379 machine-learning "https:" "https:" "https:" "https:" "https:" "Dana Farber Cancer Institute" positions at CNRS in France
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of the project MESSENGER: « Can rock-powered Microbial EcoSyStEms provide valuable iNsiGhts into early life and its emERgence? » funded by the PEPR ORIGINS (https://pepr-origins.fr/en/ ) and integration
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ultrasound, Laboratoire d'imagerie Biomedical, LIB , https://www.lib.upmc.fr/ ) and nanoparticle engineering ( PHENIX Laboratory https://phenix.cnrs.fr/ ). The LIB is located in the Centre de Recherche des
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). - Familiarity with machine learning principles and generative/classification models (PyTorch Lightning, torch, scikit-learn, etc.), as well as data/model analysis methods (PCA, t-SNE, etc.). - Proficiency in
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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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, 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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aegypti). It comprises 60 staff members across 6 research teams. https://ibmc.cnrs.fr/laboratoire/m3i/ The Institute is easily accessible by bus and tram. The CNRS contributes towards the cost of private
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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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energetic internal waves. The project covers conference fees and travel expenses, as well as publication fees. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6523-BENSOY-023/Default.aspx
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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