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Field
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, collaborating with multidisciplinary teams, and staying updated with advancements in the field. This position requires expertise in hydrodynamics, FEM, stability modeling, and a hands-on approach to field testing
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) Signals.” The project aims to develop parametric methods for generating realistic PPG signals. The work includes mathematical modeling, differential equation solving, finite element method (FEM) integration
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Qualifications Background in Generalized/eXtended FEM (e.g., GFEM, XFEM, N/IGFEM). Background in reduced-order modeling (e.g., eigendeformation-based reduced-order Homogenization Method (EHM)). Background in
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pressure range with expected installation in 2025, for in situ and operando studies under gaseous conditions. You will develop the Fluctuation Electron Microscopy (FEM) technique using most advanced STEMs
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or doctoral Degree in Communications/Electrical Engineering, Physics, or comparable disciplines Academic background with a focus on optical-wireless communication Experience with FEM-based electromagnetic
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following skills and qualifications are expected to support the team in addressing key challenges: Solid experience with FEM-based analysis tools (e.g., COMSOL, ANSYS) for thermal analysis of power components
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orders of magnitude pressure range with expected installation in 2025, for in situ and operando studies under gaseous conditions. You will develop the Fluctuation Electron Microscopy (FEM) technique using
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. Extensive experience in the development and application of finite element method (FEM) or comparable methods for AM applications. Preferred Qualifications: Demonstrated expertise in multi-physics simulations
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this position, you will have: PhD degree in relevant field Demonstrated knowledge of structural analysis of alloy components, Finite Element Modelling (FEM) and preferably morphology/topology optimisation
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influence of microstructure. The modelling will encompass methods for representing microstructures in simulations, crystal plasticity, homogenisation techniques, FEM, and parameter identification based