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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in Germany. It offers a modern, interdisciplinary, and international working environment in the city of Dresden, one of Germany’s most vibrant places. For...
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fields: Robotics Computer Science Electrical and Computer Engineering Mechanical Engineering Applied Mathematics Applied Physics Statistics and Optimization A strong background in robotics, machine
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. The enhanced image quality will support earlier and more reliable detection of eye diseases. Combining artificial intelligence with mathematical modelling, this non-invasive, cost-effective approach has
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performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling
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in a subject relevant to the proposed PhD project (such as mathematics or theoretical physics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the
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. Responsibilities and qualifications The nature of this project suggests that you should have a strong interest in the mathematical and theoretical aspects of machine learning. A solid background in mathematics (e.g
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TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in Germany. It offers a modern, interdisciplinary, and international working environment in the city of Dresden, one of Germany’s most vibrant places. For TUD...
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innovative and creative research in theoretical quantum physics, including mathematical modeling and phenomenological and numerical analysis. The PhD student should display scientific ambition and target
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 26 days ago
, Applied Mathematics, Physics, Biophysics or a similar qualification Interest in and/or experience with AI/machine learning A willingness to learn and extend this knowledge and master new challenges in
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develop probabilistic guarantees that quantify uncertainty in human preference alignment while ensuring robustness against adversarial conditions. The ability to mathematically verify AI alignment has