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Field
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innovative computational approaches, leveraging finite element simulations, AI, and clinical data, to better understand the mechanisms of MR. This aims to improve patient risk stratification and treatment
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-suited. By the end of the PhD, the candidate will have gained strong skills in experimental mechanics, test management, materials characterization, and numerical modeling, particularly finite element
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combination of experimental testing and computational modelling (Finite Element Analysis) to create solutions that accelerate the safe deployment of hydrogen aviation technologies. This position is part of
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required. Experience with finite-element method (FEM) and boundary-element method (BEM) is required. Experience with supervised machine learning in aeroelasticity is required. Programming skills, e.g
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efficiently work in a highly multidisciplinary team. You have a strong background in linear and tensor algebra, non-linear mechanics, advanced finite element analysis, computational solid mechanics
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Experience in non-linear finite element analysis and solid mechanics Experience in optical measurements related to experimental work Experience with 3D computer-aided design (CAD) software Experience with
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) + Finite element methods for complex flows in porous media (generalized multiscale finite elements via autoencoders, adaptive in space and time, splitting methods, and variational flux recovery) + Adaptive r
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factors that accelerate material deterioration (e.g., hydrogen embrittlement, corrosion). The primary tasks include developing advanced multiphysics frameworks (finite element/phase-field methods