38 computer-science-image-processing positions at Technical University of Munich in Germany
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advanced machine learning methods for multimodal and 3D medical image analysis in musculoskeletal medicine, in close collaboration with clinicians and computer scientists. PhD or Postdoctoral Researcher
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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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learning, computational mathematics, and probabilistic modeling, with direct applications in medical imaging and beyond. Details can be found in the link below. The position is suitable for disabled persons
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learning, computational mathematics, and probabilistic modeling, with direct applications in medical imaging and beyond. Details can be found in the link below. The position is suitable for disabled persons
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between the fields of computer sciences and architecture. The focus lies mainly on Building Information Modelling, decision-support methods in urban planning and knowledge-based design methods. As part of
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methods in AI and machine learning, contributing directly to state-of-the-art research with high industrial relevance. Your Qualifications A strong background and Master's degree in Computer Science, AI
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/d) in Energy Informatics, specifically for a DFG project in wind power forecasting using machine learning. You are passionate about applying cutting-edge information technology to solve the energy and
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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: Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines (typically mathematics, physics). For Postdoc applicants: Excellent track record in computer science
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efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation