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counting, or similar areas. Additional experience in the theory and practice of machine learning would be an asset. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8188-MARHEC-007
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expertise in developing computational models and machine learning methods, as well as experience in repertoire data analysis. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8023
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catalytic performance; • development of an experimental database for machine-learning models. The PhD will be conducted at ICPEES within the ECED group, which specializes in heterogeneous catalysis
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will investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable
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the complete event reconstruction and systematic uncertainty estimation pipeline for Super-Kamiokande. Reduction of Super-Kamiokande systematic uncertainties using machine learning, control samples
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will be responsible for designing and implementing physics-informed machine learning strategies for identifying constitutive laws in granular media. This includes the development of thermodynamically
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high-performance GPU cards will be provided to the PhD student to support the development, training, and implementation of machine learning models. Travel and participation costs for project meetings and
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language processing. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR8554-YAILAK-003/Default.aspx Requirements Research Field Language sciences Education Level PhD or equivalent Research
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integrative approaches at the interface of (epi)genomics, machine learning and physics, addressing key challenges in modern quantitative biology. The successful candidate will be responsible for: • Develop
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statistics is required (Bayesian and frequentist approaches; knowledge of machine learning would be an asset). Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR9191-ARNLER-009/Default.aspx