59 post-doc-image-engineering-computer-vision Postdoctoral positions at Technical University of Munich in Germany
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activities. ________________________________________ Candidate Requirements ✅ PhD degree in Engineering, Computer Science, Systems & Control, Statistics, Computational Physics, Computational Chemistry
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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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deep learning / computer vision / biomedical image computing Excellent English; German is an advantage for clinical collaboration We offer Highly interdisciplinary, translational research environment
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Garching campus. TUM’s Department of Computer Science is part of the TUM School of Computation, Information and Technology (CIT). Employment Conditions • Start date: Flexible, from January 2026 onward
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02.07.2025, Wissenschaftliches Personal The Professorship of Energy Management Technologies at TUM’s School of Engineering and Design is looking for a Postdoc (f/m/d) in Energy Informatics. You are
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programming for workflow automation and data handling Familiarity with high-content imaging and quantitative analysis is a plus Interest in interdisciplinary approaches at the interface of biology, technology
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18.10.2022, Wissenschaftliches Personal The lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is looking for a Post-Doc. The task will be the multi-modal modeling of medical data
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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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polycephalum arises from the interactions of cell nuclei within the gigantic cell. We are looking for a Post-doc (m/f/d) to start at the TUM this summer or fall. Your Task Physarum polycephalum is renowned
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engineering, and quantitative live-cell imaging to probe and model these processes. By combining stem cell biology with cutting-edge microscopy and physical concepts, we aim to establish a predictive framework