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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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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
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researchers, teacher-researchers, engineers, technicians, administrators, students, and foreign visitors work there. The research car-ried out at LAPP aims to study the physics of elementary particles and their
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Environment (UMR5300; https://crbe.cnrs.fr/en/ ) is internationally recognized for its research on the interaction between the environment and biodiversity using genetics. Numerous projects are being developed
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the impact of collective effects in high space-charge regimes. The Accelerators and Ion Sources Pole of LPSC is involved in the design, construction, and operation of the PERLE machine, particularly in
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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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artificial intelligence. shared office and access to laboratory resources Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7243-JERLAN-013/Default.aspx Requirements Research FieldComputer
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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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the framework of the PEPR Sous-Sol project ORGMET conducted by a consortium of four French laboratories GET, INEEL/ESRF, LFCR and IPREM (https://www.soussol-bien-commun.fr/fr/appel-projets-2024/orgmet