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conferences. • Contribute to the writing of scientific publications. Optional : • Design Machine Learning (ML) potentials. • Code in FORTRAN and PYTHON to improve the functionality of the global
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elucidating the molecular and cellular mechanisms of the late phase of long-term potentiation (LTP), a key process in learning and memory. The project is based on the development and use of an innovative
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to the LabNBook and UNESS platforms (more than 60,000 cumulative users). Close collaboration with AI engineers, doctoral students, post-docs, and academic partners is planned. The candidate will work on the
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