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Next INCF/OCNS Software WG Dev session: Software Citation Principles: 22, 2021, 1600 UTC (Daniel S Katz, Neil Chue Hong)
by Ankur Sinha 18 Nov '21

18 Nov '21

Dear all, Apologies for the cross posts. In the next dev session at the INCF/OCNS Software Working Group, Daniel S Katz and Neil Chue Hong will discuss principles of citing research software. https://ocns.github.io/SoftwareWG/2021/11/01/dev-session-daniel-s-katz-neil… Where: Zoom: https://ucl.zoom.us/j/94578141033?pwd=SlZBcEluT2svUWhseGFHMUVLWFB0UT09 When: November 22, 2021, 1600 UTC The abstract for the talk is below: ----------------------------------- Today, software is a key part of almost all research, and the development and maintenance of this software is done by human beings, often in academia. It's essential that these activities be seen as a valued element of scholarly work so that the people who do it have career paths that encourage them to continue to do it. One means of accomplishing this is to use the existing scholarly citation system. The FORCE11 Software Citation working group[1] developed a set of Software Citation Principles in 2016[2], and since then, the FORCE11 Software Citation Implementation working group[3] has been working with many types of stakeholders, including publishers, repositories, and standards, to implement the principles. We'll talk about this work, the changes we've seen, what still needs to be done, and how the INCF community can participate. [1] https://www.force11.org/group/software-citation-working-group [2] https://www.force11.org/software-citation-principles [3] https://www.force11.org/group/software-citation-implementation-working-group The session is open to all, but requires you to login to Zoom to limit spam. Please do forward this to your colleagues. On behalf of the INCF/OCNS Software working group, -- Thanks, Regards, Ankur Sinha (He / Him / His) Research Fellow at the Silver Lab | http://silverlab.org/ Department of Neuroscience, Physiology, & Pharmacology University College London, London, UK Time zone: Europe/London

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Postdoctoral Position in Astrocyte and Vasculature Modeling at Blue Brain, EPFL
by Daniel Keller 17 Nov '21

17 Nov '21

*BBP- Postdoctoral Position in **Astrocyte and Vasculature **Modeling* A postdoctoral position in modeling of neuro-glia-vasculature is available at the Blue Brain Project at the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland (www.epfl.ch) The Blue Brain Project, based in Geneva, Switzerland, performs large-scale simulations of the brain. The proposed research will extend a model of astrocytes and vasculature to model calcium within detailed structural models of astrocytes in various brain regions, and to investigate aspects of coupling to vasculature. The position entails development of methods and systems to perform multi-scale modeling and integrate knowledge of the signaling pathways involved in glial messaging. The ideal candidate will have a Ph.D. in computational neuroscience or related field. Experience in modeling of metabolism, blood flow, and/or biochemical signaling cascades is desired. Strong biology and mathematical background, as well as coding competence in Python, C++, and NEURON would also be useful for the position. We are looking for highly motivated individuals to be part of a highly multidisciplinary group working at the interface of neuroscience, physics and computer science. Candidates should possess good writing, collaboration, and communication skills. Selected candidates will join a prestigious project that is pioneering simulation neuroscience research, composed of a young, dynamic, interdisciplinary, and international team. We offer a state-of-the-art working environment based at the Biotech Campus in Geneva ( http://www.campusbiotech.ch/en/ ) with access to cutting-edge simulation, informatics and computing facilities. More information and application instructions can be found at: https://recruiting.epfl.ch/Vacancies/2032/Description/2

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Two Postdoctoral Scholar Positions at Washington University in St. Louis
by Shuo Wang 16 Nov '21

16 Nov '21

We are looking for two highly motivated postdoctoral scholars to work on NSF and DoD funded projects. One postdoctoral scholar will use human single-neuron recordings to study the neural circuits underlying social attention, and the other postdoctoral scholar will use multimodal neuroimaging techniques to study social behavior and brain networks in people with autism. The research will be conducted in a highly collaborative environment using state-of-the-art equipment, facilities, and analytical methods. The postdoctoral scholars will collaborate with an established team of investigators within and outside WashU and have ample opportunity to learn new techniques and methods. Applicants must hold a Ph.D. in systems, cognitive, or computational neuroscience, or in physics, electrical engineering, or computer science, with relevant research expertise in neuroscience. Applicants must also have strong programming (Matlab or similar) skills. Individuals with previous human intracranial EEG expertise and/or macaque single-neuron recordings that wish to expand into human single-unit recordings are encouraged to apply. Our lab combines multimodal and advanced measurement techniques with sophisticated computational approaches to understand the neural mechanisms and neural computations underlying social attention, face processing, emotion, memory, and decision making. Overarching questions involve how the brain figures out what is important in the environment, how socially relevant stimuli pop out and attract attention, how faces are processed and represented in general, and how memory is modulated by attention. We are particularly interested in the neural computations underlying these cognitive processes: multimodal approaches allow us to investigate these questions from the microscopic single-neuron and neural circuit level using our state-of-the-art human single-neuron recordings as well as macroscopic level using fMRI, EEG, and intracranial EEG (sEEG and ECoG). These multimodal experimental approaches are powered by sophisticated computational approaches that can deal with complex and large datasets. The Wang Neuroscience Lab is housed in the Mallinckrodt Institute of Radiology (MIR) at the Washington University School of Medicine (WUSM) in St Louis. WUSM is a world class research intensive academic health center that is consistently ranked among the nation’s research-oriented medical schools. Additionally, it is nationally known for its attractive campus, which borders residential neighborhoods and one of the nation’s largest urban parks. St. Louis is consistently rated a Forbes most affordable city with vibrant music, food and park scene, and has one of the fastest growing start-up communities with impressive accelerator and incubator services available through the Biogenerator, Cambridge Innovation Center, and Cortex Innovation District. Shuo Wang, Ph.D. Assistant Professor Washington University in St. Louis https://sites.wustl.edu/wanglab/

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Fully funded PhD and postdoc positions in Computational Neurosciences at Maastricht University
by Jolivet, Renaud 15 Nov '21

15 Nov '21

Dear Colleagues, My department has 1 fully-funded postdoc position and multiple PhD positions for Chinese students to apply to via the Chinese Scientific Council: 1. I am recruiting a postdoc to work on our European EIC Pathfinder Open grant IN-FET (https://cordis.europa.eu/project/id/862882) to develop a new type of brain-machine interface. I am looking for a postdoc with experience in the computational modelling of neuronal biophysics at the cellular and sub-cellular levels, and an interest in using that knowledge to develop equivalent neural network models. The IN-FET project aims at developing a new type of interface for neural tissue that works by modulating the extracellular concentrations of key ionic species. Experience with COMSOL desired but not mandatory. FTE work based in Maastricht, but with frequent trips to Northern Italy anticipated (Trieste region). Attractive conditions, position funded for 27 months. Anticipated start date Jan 2021. 2. Our department is looking to attract Chinese students willing to apply with us for PhD positions funded by the Chinese Scientific Council. Positions are funded for 4 years. The following projects are available in our department: * https://www.maastrichtuniversity.nl/file/2021fsebreueragingmetabolicmodelin… * https://www.maastrichtuniversity.nl/file/2021fsejolivetmechanismsandroleofa… * https://www.maastrichtuniversity.nl/file/2021fseadriaensthegeneticunderpinn… Another project is available to investigate the metabolic profile of different glial cell types. If interested, contact me at r.jolivet(a)maastrichtuniversity.nl<mailto:r.jolivet@maastrichtuniversity.nl> or DM me at twitter.com/RenaudJolivet<http://twitter.com/RenaudJolivet>. Cheers, Renaud — Prof. Renaud B. Jolivet Neural Engineering and Computation, Chair Maastricht University Organization for Computational Neurosciences, Board of Directors Initiative for Science in Europe, External Policy Advisor and Board Member Marie Curie Alumni Association, Vice-Chair of Policy +41798302129 (mobile) ‭+31433881741 (office)‬ r.jolivet(a)maastrichtuniversity.nl<mailto:renaud.jolivet@unige.ch> twitter.com/RenaudJolivet<https://twitter.com/RenaudJolivet> linkedin.com/in/renaud-jolivet-63b5534<http://linkedin.com/in/renaud-jolivet-63b5534> scholar.google.ch/citations?user=9Ozwv7EAAAAJ&hl=en<https://scholar.google.ch/citations?user=9Ozwv7EAAAAJ&hl=en>

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Call for Papers: Reproducibility in Neuroscience
by Alberto Antonietti 15 Nov '21

15 Nov '21

Are you interested in making neuroscience more reproducible? Have you already tried to replicate a study? Are you bothered by the "Data and code are available upon reasonable request"? If your answer to one of the previous questions is "yes", then you could be interested in this call for papers. With this research topic, we aim to stimulate neuroscientists from all fields to design and publish works that rigorously attempt to reproduce landmarks or controversial studies: https://www.frontiersin.org/research-topics/26709/reproducibility-in-neuros… We are inviting papers on both: - "Results reproducibility", i.e., obtain the same results from an independent study with procedures as closely matched to the original study as possible; - "Inferential reproducibility", i.e. draw the same conclusions from either an independent replication, using different research methodologies, of a study or a reanalysis of the original data. Are you interested in making neuroscience more reproducible? Have you already tried to replicate a study? Are you bothered by the "Data and code are available upon reasonable request"? If your answer to one of the previous questions is "yes", then you could be interested in this call for papers. With this research topic, we aim to stimulate neuroscientists from all fields to design and publish works that rigorously attempt to reproduce landmarks or controversial studies: https://www.frontiersin.org/research-topics/26709/reproducibility-in-neuros… We are inviting papers on both: - "Results reproducibility", i.e., obtain the same results from an independent study with procedures as closely matched to the original study as possible; - "Inferential reproducibility", i.e. draw the same conclusions from either an independent replication, using different research methodologies, of a study or a reanalysis of the original data. We will consider both confirmatory and negative results, the unique criteria will be the rigorousness, fairness, and soundness of the replication study. Authors are required to make all materials and methods used to conduct their research available to other researchers. Data and codes used to analyze results must comply with FAIR principles and should preferably be uploaded to an online repository providing a global persistent identifier (e.g., OSF, Harvard Dataverse, Zenodo). Authors are also strongly encouraged to subject their codes to an independent audit at codecheck.org.uk. I’m very pleased to be launching a new article collection, Reproducibility in Neuroscience, together with an expert editorial team: - Alberto Antonietti - Blue Brain Project, Ecole polytechnique fédérale de Lausanne (EPFL), Geneva, Switzerland - Nele A Haelterman - Baylor College of Medicine, Houston, United States - Reeteka Sud - National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India - Nafisa M Jadavji - Midwestern University, Glendale, AZ, United States - Denes Szucs - University of Cambridge, Cambridge, United Kingdom We’re now in the process of putting together a group of top researchers whose work we’d like to feature in this collection, and we would like you to participate. The research topic is hosted by Frontiers in Integrative Neuroscience, you can find all information here: https://www.frontiersin.org/research-topics/26709/reproducibility-in-neuros… Important notice on Publishing Fee (APC) support: If Frontiers publishing fees are too high for your funding situation, you are eligible for full or partial APC fee support. In order to apply to fee support, please complete the fee support application form online, and allow up to two weeks for Frontiers to review and reply to your request: https://frontiers.qualtrics.com/jfe/form/SV_51IljifwFBXUzY1 More information can be found at: https://www.frontiersin.org/about/fee-policy Please get in touch if you have any questions - looking forward to hearing from you. Alberto On behalf of the Topic Editors. We will consider both confirmatory and negative results, the unique criteria will be the rigorousness, fairness, and soundness of the replication study. Authors are required to make all materials and methods used to conduct their research available to other researchers. Data and codes used to analyze results must comply with FAIR principles and should preferably be uploaded to an online repository providing a global persistent identifier (e.g., OSF, Harvard Dataverse, Zenodo). Authors are also strongly encouraged to subject their codes to an independent audit at codecheck.org.uk. I’m very pleased to be launching a new article collection, Reproducibility in Neuroscience, together with an expert editorial team: - Alberto Antonietti - Blue Brain Project, Ecole polytechnique fédérale de Lausanne (EPFL), Geneva, Switzerland - Nele A Haelterman - Baylor College of Medicine, Houston, United States - Reeteka Sud - National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India - Nafisa M Jadavji - Midwestern University, Glendale, AZ, United States - Denes Szucs - University of Cambridge, Cambridge, United Kingdom We’re now in the process of putting together a group of top researchers whose work we’d like to feature in this collection, and we would like you to participate. The research topic is hosted by Frontiers in Integrative Neuroscience, you can find all information here: https://www.frontiersin.org/research-topics/26709/reproducibility-in-neuros… Important notice on Publishing Fee (APC) support: If Frontiers publishing fees are too high for your funding situation, you are eligible for full or partial APC fee support. In order to apply to fee support, please complete the fee support application form online, and allow up to two weeks for Frontiers to review and reply to your request: https://frontiers.qualtrics.com/jfe/form/SV_51IljifwFBXUzY1 More information can be found at: https://www.frontiersin.org/about/fee-policy Please get in touch if you have any questions - looking forward to hearing from you. Alberto On behalf of the Topic Editors -- Questa email è stata esaminata alla ricerca di virus da AVG. http://www.avg.com

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Research Fellow "Machine Learning for Science" in Tübingen
by Philipp Berens 14 Nov '21

14 Nov '21

We have several positions to fill as Research Fellow "Machine Learning for Science" with potential runtime until 12/2025. We are searching at the postdoctoral level, for details see: https://www.nature.com/naturecareers/job/machine-learning-for-science-resea… Best Philipp -- -- Professor of Data Science for Vision Research Institute for Ophthalmic Research, University of Tübingen Cluster of Excellence "Machine Learning - New Perspectives for Science" www.berenslab.org

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PhD Position - A framework for automated inference, quality assessment and model enhancement of physics-based simulation models
by Philipp Benner 13 Nov '21

13 Nov '21

Dear colleagues, We are looking for a PhD student for the following project: For the design of safety critical components and structures, it is vital to ensure that integrity and reliability are maintained under all environmental conditions and feasible parameter settings. Physics based simulation models such as the Finite Element Method provide means to explore the behavior of a structure for many more scenarios than what can be measured experimentally. The development of an appropriate model either on the structural level or for the constitutive behavior of the materials involved is a complex task. The modelling assumptions can only be validated based on experimental data, which are either provided by databases with lab tests under different conditions on the material scale, or using monitoring techniques for a structural modelling problem. The challenge is that simulation models usually have multiple parameters that jointly influence the simulation results , i.e. there is not a one to one mapping between a single parameter and a single data set. As a consequence, an inverse problem has to be solved. The goal of this proposal is to 1. automate the procedure of calibrating model parameters based on experimental data including objective measures of the model quality 2. identify model discrepancies - which is particularly difficult for large datasets - by combining using Gaussian process models with physics based models 3. and suggest model improvements based on a dictionary type of learning procedure. All of the procedures are implemented in a Bayesian framework to account for measurement and model uncertainties. The validation of the developed methods is initially performed using virtual experiments allowing to directly prescribe model deficiencies and compare the identified models to the ground truth. The implementation of the models is done in an open source framework. As a consequence, the procedures are planned to be validated in parallel projects on real data sets. Details: https://www.bam.de/umantis/EN/952.html Kind regards, Philipp Benner

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PostDoc validation of safety-critical ML methods
by Philipp Benner 13 Nov '21

13 Nov '21

Dear colleagues, We have another exciting postdoc position: The digitization of engineering and materials science offers a wide range of options for optimizing manufacturing processes and testing procedures. Machine learning methods in particular show great potential here, e.g. in the prediction of material properties, the optimization of process parameters or as meta models for complex physical models in the context of a digital twin. The application of machine learning methods to safety-critical issues requires robust, explainable and generalizable models that can in particular also provide estimators for the accuracy of the model prediction. In the field of engineering, the dimensionality of the input data is also relatively large, combined with a relatively small number of data records. The aim is to develop methods that make it possible to apply ML methods taking into account statistical methods for safety-critical questions, and in particular to integrate additional information from physical models (described by partial differential equations). This sub-project is a collaboration between Department 7.7 “Modeling and Simulation” and Section S.3 “eScience”. The position is embedded in the additive manufacturing competence center and is financed by the QI-Digital (quality infrastructure) project. The project is integrated into an international research environment and requires active networking with industry and research. Further information: https://www.bam.de/umantis/EN/1024.html <https://www.bam.de/umantis/DE/1024.html> Kind regards, Philipp Benner

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COSYNE 2022: Abstract submission closes soon
by Tomas Hromadka 11 Nov '21

11 Nov '21

==================================================== Computational and Systems Neuroscience 2022 (Cosyne) MAIN MEETING 17 - 20 March 2022 Lisbon, Portugal WORKSHOPS 21 - 22 March 2022 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 is 20 November 2021. 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 is now open Abstract submission deadline: 20 November 2021 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. COSYNE SPEAKERS Eugenia Chiappe (Champalimaud Centre for the Unknown) Albert Compte (IDIBAPS, Barcelona) Sandeep Robert Datta (Harvard Medical School) André Fenton (New York University) Kate Jeffery (University College London) Ann Hermundstad (Janelia Research Campus, HHMI) Michael A. Long (New York University) Christian Machens (Champalimaud Centre for the Unknown) Asya Rolls (Technion - Israel Institute of Technology) Susanne Schreiber (Humboldt-Universität zu Berlin) Maryam Shanechi (University of Southern California) Scott Waddell (University of Oxford) Martha White (University of Alberta) ORGANIZING COMMITTEE General Chairs: Anne-Marie Oswald (U Pittsburgh) and Srdjan Ostojic (Ecole Normale Superieure Paris) Program Chairs: Laura Busse (LMU Munich) and Tim Vogels (IST Austria) Workshop Chairs: Anna Schapiro (U Penn) and Blake Richards (McGill) Tutorial Chair: Kanaka Rajan (Mount Sinai) DEIA Committee: Gabrielle Gutierrez (Columbia) and Stefano Recanatesi (U Washington) Undergraduate Travel Chairs: Angela Langdon (Princeton) and Sashank Pisupati (Princeton) Development Chair: Michael Long (NYU) Social Media Chair: Grace Lindsay (Columbia) Audio-Video Media Chair: Carlos Stein Brito (EPFL) Poster Design: Maja Bialon PROGRAM COMMITTEE Laura Busse (U Munich) Tim Vogels (IST Austria) Athena Akrami (UCL) Omri Barak (Technion) Brice Bathellier (Paris) Bing Brunton (U Washington) Yoram Burak (Hebrew University) SueYeon Chung (Columbia) Christine Constantinople (NYU) Victor de Lafuente (UNAM Mexico) Jan Drugowitsch (Harvard) Alexander Ecker (Göttingen) Tatiana Engel (Cold Spring Harbor) Annegret Falkner (Princeton) Kevin Franks (Duke) Jens Kremkow (Berlin) Andrew Leifer (Princeton) Sukbin Lim (Shanghai) Scott Linderman (Stanford) Emilie Mace (MPI Neurobiology) Mackenzie Mathis (EPFL Lausanne) Ida Momennejad (Microsoft) Jill O'Reilly (Oxford) Il Memming Park (Stony Brook) Adrien Peyrache (McGill Montréal) Yiota Poirazi (FORCE) Nathalie Rochefort (Edinburgh) Cristina Savin (NYU) Daniela Vallentin (MPI Ornithology) Brad Wyble (Penn State) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) 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 -> Mailing lists for details.

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Two postdoctoral positions at Harvard
by Cengiz Pehlevan 11 Nov '21

11 Nov '21

Dear colleagues, We have two postdoctoral positions at Harvard that may be of interest. 1) The George F. Carrier Postdoctoral Fellowship. This prestigious independent position at Applied Mathematics is open to candidates with a wide range of interests, including neuroscience and machine learning. Even though the listed deadline has passed, we are still accepting applications. Details are here: https://academicpositions.harvard.edu/postings/10697 <https://academicpositions.harvard.edu/postings/10697> 2) Postdoctoral Fellow in the Theory of Representation Learning in Artificial and Natural Systems. We are looking for exceptional junior scientists to work collaboratively with a group of faculty from Computer Science (Boaz Barak), Statistics (Lucas Janson), Electrical Engineering (Demba Ba) and Applied Mathematics (Cengiz Pehlevan) towards a theory of representations in artificial and natural systems. Details are here (towards the bottom of the page): https://academicpositions.harvard.edu/postings/10730 <https://academicpositions.harvard.edu/postings/10730> Best wishes, Cengiz

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