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About Us In a nutshell Institutions & Location Glossary Research Scientific Orientation BIOLOGY CHEMISTRY & BIOCHEMISTRY MOLECULAR CONDENSATES BIOLOGICAL PHYSICS MATHS, COMPUTATION & AI Research
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NTNU and the application process here. ... (Video unable to load from YouTube. Accept cookie and refresh page to watch video, or click here to open video) About the position The Department
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their work at major international conferences. Applicants should have a 1st or high 2:1 honours degree (or international equivalent) in mathematics, physics, engineering, computer science or other related
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detection of chemical and microbial contaminants in rivers. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme, which is supporting new research
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of Sport, Exercise, and Nutrition Education – kimberley.edwards@nottingham.ac.uk This project is not funded, and we are seeking a student who can self-fund the PhD. Programme description: The overall theme
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We are looking for a PhD candidate to join the AI-Based Materials Science group in the Physics Department at the Technical University of Munich. In this position, you will work at the interface
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involved in analyzing data collected from the TexNet seismological monitoring program and other stations or assets that provide quality data. Comparing different methods and tools for moment tensor inversion
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Charles Sturt University | Charles Sturt University, New South Wales | Australia | about 15 hours ago
awarded an Australian Government Research Training Program (AGRTP) Scholarship or equivalent. The successful applicant will have the opportunity to work with Casella Family Brands . Prospective candidates
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Carl von Ossietzky University of Oldenburg • | Oldenburg Oldenburg, Niedersachsen | Germany | 1 day ago
defined four main research areas as the following: Environment and Sustainability Neurosensory Science and Systems Medicine, Health and Life Sciences Chemical, Physical, Mathematical and Computational
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computational challenges. This PhD project will investigate novel registration strategies for ultrasound-derived musculoskeletal point clouds. The work will focus on developing geometry-aware alignment methods