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Field
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interpreted using deep learning to estimate tool-to-retina distance and generate accurate three-dimensional navigation commands without relying on conventional 3D reconstruction. Research Objectives
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07.08.2026, Academic staff The professorship of Digital Structures with Mineral Materials is looking for an enthusiastic doctoral (PhD) candidate for a project on reinforcement of 3D printed
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of coronary artery disease and supporting clinical decision-making during catheterization procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop
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and synthesize via light-based 3D-printing architecture (meta)materials for medical soft robotics applications. Furthermore, the morphology, microstructure, and mechanical behaviour of the metamaterials
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-graduate, hands-on laboratory experience. Documented experience with advanced human cell culture, including 3D models and organ-on-chip systems. Hands-on experience with pluripotent stem cell culture
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. Demonstrated experience in one or more of: medical or optical imaging (e.g. OCT, MRI, CT); image processing and analysis of 2D/3D data; computational modelling, simulation, or optical system design. Proficiency
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of Josephson junctions. The methodology combines TEM, geometric phase analysis (GPA), chemical analysis (EDX), and growth modeling. Experiments using 4D-STEM coupled with electron ptychography will provide
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strains) and assess their role in CaCO3 dissolution, before and after pressurisation. • Develop and run multiphysics numerical models in COMSOL (3D geometries from tomography, transport–reaction coupling
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-level power, thermal and energy-efficiency models for future heterogeneous computing systems built on advanced CMOS technologies What you will do Continued technology scaling and the integration
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complementary information on 3D structure (GEDI lidar, BIOMASS P-band radar, NISAR L-band radar) and high spatiotemporal resolution (Sentinel‑1 C-band radar, Sentinel‑2 multispectral). State-of-the-art foundation