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visiting SRC for collaborative data processing and participating in seismic survey on the island arc. The candidate will benefit from working with a large multi-disciplinary research team recently funded by
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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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ecology and oceanography, the project will leverage large existing datasets on (i) the movement of migratory seabirds throughout their annual cycle, available via BirdLife’s Seabird Tracking Database (STD
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ability to evaluate fossil fuel CO2 (ffCO2) emissions is currently limited. ‘Bottom-up’ emissions estimates, based on inventory-style accounting and mobile tracking data, can differ significantly from each
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spectroscopic methods suitable for large-scale sample screening and eventual field deployment. The project will also involve developing your skills in data science, including multivariate analysis, machine