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Field
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deformation microscopy, high-field MRI, clinical MRI, PET-MRI, and molecular read-outs. •Applying inverse finite element modeling (FE modeling) for the multiscale mechanical characterization of cartilage
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by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational
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-source computational tools in a project that aims to create life-saving technology to prevent devastating skull fractures in elderly populations. This unique position combines advanced finite element
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of virtual models (digital twins) for studying and detecting abnormal operating conditions (predictive diagnostics of anomalous behaviors) in distribution transformers using the finite element method (FEM
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-assembly), to macroscopic finite element analysis (strength, stiffness, fracture toughness). Experimental techniques (SEM, XRD, Raman, TGA) will validate the models, enabling robust predictions of composite
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for simulating such complex geometries. For example, the memory and computation time required become prohibitive with standard “black-box” finite element methods. The objective is therefore to develop a dedicated
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(mechanical, electromagnetic, and, possibly, fluid-dynamic) and multi-scale simulations for drone components using finite element tools (e.g., Abaqus, Comsol). · Supporting the development of an AI
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, 2025. We are looking for: The applicant should perform active research in numerical analysis of finite element or finite volume methods for coupled problems in one of the application areas of the group
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characterization, and/or component validation and verification. Strong background in CAD, finite element analysis, additive manufacturing, integrated computational materials engineering techniques and software
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suitable candidate for this project should have some knowledge of aspects of the design, analysis and/or implementation of finite element methods for partial differential equations. Prior experience in