62 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" 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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motivated to acquire new skills. Candidates must be fluent in English and/or French with scientific writing skills. The doctoral contract will take place at the CRISMAT laboratory (https://crismat.cnrs.fr
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Office equipped with a computer station and common
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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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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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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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, 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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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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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