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for the detection of trace amounts of pollutant molecules (BTEX) in aqueous environments (saline or fresh water). He/she will contribute to the implementation of the complete optical system and associated
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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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professors, one senior lecturer, and four CNRS researchers. The team is working jointly on two projects: TESSERACT, which aims to detect light dark matter and is funded by the TES4DM project, and Ricochet
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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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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
) Context of the project: We are interested in the numerical simulation of eddy current testing (ECT). The target application is the non-invasive detection of flaws within highly conductive metallic
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Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Objective 1: The goal is to develop a medical device incorporating
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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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of London Cancer Institute. Objectives: The aim of the project is to study chromatin remodeling defects in cancer. The successful candidate will be responsible for designing and executing experiments
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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