367 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" positions at CNRS
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impact measurements, AFM imaging, and AFM-SECM experiments. The SEEAFM project will be developed within the Electrochemistry group of the IMF team at the CEISAM laboratory. Where to apply Website https
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new thermoelectric materials using data science and machine learning methods applied to materials, based on expert-reviewed experimental data from the literature and public databases (notably
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expected to present his/her scientific findings at national and international conferences and to write research articles based on the obtained results. Where to apply Website https://emploi.cnrs.fr/Offres
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to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7327-MARROU0-077/Default.aspx Requirements Research FieldGeosciencesEducation LevelPhD or equivalent Research FieldAstronomyEducation LevelPhD
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located in an innovative environment, at the cutting edge of future technologies, in strategic application sectors. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR5270-SYLGON-070/Default.aspx
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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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postdoctoral students. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR9001-FABOEH-006/Default.aspx Requirements Research FieldMathematicsEducation LevelPhD or equivalent Research
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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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will involve measurements at synchrotron radiation facilities and visits to collaborating research groups. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7265-JULORD-012/Default.aspx
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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