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, understanding and predicting their thermal conductivity from first principles calculations is very challenging. In this doctoral research project, we plan to use machine learning potentials to investigate
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prostheses, and more broadly the emergence of brain–machine interfaces capable of bidirectional communication with the nervous system. In addition, they open new perspectives for personalized medicine
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, machine learning techniques, etc.) is desirable. This thesis offer within the AstroParticle and Cosmology Laboratory (APC) is part of the Deep Underground Neutrino Experiment (DUNE). DUNE is an
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functionalized surfaces. Key activities include: Modeling surface defects (e.g., vacancies, dopants, and functional groups) and their impact on catalytic charge transfer, in collaboration with experimental teams
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fabrication Prototyping Electrical and electronic engineering Numerical simulation Optics Computer-aided design (CAD) Optical and electrical characterization techniques Semiconductor materials # Soft Skills
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the impact of collective effects in high space-charge regimes. The Accelerators and Ion Sources Pole of LPSC is involved in the design, construction, and operation of the PERLE machine, particularly in
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is part of the PEPR-DIADEM GREENTEA project 'High-speed generation through machine learning of new thermoelectric sulphide alloys composed of abundant elements'. The generation of electricity from
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Sklodowska-Curie Doctoral Network linking 21 academic, cultural, and industrial partners to develop advanced nondestructive evaluation and data-driven digital tools for paintings and 3D artworks (https
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researchers have been heavily involved in the building of most current and future direct imaging instruments providing a unique access to these instruments: at the Very Large Telescope (VLT / SPHERE) and its
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The