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Field
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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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experience (PWLE) to co-develop an accessible "second skin" for the interface, ensuring usability and inclusivity. Assist in data analysis, including harmonisation of large-scale datasets and exploration
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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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data-driven approaches, multi-scale model development and software development depending on the interest of the successful applicant. Big picture: The Tarzia Research Group (https
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, as well as for their babies. You will work with large, complex datasets from national surveys and routinely collected health data to support impactful research. You will manage your own research
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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
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on an exciting Wellcome-Trust funded project. The research focuses on decoding neural representations across dynamic brain states through advanced computational analysis of large-scale neural recordings. What you
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. You will focus on machine learning, but will be involved in all areas. There are also spinout opportunities. For details: PhD information sheet The team have wide experience studying bumblebee behaviour
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(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by