67 machine-learning "https:" "https:" "https:" "https:" "https:" "Dana Farber Cancer Institute" uni jobs at CNRS
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tax monthly), with 75% of public transportation costs covered by the employer and 44 days of paid leave per year. Within the framework of the PEPR B-BEST program (https://www.pepr-bioproductions.fr
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, Applications of Deep Learning in Electromagnetics: Teaching Maxwell's equations to machines. Scitech Publishing, 2023. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR6164-DAVGON-024
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output. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR137-HENJAF-017/Default.aspx Requirements Research FieldPhysicsEducation LevelMaster Degree or equivalent Research
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, manual surveying and block surveying - Proficiency in English Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR5138-NEDKAC-009/Default.aspx Requirements Research FieldHistoryEducation
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MICADO (the first light instrument of the Extremely Large Telescope). The project provides a collaborative network, engaging with leading experts in optics, astrophysics, and machine learning from
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spectroscopy techniques and support the rational design of more efficient photocatalysts for sustainable chemical transformations. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR8181-HELTIS
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team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed
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are part of the European project ERC CoG 101086807 MAGNETALLIEN which aim to probe AC detection of spin pumping signal and its high harmonics : https://cordis.europa.eu/project/id/101086807 The candidate
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. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6457-SOPDEP-065/Default.aspx Requirements Research FieldChemistryEducation LevelPhD or equivalent Research FieldChemistryEducation LevelPhD
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MICADO (the first light instrument of the Extremely Large Telescope). The project provides a collaborative network, engaging with leading experts in optics, astrophysics, and machine learning from