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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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well as decentralized machine learning algorithms for large-scale clouds with dynamique parameters. -- Conception of machine learning algorithmes for resource allocation -- Numerical experiments -- Drafting research
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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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-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