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ElastoGravity Signals. Journal of Geophysical Research: Machine Learning and Computation, 1, e2024JH000360. https://doi.org/10.1029/2024JH000360 Juhel, K., Hourcade, C., & Bletery, Q. (2024). PEGSGraph : GNN
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in the field of operational research and/or machine learning algorithms would be a plus. In accordance with the commitments made by the CEA to promote the integration of disabled people, this job is
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archaeological and historical contexts is also required. Additionally, the ability to perform *ad hoc* data processing (multivariate statistics, machine learning, etc.) is desirable. Proficiency in programming
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of technological disruption driven by Artificial Intelligence, we propose to analyze the data and quantify these similarities by exploring various applications of machine learning methods. With the advancement of AI
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, ideally molecular dynamics and/or DFT. Scientific programming skills, particularly in Python, are expected. Familiarity with machine learning or generative AI methods applied to materials would be a strong
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/F) will work within the “RNA Architecture and Reactivity” unit and join the “Structure, Dynamics, and Targeting of Biomolecular Machines” team. This team currently consists of 6 researchers, 3
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. Development and integration of state-of-the-art machine learning techniques in the analysis and event reconstruction will be a major component of this work. - Characterization of silicon detection modules using
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IRCM - Cancer Research Institute of Montpellier | Montpellier, Languedoc Roussillon | France | 3 months ago
dedicated to developing new antibody-based biotherapies and diagnostic tools for solid tumors, auto-immune diseases and emerging viruses. The team uses in vitro selection approaches and home-made designed
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Specific Requirements Required Profile: Master degree in computer science or applied mathematics, Engineering school. Background and experience in machine learning. Good technical skills in programming
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to correlate polymerisation kinetics, macromolecular architecture, morphological evolution and drug encapsulation mechanisms. Beyond experimental work, the project will integrate machine learning approaches