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on the project can be found here: https://hecustom.eu/ TSR patients now expect to regain the full, complex range of motion needed for everything from fastening a seat-belt to serving a tennis ball. Yet
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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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/mod/aboutand our linkedIn page: linkedin.com/showcase/lmsd-kuleuven/. The PhD will be co-supervised by prof. Varvara Kouznetsova (https://www.tue.nl/en/research/researchers/varvara-kouznetsova ) from
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and Projects (FEM) serves as the University’s strategic lead for campus-wide utility infrastructure, energy and water systems, engineering compliance, and regulatory standards. This position provides
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conducting solid oxide cells (E) Skills & Abilities Practical experience of applying computational techniques to the modelling of microstructure in solid oxide cell technologies (e.g. FEM, Gaussian, Bayesian
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common CAD and FEM software tools are beneficial We offer: a wide range of opportunities for individual professional development through central training courses provided by the research network or TU
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of the proposed doctoral individual project: The doctoral candidate will carry out the individual project titled: “Optimization of Functionally Graded Osteochondral Scaffolds” Objectives: 1) analyse existing FEM
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) Corrosion behavior (electrochemistry & high-temperature oxidation) In-situ monitoring of AM processes Computational skills in: Phase-field modeling, Machine Learning, FEM, DEM, COMSOL Alloy design (CALPHAD
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modeling of highly compact power electronic converter systems. Verification of the concepts using modern circuit simulators as well as FEM simulations. Construction of laboratory prototypes to verify