264 machine-learning-"https:" "https:" "https:" "UCL" Postdoctoral positions at CNRS in France
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of Learning and Development (LEAD- UMR-5022), at the Université Bourgogne Europe, CNRS (https://lead.ube.fr/ ) . To apply, please submit: - CV - Cover letter describing your interest in the position
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-machines and nano-robots as a drug delivery vehicles. As a core research activities, the postdoc candidate activities are the: - Design and in silico modeling of DNA origami nanostructures with high
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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researchers with ample experience in MEG/EEG data analysis, BCIs, signal processing, deep learning for brain imaging analysis, biomedical statistics, dynamical systems and research on motor control. The lab has
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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computer scientist with experience in bioinformatics, solid programming skills and knowledge in 3D protein structures. Machine learning skills and knowledge of Web development are a plus. Good interpersonal
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from the advantages offered by the CNRS. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5280-FRABES-003/Candidater.aspx Requirements Research FieldEngineeringEducation LevelPhD
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Postdoctoral researcher (M/F), synthesis of crystal phase heterostructures by Molecular Beam Epitaxy
supervisors and academic partners. A demanding research environment focused on publishable results and on the demonstration of unprecedented growth control. Where to apply Website https://emploi.cnrs.fr
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part of the international Refuge-Arctic project (https://www.refuge-arctic.ulaval.ca ) with links to the NASA FORTE project, whose overall objective is to better understand and predict the role played by
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dynamical systems), epidemiological modelling, data analysis (statistics, machine learning). • in scientific programming (preferably Python, Matlab, R) Genuine interest in the analysis and modeling