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                movements can be preceded by slow movements lasting from several days to several years. These movements can be detected and tracked by satellites, either using radar or optical sensors. Since 2016, data from 
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                project team that includes doctoral students and technical staff. The main objective of this postdoc position is (1) to develop theoretical modelling approaches (bioenergetics, thermodynamics, ecological 
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                will participate in laboratory experiments, data analysis, field work, and work as part of a project team that includes doctoral students and technical staff. The main objective of this postdoc position 
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                objective of the successful candidate will be the implementation of advanced fast MAS solid-state NMR, and also the set-up of DNP approaches. The goal is to study structures of the viral membrane-bound 
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                of 360-degree vision and robotics (collaborative robot arm, humanoid robot) to enable the dynamic handover of an object from a person to a robot and carry it together to move it. - Activity 1: Substantive 
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                research problems in chemistry (ANR TcPredictor project) and to the study of materials under pressure, in particular superconducting hydrides; implementation of a multi-objective Tc-energy approach 
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                retardants may be incorporated to tailor the material properties. Achieving a high carbon yield and optimising the resin processing will be key objectives of this study. This post-doctoral position is part of 
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                . The main objective will be to functionalize the surface of these 3D metal parts, obtained by additive manufacturing, with a coating based on metal oxide nanoparticles. This coating must have a dual 
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                (pilot Aurélien Ponte). The objective of the position is to conduct a study (analysis, manuscript writing) aimed at correlating SWOT sea level data and GDP drifting buoy current data on a global scale 
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                (MERCE). The main objective is to develop safe planning and reinforcement learning algorithms with various degrees of confidence for variants of Markov decision processes. More precisely, we will develop