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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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Your Job: We are looking for a PhD student in machine learning to work within a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop 3D+t
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-based 3D microscopy” Where to apply Website https://reclutamento.dsi.infn.it Requirements Research FieldPhysicsEducation LevelMaster Degree or equivalent Specific Requirements Candidates must meet the
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candidate will undertake a range of activities, including: Contributing to a project investigating how 3D engineered microenvironments modulate stem cell behaviour in osteoarthritis, working under
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on applying computer vision, machine learning, and sensor fusion to automatically detect, classify, and localize defects, improving the scalability and reliability of building inspection. Research on 3D
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2023.12614.PEX, title 3DBIOGEL4HEALTH – Exploring the 3D BioPrinting for Design of Novel Biodegradable Hydrogels as Lutein Carriers. The call is governed by this Notice of Opening, the University of Coimbra
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composition data and physical capability of children ages 3 through 17. You will work in an engaging work environment with access to leading research tools, such as high-resolution 3D body scanning technology
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detailed records of findings Students may also work with analytical and clinical software such as MATLAB, Qualisys, Visual 3D, and Power BI, and contribute to literature reviews or research documentation
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gene. Development, 140(21), 4362–4374. https://doi.org/10.1242/dev.098061 Sánchez-Posada, J., Derrick, C. J., & Noël, E. S. (2025). morphoHeart: a novel quantitative tool to perform integrated 3D