research Centre, Germany. We are looking for candidates with a proven track record in developing scientific software who are interested in further developing NESTML, a modelling language and corresponding toolchain for the convenient specification of neuron and synapse models and the automatic generation of efficient C++ code from this specification modelling language. For a full description and details of how to apply, please see the announcement on our website: *Scientific Software Developer in Computational Neuroscience* https://www.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2020-230-E… The application deadline for the position is August 5th. Thank you for your consideration! With kind regards, Charl Linssen _____________________________________ Charl Linssen Ir. MSc SimLab Neuroscience / IAS-6 Jülich Supercomputer Centre (JSC) Institute for Advanced Simulation Forschungszentrum Jülich GmbH c.linssen(a)fz-juelich.de +49 (0)2461 61-5269 _____________________________________

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IMRF2020 postponed to June 07-10 2021 in Ulm, Germany
by Marc Ernst July 15, 2020

July 15, 2020

Dear participants of the IMRF, Although, the COVID-19 situation is getting better in some places around the world, it is still getting worse in a lot of other places, and travelling to and from Germany is still far away from normal. Additionally, distancing restrictions apply and will likely apply for quite some more time (maybe until a vaccination has been found), which would not allow us to host as many people as anticipated at the venue we reserved in October 2020. As many other conferences, we also considered moving to an online format for the IMRF meeting (https://cops.ifp.uni-ulm.de/imrf2020/ <https://cops.ifp.uni-ulm.de/imrf2020/>). However, we feel the community would not benefit as much as having a meeting in person. Therefore, we decided to postpone the IMRF meeting once again (and hopefully for the last time) to June 07-10, 2021. Abstract submission and registration will stay open. All abstracts already submitted will further be considered. However, as there may be new data or insights gathered even during the COVID-19 pandemic, you can of course log on and adapt your abstracts until the new deadline for abstract submission. Same applies for the symposia already accepted. However, as the symposia have already gone through a review process, we would check these changes again and in case of substantial revisions we would probably re-review them again. We will announce the new deadlines for submission and registration in due time. The abstract submission and registration page can be found here: https://cops.ifp.uni-ulm.de/imrf2020/index.php/imrf-2020/registration-submi… <https://cops.ifp.uni-ulm.de/imrf2020/index.php/imrf-2020/registration-submi…> Also for those who already registered, your registrations will stay valid. Others can register at any time. The new registration deadlines will also be announced soon. Sorry for the inconvenience this second postponement may cause and thanks for your understanding. Be safe and stay healthy!!!! Best, Mac Ernst on behalf of the IMRF Organizers.

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Professorship position in explainable/interpretable Machine Learning
by Jörg Lücke July 15, 2020

July 15, 2020

Dear list, Let me draw your attention to a currently advertised position on explainable / interpretable learning algorithms. The position is in the Health Sciences but researchers with a data analysis background interested in developing in the direction of health data analysis are of interest. Also candidates with a computational neuroscience background or a robotics background are of interest. So the spectrum of potential candidate profiles is relatively broad. Please see the following link for the official advertisement. https://uol.de/stellen/?stelle=67364 The position is a German W2 Professorship position (similar Associate Professor). Thanks and best wishes, Jörg Lücke -- Jörg Lücke (PhD) Professor and Head of the Machine Learning Lab Department of Medical Physics and Acoustics School of Medicine and Health Sciences University of Oldenburg 26111 Oldenburg Germany www.uol.de/ml

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CNS*2020 Workshop on "Multi-disciplinary approaches to quantify and model calcium signaling in nervous systems and beyond", July 21-22, 2020 (8.30 am-5 pm BST / GMT+1)
by Maurizio De Pittà July 14, 2020

July 14, 2020

Dear colleagues, Please share it with your contacts. I am delighted to be able to share with you the finalized program of the forthcoming Workshop on "Multi-disciplinary approaches to quantify and model calcium signaling in nervous systems and beyond," July 21-22, 2020 (8.30 am-5 pm BST / GMT+1) as part of the CNS*2020 Virtual Conference. Workshop website: https://sites.google.com/view/cns2020-calcium-workshop/home We are joining together some of the prominent scientists in the field, touching a whole range of topics and approaches, ranging from techniques and machine learning tools to acquire calcium signals in living systems, to modeling in neurons, synapses, glial and other systems of the body. Confirmed speakers (in alphabetical order): Amit Agarwal, Heidelberg University, Germany Johnatan Aljadeff, University of California at San Diego, USA Alexey Brazhe, Lomonosov Moscow State University, Russia Pengxing Cao, School of Mathematics and Statistics, University of Melbourne, Australia Evan Cresswell-Clay, National Institute of Health, USA & The Basque Center for Applied Mathematics, Spain Silvina Ponce Dawson, Department of Physics, FCEN-UBA & IFIBA, CONICET-UBA, University of Buenos Aires, Argentina Martin Falcke, Max Delbrück Center for Molecular Medicine Berlin, Germany Johannes Friedrich, Simons Foundation, USA Andrea Giovannucci, UNC-Chapel Hill/North Carolina State University, USA Michael Graupner, Université de Paris, CNRS, SPPIN, France Shawn Means, School of Natural and Computer Sciences, Massey University, New Zealand Vijai Rajagopal, University of Melbourne, AUS Leonid Savtchenko & Dimitri Rusakov, Queen Square Institute of Neurology, University College London, UK Simon Schultz, Centre for Neurotechnology and Department of Bioengineering, Imperial College London, UK Alexey Semyanov, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia Ivo Siekmann, Department of Applied Mathematics, Liverpool John Moores University, UK Alexander Skupin, University of Luxembourg, Luxembourg James Sneyd, The University of Auckland, New Zealand Ghanim Ullah, University of South Florida, USA Agne Tilūnaitė, School of Mathematics and Statistics, University of Melbourne, Australia Ruediger Thul, The University of Nottingham, UK Attendance to the online Workshop is FREE but requires registration to the CNS*2020 meeting (this year free of charge). More Info: https://docs.google.com/document/d/1N45m5I4lZ4wUX4kOkxgPqEK4yeIdADuKgdqPuBF… Schedule of the Workshop's talks, along with Crowdcast links for individual sessions may be found on the Sched page of CNS*2020: https://cns2020online.sched.com/overview/type/Workshop/W02%3A+Calcium+signa… CALCIUM WORKSHOP webpage: https://sites.google.com/view/cns2020-calcium-workshop/home Thank you for your consideration. The workshop organizers: Pengxing Cao, University of Melbourne, Australia Maurizio De Pitta, Basque Center for Applied Mathematics, Spain Ivo Siekmann, Liverpool John Moores University, UK ----- Maurizio De Pitta' Research Fellow MCEN -- Group of Mathematical, Computational and Experimental Neuroscience BCAM -- Basque Center of Applied Mathematics https://sites.google.com/site/mauriziodepitta/home

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Postdoc position at the Research Center Juelich
by Daun, Silvia July 13, 2020

July 13, 2020

Dear All, I have a Postdoc postion to offer in my lab: "Researchers at the subinstitute Cognitive Neuroscience (INM-3) investigate the neural mechanisms underlying cognitive (dys-) function in healthy subjects and patients suffering from neurological and psychiatric disorders. Functional imaging (PET, MRI) and electrophysiological methods (EEG, TMS, tDCS) are combined with computational approaches. The successful candidate will investigate how neural information processing within the human motor system is impaired by (non-)pathological aging under the supervision of Prof. Dr. Silvia Daun. We are looking to recruit a Postdoc - Cognitive Neuroscience / Computational Neurology at the Research Center Juelich Your Job: • Design, acquisition and analysis of EEG data from healthy subjects and stroke patients • Development of analysis algorithms and mathematical models • Presentation and publication of the results • Interaction with team members and collaborators from Psychology, Medicine, and Computational Neuroscience Your Profile: • Completed study in Computer Science, Computational Neuroscience, Physics, Mathematics, Biomedical Engineering including an excellent doctoral degree • Significant programming skills (preferably in Matlab or Python) • Keen interest in cognitive and systems neuroscience • Experience with the conduction of EEG experiments • Proven scientific achievements as evidenced by publications in international, peer-reviewed journals • Interest in combining basic research and translational research on stroke patients • Good command of English • High social competence and organizational talent • High motivation Our Offer: • Exciting working environment on an attractive research campus with excellent infrastructure, located between the cities of Cologne, Düsseldorf, and Aachen • A stimulating, collaborative, and international research environment • A comprehensive further training programme • Flexible working hours and various opportunities to reconcile work and private life • Full-time position with the option of slightly reduced working hours • Limited for 3 years with possible longer-term prospects • Salary and social benefits in conformity with the provisions of the Collective Agreement for the Civil Service (TVöD). Depending on the applicant`s qualifications and the precise nature of the tasks, salary grade EG 13 TVöD-Bund Forschungszentrum Jülich promotes equal opportunities and diversity in its employment relations. We also welcome applications from disabled persons." To apply, please follow the link: https://www.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2020-212-E… All the best, Silvia Prof. Dr. rer. nat. Silvia Daun Kognitive Neurowissenschaften Institut für Neurowissenschaften und Medizin (INM-3) Forschungszentrum Jülich Leo-Brandt-Str. 5 52425 Jülich Telefon: 02461-61-8638 Telefax: 02461-61-9853 Email: s.daun(a)fz-juelich.de und Professorin für Computational Neuroscience - Modeling Neural Network Function Zoologisches Institut Universität zu Köln Biowissenschaftliches Zentrum, Zi. 1.104 Zülpicher-Straße 47b 50674 Köln Telefon: 0221-470-3829 Telefax: 0221-470-4889 Email: silvia.daun(a)uni-koeln.de http://www.neuro.uni-koeln.de/neuro-gruhn-staff-sg.html ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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job post: machine learning research scientist at NIMH
by Francisco Pereira July 12, 2020

July 12, 2020

*** HIRING: machine learning research scientist The Machine Learning Team at the National Institute of Mental Health (NIMH) in Bethesda, MD, has an open position for a machine learning research scientist. The NIMH is the lead federal agency for research on mental disorders and neuroscience, and part of the National Institutes of Health (NIH). *** About the NIMH Machine Learning Team Our mission is to help NIMH scientists use machine learning methods to address a diverse set of research problems in clinical and cognitive psychology and neuroscience. These range from identifying biomarkers for aiding diagnoses to creating and testing models of mental processes in healthy subjects. We work with many different data types, including very large brain imaging datasets from various imaging modalities, behavioral data, and picture and text corpora. We have excellent computational resources, both of our own (tens of GPUs for deep learning) and shared within the NIH (a cluster with hundreds of thousands of CPUs, and hundreds of GPUs). As a machine learning research group, we develop new methods and publish in the main machine learning conferences (e.g. NeurIPS and ICLR), as well as in psychology and neuroscience journals. Many of our problems require devising research approaches that combine imaging and non-imaging data, and leveraging structured knowledge resources (databases, scientific literature, etc) to generate explanations and hypotheses. You can find more about our work and publications at https://cmn.nimh.nih.gov/mlt *** About the position We are seeking candidates who are capable of combining machine learning, statistical, and domain-specific computational tools to solve practical data analysis challenges (e.g. designing experiments, generating and testing statistical hypotheses, training and interpreting predictive models, and developing novel models and methods). Additionally, candidates should be capable of visualizing and communicating findings to a broad scientific audience, as well as explaining the details of relevant methods to researchers in a variety of domains. Desirable experience that is not required, but will be considered very favorably: - neuroimaging data processing and analysis (any MRI modality, as well as MEG and EEG) - other types of neural data (e.g. neural recording, calcium imaging) - modelling of human and animal learning and decision-making - Bayesian statistical modelling Finally, you should have demonstrable experience coding in languages currently used in data-intensive, scientific computing, such as Python, MATLAB or R. Experience with handling large datasets in high performance computing settings is also very valuable. Although this position requires a Ph.D. in a STEM discipline, we will consider applicants from a variety of backgrounds, as their research experience is the most important factor. This is an ideal position for someone who wants to establish a research career in method development and applications driven by scientific and clinical needs. Given our access to a variety of collaborators and large or unique datasets, there is ample opportunity to match research interests with novel research problems. We also maintain collaborations outside of the NIH, driven by our own research interests. If you would like to be considered for this position, please send francisco.pereira(a)nih.gov a CV, with your email serving as cover letter. If you already have a research statement, please feel free to send that as well. There is no need for reference letters at this stage. Other inquiries are also welcome. Thank you for your attention and interest!

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Two Research (PhD) Positions in Machine Learning Theory and Applications - Oldenburg University, Germany
by Jörg Lücke July 10, 2020

July 10, 2020

The Machine Learning Lab at the University of Oldenburg, Germany, is seeking to fill two positions for doctoral researchers Our Machine Learning Lab conducts mathematically grounded research on novel approaches in Machine Learning with a focus on probabilistic generative approaches including deep generative models. Examples are deep variational autoencoders, deep mixture models, and Bayesian networks. Our research projects are conducted in collaboration with leading international labs, and we publish in leading international journals and present on leading conferences. Our interests are in understanding methods and in developing novel approaches to solve difficult problems in Machine Learning. We are interested in problems with strong data corruptions, strong noise and in problems with few data or few labels. Furthermore, we are in general interested in the development of novel approaches that significantly improve learning efficiency (with applications to Big Data). At the same time, we model neural information processing using Machine Learning models in order to understand the nature of biological intelligence. The two positions will both allow for basic research, and they will both allow for applications to data for tasks such as data enhancement (denoising, inpainting, deblurring), unsupervised and semi-supervised learning, super-resolution, outlier detection etc. Part of one position has a focus on addressing such tasks for medical data. Ideal candidates have a strong background in a theoretical subject and/or a high interest in further advancing Machine Learning methods such as variational optimization. Example degrees that qualify for the positions are degrees in Physics, Mathematics, Statistics, in the Data Sciences or degrees of related disciplines. Strong programming skills are a big plus. Candidates have to hold a MSc degree or have to be sufficiently close to obtaining one. Interested researchers are invited to apply for both positions simultaneously (please indicate in the cover letter). This is an informal description of the positions. The only officially relevant descriptions can be found here (please follow the instructions therein): https://uol.de/stellen/?stelle=67425 https://uol.de/stellen/?stelle=67430 Both positions are funded for 2.5 / 3 years with an intention for extensions. Oldenburg is a nice and affordable place to live, and is located within 40mins travel time of the North Sea coast. It is part of the Bremen/Oldenburg metropolitan region of Germany with close cultural and academic links to Dutch cities like Groningen across the German/Dutch border. The application deadline for the positions is July 19, 2020. -- Prof. Dr. Jörg Lücke Leiter Abteilung Machine Learning Department für Medizinische Physik und Akustik Fakultät für Medizin und Gesundheitswissenschaften Carl von Ossietzky Universität Oldenburg D-26111 Oldenburg www.uol.de/ml

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Workshop: Open data, tools, and models from the Allen Institute supporting systematic computational studies in neuroscience
by Anton Arkhipov July 10, 2020

July 10, 2020

Dear Colleagues, The Workshop “Open data, tools, and models from the Allen Institute supporting systematic computational studies in neuroscience” will take place online on July 21-23, 2020, as a part of the 29th Annual Computational Neuroscience Meeting (CNS*2020). Join us at the Workshop to learn about unique open datasets, software tools, and computational models from the Allen Institute and to discuss how the community can utilize these free resources to support and inform computational and theoretical work. To attend, please register for CNS*2020 at https://www.cnsorg.org/cns-2020 <https://www.cnsorg.org/cns-2020%0b>The registration is free. When: July 21-23, 2020, 8:00am-12:00pm, Pacific Time Workshop Reference: W6 Workshop Organizers: Anton Arkhipov (Allen Institute for Brain Science, Seattle, WA) Saskia de Vries (Allen Institute for Brain Science, Seattle, WA) Nuno da Costa (Allen Institute for Brain Science, Seattle, WA) Confirmed Speakers: Michael Buice (Allen Institute for Brain Science, Seattle, WA) Forrest Collman (Allen Institute for Brain Science, Seattle, WA) Eva Dyer (Georgia Tech, Atlanta, GA) Gaute Einevoll (University of Oslo, Oslo, Norway) Michael Hawrylycz (Allen Institute for Brain Science, Seattle, WA) Tim Jarsky (Allen Institute for Brain Science, Seattle, WA) Jerome Lecoq (Allen Institute for Brain Science, Seattle, WA) Gabriela Michel (Janelia Research Campus, Ashburn, VA) Stefan Mihalas (Allen Institute for Brain Science, Seattle, WA) Lydia Ng (Allen Institute for Brain Science, Seattle, WA) Blake Richards (McGill University, Montreal, Canada) Josh Siegle (Allen Institute for Brain Science, Seattle, WA) Bosiljka Tasic (Allen Institute for Brain Science, Seattle, WA) Jennifer Whitesell (Allen Institute for Brain Science, Seattle, WA) Joel Zylberberg (York University, Toronto, Canada) Further details: https://alleninstitute.org/what-we-do/brain-science/events-training/2020-cn… We hope to see you there! Best wishes, Anton. Anton Arkhipov Associate Investigator T: 206.548.8414 [cidimage001.png(a)01D5F0E2.E3F24C00] www.alleninstitute.org<https://nam12.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.alleni…>

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