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computer aided methods. Qualifications and Experience • Outstanding academic degree in materials science, metallurgy, metal physics or similar degree • Excellent doctorate with focus on computational
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and the Institute for AI and Informatics in Medicine, both at TUM and the TUM University Hospital (Klinikum rechts der Isar). We develop and translate advanced machine learning for 3D/multimodal medical
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area has received best paper awards at PacificVis and Graph Drawing, with recent publications in IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum. Environment
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography
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, Human-Computer Interaction, and their responsible applications. Ideal candidates will have: An M.Sc. degree (or equivalent) in Computer Science, Game Engineering, Mathematics, Statistics, or related
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://mediatum.ub.tum.de/doc/1687691/ltbbjgwihiht96fqfeblxdyj7.ITSC22_CommonOcean.pdf Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines
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academic assignments at the chair What we look for in you Completed master’s degree in computer science, transportation, or related engineering fields Solid background in generative AI, machine learning, and
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epithelial cell biology, cellular metabolism and mitochondrial function. Experience in mouse models and ex vivo organoid culture is a prerequisite. The candidate should also have the ambition and commitment
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of Orthopaedics and Sports Orthopaedics and the Institute for AI and Informatics in Medicine. We work at the intersection of artificial intelligence, medical imaging, and clinical practice, developing methods
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at the TUM School of Life Sciences PhD studentship (m/f/d): Tree Carbon Allocation to the Rhizosphere and Related Microbial Processes under Severe Drought Join the new EU-funded FutureForests international