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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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to eruptive activity. These transitions pose significant challenges to hazard management (1). Physical parameters, such as the location, geometry, and size of the volcanic system, and their changes over time
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can feed directly into precision surgery algorithms and clinical trials. Few PhD projects offer such a clear line of sight from variant to mechanism to clinical translation. Located on the thriving
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observations and modelling of the physics and biogeochemistry of Antarctic shelf seas. You will gain experience in computer coding, statistics for environmental science, working with and piloting autonomous
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. Communication of scientific findings through publications and conferences. Person Specification A highly motivated candidate with: A degree or equivalent in numerate, computational, or environmental subject areas
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Primary Supervisor - Dr Marius Somveille Background Seabirds are highly mobile organisms connecting distant regions across the world’s oceans and seas. While being important contributors to marine ecosystems, seabirds are also particularly threatened by human activity. To design effective...
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at the John Innes Centre, providing opportunities to develop extensive skills in a breadth of areas, including field surveys, plant pathology, molecular biology, and computational biology. Additionally, you