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. This PhD project is part of a collaborative research effort involving three academic laboratories (IES-Montpellier, PROMES-Perpignan, LaTEP-Pau) and a deep-tech start-up (EXTRAJOOL-Bordeaux), bringing
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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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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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: ANR JCJC “NanoG4V” : ANR-24-CE51-7558 Expected Outcomes By the end of the PhD, the candidate is expected to: • Acquire solid expertise in the synthesis and advanced characterization of quantum-grade