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system using 3D medical imaging modalities (CT, MRI, PET) and explainable AI (XAI) techniques to support medical professionals in improving diagnostic accuracy, reducing workload, and enhancing patient
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geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics
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well as medical imaging tools such as itk-SNAP, LinkEHR, 3D Slicer, and Fiji. - Experience working in multidisciplinary teams and European projects, with strong skills in coordinating multidisciplinary teams
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biomechanics, prosthetic engineering, virtual reality, 3D printing, amputee rehabilitation, epidemiology, biopsychosocial aspects of limb loss, and orthopedic surgery. As a member of the Division