311 structures-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" positions at CNRS
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proposed by FLI and ALPAO will make it possible to tackle both the problem of speed, and that of spatial scaling in anticipation of the ELT. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre
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scientists working in diverse domains of fundamental and applied Physics. The postdoc will integrate the Condensed Matter group at CPHT. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7644
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modeling of polymeric, reinforced, and porous materials, with strong expertise in large deformations and numerical homogenization. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7649-JULDIA
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Starrydata2). The work will include the implementation of machine learning models (neural networks, random forests, SISSO), generative approaches for predicting crystal structures, the use of machine learning
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to structured programming in C++ and Python - knowledge of linux / unix operating system - fluent knowledge of spoken and written English - fundamental knowlegde of machine learning (and statistics) - good level
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(MESR). The Marie Sklodowska-Curie GLYCOCALYX doctoral network (https://www.glycocalyx.org/ ) brings together 15 European partners implementing a multidisciplinary research and training program to study
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conducted with Italian partners in Rome (Sapienza University, Catholic University of Rome, Gemelli Institute). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7252-VINCOU-004/Default.aspx
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, INSERM and Sorbonne Université. The candiate will also work with our collaborators in the project. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8265-FRATRO-002/Default.aspx Requirements
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to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR9009-CLALEN-001/Default.aspx Requirements Research FieldMathematicsEducation LevelPhD or equivalent Research FieldHistoryEducation LevelPhD or equivalent
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. Argument(ation) mining, the new and rapidly growing area of Natural Language Processing (NLP) and computational models of argument, aims at the automatic recognition of argument structures in large resources