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the gap between numerical simulations and clinical practice. The candidate will work alongside experts in solid mechanics, finite element analysis, and machine learning and cardiology, benefiting from
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materials. The primary focus of this work is on mechanical characterization, microstructural analysis, and finite element analysis (FEA) and artificial intelligence (AI)/machine learning (ML) modeling
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experiments and numerical simulations and will be divided into three parts: Microstructure: 1.1. Experimental Characterization: Using X-ray tomography, image analysis with conventional tools or deep learning
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Required Skills: • Numerical (finite element) and experimental mechanics. • Mechanical modeling of hyperelastic materials. • Data analysis and programming (preferably Python). Internal Application form(s
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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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, biomedical engineering, or a related field. • Strong background in musculoskeletal modeling and finite element analysis (preferred). • Proven experience in presenting research at international cferences
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outstanding grades Excellent knowledge of continuum mechanics and finite element analysis Excellent coding abilities in at least one language Knowledge and experience with fracture mechanics and/or phase-field
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programming, as well as experience programming in python with jupyter notebooks. Experience and demonstrated knowledge in CAD design and drawing. Experience in computational models in finite elements, with
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. Duties You will be responsible for developing a damage coupled diffusion finite element model that captures the progressive destruction of cell walls during chemical delignification as
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reviewed journals and previous experience in experimental work and Finite Element Analysis (FEA) are essential. Proven management, networking and administration skills are also desirable as the post holder