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Alpes and the University of Savoie Mont-Blanc. https://lpnc.univ-grenoble-alpes.fr/ Team Description: You will be part of the LPNC's "Vision and Emotion" team (UMR 5105; leaders: David Alleysson, CNRS
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will also support the development of machine-learning models to predict biochar catalytic performance from feedstock composition and preparation conditions. Where to apply Website https
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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 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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both conventional and machine learning approaches -supervision of intern(s) Institut NÉEL is a CNRS unit (UPR 2940) under agreement with the University Grenoble Alpes. The laboratory is related to
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biomechanical modeling, ideally applied to rigid multibody systems and to the musculoskeletal system. - Python programming (NumPy, SciPy, scikit-learn); interest in statistics, machine learning, model
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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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. ● Excellent academic track record and strong mathematical skills. ● Excellent programming skills. ● Experience in optimization and machine learning. ● Excellent spoken and written English skills. Recruitment
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, their photoluminescence properties have been less thoroughly explored. In this context, the AI-Unclon project funded by the ANR aims to use machine learning tools to predict the evolution of
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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