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, Infected macrophage populations. Perform parameter estimation using optimization and machine learning approaches Develop numerical schemes for high-dimensional structured PDEs (pseudospectral methods
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Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
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Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 14 days ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09839 Requirements Skills/Qualifications Strong mathematical background. Knowledge in numerical optimization is a plus. Good programming skills in
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and microstructure-based modeling Experience with numerical methods for PDEs Programming skills in Python (knowledge of C++, Fortran or HPC is a plus) Scientific curiosity and critical thinking Ability
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shaping will be central to the study. The numerical model will be based on the boundary element method (BEM) and semi-analytical approaches developed at I2M. The experimental proof-of-concept will leverage
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regimes. This PhD project aims to develop predictive pore network models integrated with thermodynamics and upscaling methods toward reservoir-scale applications. We seek candidates with a strong background
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FieldEngineeringEducation LevelMaster Degree or equivalent Skills/Qualifications Desired profile Holding a Master of Science degree in Mechanics, the candidate has solid skills in numerical mechanics, numerical methods, and
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and microstructure-based modeling Experience with numerical methods for PDEs Programming skills in Python (knowledge of C++, Fortran or HPC is a plus) Scientific curiosity and critical thinking Ability
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the candidate will combine three levels of fidelity (first-principles based tool / RANS / Lattice Boltzmann Method) to design centrifugal turbomachines answering the needs of the project REVCO2. Numerical