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, structural optimization, coupled problems, and experimental mechanics, with applications to metals, polymers, fibrous materials, and granular materials. Numerical methods, such as the finite element method
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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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(including, but not limited to, phylogenetic analysis, morphometrics, or finite elements modelling) are expected. Extensive participation and / or experience in leading fieldwork is expected. The successful
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experiments on structural frames, members, and components Conducting thorough investigations utilizing finite element analysis Assessing seismic performance through macro modeling of structures Disseminating
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Engineering or a closely related discipline. You will have demonstrable experience in one or more of the following areas: Finite Element Analysis, Computational Fluid Dynamics, Discrete Element Method, Multi
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
to develop a digital twin of the process. The approach is to couple phenomenological models obtained by AI processing of experimental data with Finite Element Models (model reduction by AI) and Cellular
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to be developed: Carry out 3D design of parts and assemblies in Creo Parametric and/or Creo Elements. Calculate and simulate using finite elements. Prepare plans and documentation for manufacturing. Where
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assigned. (2%) Required Education and Experience Master’s Degree in relevant field of engineering 3 years of related professional experience to include non-linear finite element modeling and simulation
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research methodology is coupled CFD (Computational Fluid Dynamics) and FEM (Finite Element Method) modelling and simulations. This is the only methodology allowing simulations of fluid-structure interaction
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include the development of finite elements methods, as well as inverse design strategies based on deep-learning and Neural Networks approaches. The latter will then bring the project to the experimental