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technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in
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agents and as photosensitizers. The PhD student will acquire expertise in techniques for studying ROS generation in solution (indirect methods using internal dyes) and in vitro (using ROS-active dyes
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financement Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/133293 Requirements Specific Requirements Etudiant(e) titulaire d'un Master II en Statistique / Machine Learning
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-flexible technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD will take place at the Institut Lavoisier de Versailles (ILV), a
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the growing industrial demand for efficient thermal management, this PhD project focuses on developing low-cost, low-tech, self-adaptive vortex generators as passive flow-control devices for various
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Description The PhD student will join the T4-SECRET team (https://igdr.univ-rennes.fr/en/t4-secret-group-kevin-mace ), a young and dynamic group specialised in the structural and mechanistic study of Type IV
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, engineering, bioinformatics, machine learning, artificial intelligence) to support minimally invasive and targeted preventive and predictive medicine capable of limiting age-related functional disorders
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and Seidel in the early 2000s, inspired by symplectic geometry. This PhD project is part of a broader research program aiming to use categorical tools to derive geometric results about the
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. The team is currently composed of 6 permanent members, 4 PhD. student, 3 Post Doc and 1 master's degree. All the skills necessary for the successful of the thesis are mastered by all members of the team. Web