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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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exciting opportunities for machine learning to address outstanding biological questions. The PhD student to be recruited will be working on the development of machine learning methods for single-cell data
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interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms
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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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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 22 hours ago
tools for solving these problems. The goal of this PhD is to understand how these results could be integrated or inspire the designing process of the models for the deployment and the execution of Cloud
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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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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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21 Aug 2025 Job Information Organisation/Company CNRS Department Institut des sciences analytiques et de physico-chimie pour l'environnement et les matériaux Research Field Physics Researcher Profile First Stage Researcher (R1) Country France Application Deadline 10 Sep 2025 - 23:59 (UTC) Type...
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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, including 180 permanent staff (researchers, professors, engineers, technicians, and administrative personnel) and around 180 non-permanent staff (PhD students, postdocs, and fixed-term contracts). Each year