264 machine-learning "https:" "https:" "https:" "https:" "U.S" Postdoctoral positions at CNRS
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Website https://emploi.cnrs.fr/Candidat/Offre/UMR5521-FLOVIE-003/Candidater.aspx Requirements Research FieldEngineeringEducation LevelPhD or equivalent Research FieldPhysicsEducation LevelPhD or equivalent
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out within the PICMIC group at IP2I in Lyon, under a pre-maturity grant obtained following a patent awarded to Professor I. Laktineh. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5822
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involved and stakeholders interested in the project. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8538-PIEBAR-007/Candidater.aspx Requirements Research FieldEnvironmental scienceEducation
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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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diffractometer, a GC for common gas analysis, a GC/MS, and an HPLC/MS. DFT calculations will be performed using annual allocations on national high-performance computing centers. More details here: https
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of errors between model predictions and post-operative reality This work will be carried out by the Biomécamot team (https://www.timc.fr/BiomecaMot ) at the TIMC laboratory, which is part of the CNRS's
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colleagues, in order to acquire new skills. • Design and synthesis of new molecules with photocrosslinking functionalities that can self-assemble on surfaces according to compatible patterns. This task will
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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
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, access to computer cluster Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8197-VALHER-212/Candidater.aspx Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent
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Eligibility criteria Instrumental optics and imaging (microscopy, camera detection) for biology. Skills in coding and experiment control. Basics of machine learning and/or signal processing. Teamwork