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be done via computer simulations, including Monte Carlo and molecular dynamics, combined with the use of statistical mechanics to predict e.g. phase transitions, nucleation rates, etc. The work will be
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for such applications. To respond to these challenges, this project aims to investigate automated decision making based on machine learning. The candidate (H/F) will propose and validate centralized as
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, engineering, bioinformatics, machine learning, artificial intelligence) to support minimally invasive and targeted preventive and predictive medicine capable of limiting age-related functional disorders
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by exploiting foundational machine-learning potentials such as MACE, SevenNet, or Orb-V3. The predictions will then be progressively refined and verified by DFT and, ultimately, tested experimentally
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via thermodynamic power cycles. However, conventional expansion machines (turbines or volumetric devices) face significant limitations at low power scales: - Turbomachinery suffers from reduced
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qu'avec un.e autre doctorant.e et deux post-doctorant.e.s également recruté.e.s via JET2SB. Le.a doctorant.e fera donc partie d'un effort de recherche particulièrement dynamique. Dans le cadre du projet
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this thesis, the student will interact with researchers from these three teams, as well as with another doctoral student and two post-doctoral fellows also recruited via JET2SB. The doctoral student will
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be highly interdisciplinary. Two different profiles are possible for this position: either a profile in engineering sciences or biomedical physics, with a strong desire to learn about microbiology
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, to understand particle formation and defect incorporation mechanisms. 2. Optimize the optical properties of G4V-NDs via original post-synthesis treatments, with in situ testing at the SOLEIL synchrotron
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/InstituteInstitut Jacques MonodCountryFranceCityPARIS 13Geofield Contact City PARIS 13 Website http://www.ijm.fr/ STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket