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algorithm development and satellite remote sensing • Good written and spoken English • Ability to work independently as well as in a team • Proficiency in programming languages (e.g. Python, R, Fortran
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at structuring and expanding key research communities working at the intersection of AI and the humanities. EIDA (ANR-22-CE38-0014) seeks to develop a new critical approach to astronomical diagrams produced
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, Action and Perception (RAP) team (https://www.laas.fr/en/teams/rap/ ) at LAAS-CNRS, Toulouse, France. The research conducted in the RAP team focuses on the design, prototyping, implementation, and
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properties are optimized by machine learning algorithms to retrieve properties of reference flames gathered in a learning base. A virtual scheme consists of a main block that models the heat release from
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using wall oscillations, relating small-scale turbulence to heat transport, modelling large-scale outer flow effects, and developing low-order heat transfer models. Partnerships with industry will