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implement and train neural network architectures, including Physics-Informed Neural Networks (PINNs), in order to integrate physical constraints into the learning process and improve the identification and
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concerned the conversion of (thio)esters into (thio)ethers via nickel-catalyzed intramolecular decarbonylation. This research axis was explored through a PhD project carried out in the laboratory and has
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architecture, coat assembly, and organelle identity. By investigating how cells build and remodel carriers and compartments around oversized cargo, the project seeks to reveal general principles of secretory
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in proposing new molecular architectures in relation to the targeted application; He/she will also take the lead in measurements using near-field techniques and interactions with our physicist