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of 3D crystalline structures; – depending on the candidate's profile, implementing machine learning methods (AI & machine learning) for the analysis of physicochemical data from the hpmat.org database
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Information Eligibility criteria Applicants should hold a PhD in theoretical chemistry, physics, materials science, or a related field; -demonstrate strong expertise in machine learning (regression, neural
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Website https://emploi.cnrs.fr/Offres/CDD/UMR5267-DOMCAI-002/Default.aspx Requirements Research FieldLanguage sciencesEducation LevelPhD or equivalent Research FieldLanguage sciencesEducation LevelPhD
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Description CNRS offers a 18-month fixed-term contract researcher position to work on the recently funded project ACCTS (“Assessing cirrus cloud thinning strategies by learning from aerosol-cirrus interactions
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City STRASBOURG Website http://icpees.unistra.fr/ STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone YahooMail
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/InstituteLaboratoire de Physique des SolidesCountryFranceCityORSAYGeofield Contact City ORSAY Website http://www.lps.u-psud.fr/ STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail
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of results at conferences - interaction with team members and international collaborators The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning
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elucidating the molecular and cellular mechanisms of the late phase of long-term potentiation (LTP), a key process in learning and memory. The project is based on the development and use of an innovative
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learning simulations - Growth of metallic heterostructures by sputtering / ALD - Optical and e-beam lithography - Ion beam and reactive etching - Fabrication of skyrmion based nano-devices - Electrical
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic