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for candidates with a background in meteorology, climatology, physics, engineering and any related discipline, and a strong interest in applying advanced physical and computational methods to real-world
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). Atmospheric rivers are poorly forecast on the subseasonal scale, and regions identified as having particularly poor skill include the Indian monsoon region, Madagascar, and Indonesia (DeFlorio et al., 2019
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for career development in environmental science. For further information on this project and details of how to apply to it please visit https://centa.ac.uk/studentship/2026-b15-a-multi-scale-quantitative
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astrophysics, and reproducible research software development. Candidate Profile We welcome all applicants with a background in: • Physics, Astrophysics, Data Science, Applied Mathematics or a related field
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) honours degree (or equivalent) in subject specific area like meteorology, physics, climate sciences or related subject areas. Applications should be made via the above 'Apply' button. Further information
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Driven by our data hungry society, chip-to-chip and device-to-device data bit rates will need to reach terabits per second in a not distant future. Such data rate will only be met if there is a
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peristalsis throughout the intestine. The outcome will address a clear clinical need by providing sensitive, localized motility data to improve diagnosis of neuromechanical GI disorders. The sensor will rely
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rigidity to penetrate without damaging tissue and stability against peristalsis. The device will also include onboard electronics for wireless data transfer to an external receiver. The device will be tested
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the rich, unstructured information found in clinical notes and cannot effectively gather data on lifestyle and social determinants of health. This PhD project will pioneer a novel, hybrid AI framework
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collaboration with modelling or industrial partners Candidate Requirements We welcome applications from candidates with the following background: Academic degree (BSc / MSc or equivalent) in Materials Science