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Technology, Mechatronics, Robotics, Systems Engineering, Applied Mathematics, Technomathematics, Computer Science, Engineering Informatics, Theoretical Computer Science, Physics Description Description
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in Astronomy, Biology, Computer Science, Chemistry & Materials, Data Science & Scientific Computing, Earth Science, Mathematics, Neuroscience, and Physics in a world-class research environment
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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academic area such as applied mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and
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As Austria's largest research and technology organisation for applied research, we have set ourselves the goal of making substantial contributions to solving the major challenges of our time: climate change and digitalisation. With a high standard of excellence, we are working to make a...
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Location: Students will be based at the CREWW building on Streatham Campus in Exeter. Flooding is the most common natural disaster, impacting billions worldwide. Natural Flood Management (NFM), a nature-based solution opposed to traditional ‘grey’ engineering, offer catchment-level solutions by...
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Physics is looking for a PhD student in computational physics with a focus on understanding
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Postdoctoral Opportunity : Nuclear Physics and Applications – UM6P About Mohammed VI Polytechnic University (UM6P) Mohammed VI Polytechnic University (UM6P) is a leading African institution
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REQUIREMENTS: A Master’s degree in Biology, Biomedical Imaging, Physics, or a related discipline A strong interest in in vivo imaging, cell tracking, functional cell analysis, and data interpretation Previous
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perpetuation (or maintenance/persistence); to build ML models that include the heart’s physical properties to find patterns in the data and predict which areas in the heart drive AF. This project will explore