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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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optimizations are still needed to adapt the translation of these mRNAs to the cell types of interest. As part of a collaboration with Chantal Pichon's team (University of Orleans), this project aims to use
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used to determine geometries and relative stabilities; to compute frontier energy levels, electron affinities, ionisation energies, reorganisation energies, and other descriptors linked to n‑type
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-processing pipeline for high-field MRI medical data (normalization, denoising, spatial registration) to optimize the quality and consistency of data used in analyses, and to facilitate the search
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well as their electrical characterisation. His/her role will involve overseeing all nanofabrication activities within the project, including the development of new cleanroom processes, as well as training PhD students in
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, time response, noise, cryogenic measurements) *punctual measurements on synchrotron might also be involved *Reporting of the results This project is part of the ERC AQDtive and ANR camIR (funded for 3