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uncertainties (delays, resources, failures) using various methods, including Bayesian approaches. 3. Optimize the workshop configuration, taking into account scenario variability, by relying on the surrogate
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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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Complex sugars (CS) are key ligands for modulating the pharmacological properties of proteins, triggering specific cellular responses, and enabling targeted vectorization in biotherapies. There is therefore
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to its host and its persistence in order to identify potential therapeutic targets. This project aims to identify and validate the function of regulators or actors of specific metabolic pathways using
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that operate in aqueous environments - the engineering of polymers, nanoparticles, or nanostructures for targeted functions and applications. Team 2, entitled “Biopolymers and Bio-based Polymers,” is led by
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research contractors. Through the design and characterization of new materials, the laboratory's approach leads to the optimization of a wide range of properties for targeted applications. The position is in
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input fields and then regress on the target variables in the embedding space. However, many challenges remain to be solved with this approach (regarding the use of CNNs vs Vision transformers
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program on detection techniques, laser techniques, data acquisition techniques for experiments, and the manufacture of targets and thin films. The FIRE group is responsible for welcoming external teams and