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biologists, physicists and computer scientists. Your second base will be Alphée Michelot's group at the Mechanobiology Institute of Singapore (MBI) to achieve objective 3. The Michelot group is an expert in
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climatic conditions, using machine learning approaches based on isotopic data. SSIAs for δ13C, δ15N and δ34S in dentin collagen and δ66Zn in enamel to reconstruct the evolution of seasonal habitats and the
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strong interest in computer science (software development, machine learning techniques, etc.) is desirable. · Applicants must have a maximum of 3 years of research experience after the PhD. · Language
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and machine learning Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7018-CEDGEN1-002/Default.aspx Work Location(s) Number of offers available1Company/InstituteLaboratoire de
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new methodologies relying on statistical inference and machine learning from data fusion and transpose these to the field of exoplanet characterization. She/He will develop and maintain the FORMOSA code
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Paul-Valéry, Montpellier, UMR TETIS). The team combines expertise in evolutionary biology, ornithology, and advanced machine learning techniques, including generative AI. The candidate will have a dual
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Technologies du Langage) department. This team specializes in machine learning methods applied to language processing and has extensive experience and international recognition in speech technologies. Where
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data processing pipelines for LSST and Euclid, as well as Machine Learning algorithms for photometric redshift estimation and cluster detection. - Processing of external Euclid Data from Rubin/LSST and
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programming, CAD or generative design tools, knowledge in crystal plasticity, continuum mechanics, additive manufacturing, data science, and machine learning. Additional comments More information about the
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machine-learning is required, as well as a good knowledge of associated theoretical tools (statistical physics of liquids, ...; programming experience among: Python, Fortran, C, C++, ...). A good command of