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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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general, and specifically on systems with characteristic nanoscale features. They use finite element and ab initio software as numerical tools for modelling and analysis. We are seeking highly qualified and
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Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | about 1 month ago
parallel and heterogeneous architectures, permits the integration of advanced interoperable CFD components, including in particular Finite Volume (FV) as well as Finite Element (FE) methods, namely
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mathematics. An important aspect of the ongoing research is solving stochastic partial differential equations on surfaces, e.g., with surface finite element methods. Who we are looking for The following
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implant positioning influence stresses in the bone and risks such as wear, impingement, and dislocation. By combining innovative motion analysis techniques with finite element modelling, the research will
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 28 days ago
component to conceive novel setups and collect data to compare with simulations. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2025-09688 Requirements Skills/Qualifications
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expertise in the analysis and design of concrete structures. Advanced proficiency in Finite Element Modelling (FEM) using tools such as Abaqus, ANSYS, RFEM, SAP2000, MIDAS or equivalent. Solid understanding
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mathematics. An important aspect of the ongoing research is solving stochastic partial differential equations on surfaces, e.g., with surface finite element methods. The following requirements are mandatory: A
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structure-preserving discretization algorithms (a refinement of finite-element analysis compatible with exact geometric, topological, and physical constraints) with artificial neural networks for achieving