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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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, technicians, and staff. Each year, many undergraduate and graduate students, PhD candidates, postdocs, and visiting scientists join its activities. Research at LPS covers a broad range of condensed matter
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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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-permanent staff (doctoral students, postdocs, associate researchers and interns). The ICS has characterization platforms (UV-Vis and IR spectroscopies, size exclusion chromatography, light scattering, etc
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laboratory team is likewise highly recognized for its research in computer vision and neuro-inspired artificial learning. Both teams have been collaborating for four years on projects at the interface between
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published openly in the form of process flowsheet databases. Skills: Machine Learning/Deep Learning skills are essential, as well as programming proficiency, as well as some knowledge of energy or process
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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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, 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
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correlations or more innovative methods of multivariate analysis and we anticipate here an opportunity of using machine learning that could help in predicting properties or classifying sources. A last step will