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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | about 8 hours ago
dozen passes are regularly made. One of the challenges of the project is to propose numerical approaches that enable these simulations to be carried out within a reasonable time frame, given the volumes
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position is the development of novel machine learning methods for modeling molecular properties, in particular regression models for bi-molecular properties. The research is embedded in the thematic context
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to develop strong skills in viscous fluid mechanics, numerical methods and applied mathematics. Start date: October 2026. Duration: 4 years. Education: A strong 4-year degree or MSc degree in Mechanical
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until the grant's contract is done; proven previous experience with articles published in first quartile journals (Q1) on the Discontinuous Galerkin Finite Element Method (DGFEM); experience implementing
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mechanics, or advanced material behavior. Programming skills (e.g., Python, MATLAB, Julia,..), ideally with experience in numerical methods or scientific computing. Familiarity with machine learning
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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experimental research work on free and confined flames in a laboratory environment. Workplan and the objectives to achieve: The work to be developed consists of the experimental and numerical investigation of a
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skills to model and design optical systems for sustainable high-tech devices for billions of people? Do you like to develop and analyze numerical methods for partial differential equations? Information
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on the numerical modeling results. Physical Oceanography, 27(4), 352–363. https://doi.org/10.22449/1573-160X-2020-4-352-363 Sokolov, A., Chubarenko, B., 2024. Baltic Sea wave climate in 1979–2018: Numerical