206 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Postdoctoral positions at CNRS
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A, Campus Illkirch station) from Strasbourg train station or by car (parking available). Public transportation costs are partially covered. Where to apply Website https://emploi.cnrs.fr/Offres/CDD
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support machine learning applications for analyzing electron microscopy images of nanoalloys. Model interactions between nanoalloys and carbon substrates to reflect experimental conditions, incorporating
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or Full-time at IRIF Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8243-SANMAR-008/Default.aspx Requirements Research FieldComputer scienceEducation LevelPhD or equivalent Research
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The Laboratory of Organic Polymer Chemistry (LCPO) is a joint research unit attached to the CNRS, the University of Bordeaux and the Bordeaux Polytechnic Institute (http://www.lcpo.fr ). The LCPO is composed of 4
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Website https://emploi.cnrs.fr/Offres/CDD/UMR5566-LIOREN-010/Default.aspx Requirements Research FieldAstronomyEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research FieldAstronomyYears
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of the Inria center of the University of Lille. The position is funded by the CPER WaveTech@HdF project. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8524-GUIFER-001/Default.aspx Requirements
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on quantum light, either usiing "discrete variables" (photon number superpositions) or "continuous variables" (field quadratures) Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR9001-LOILAN-007
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. In this project, we aim to develop digital tools combining density functional theory (DFT) and machine learning (ML) to accelerate the in-silico design of solid catalysts for the DA process. - Perform
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e.g., ultra-cold gases of bosonic or fermionic atoms, machine learning technologies and quantum computing. At the same time, we work in close connection with IJCLab experimentalists, particularly
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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