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biosensor, transforming an existing prototype technology into a deployable environmental monitoring solution. Building on recent innovation at Exeter, this PhD will translate a novel discrete gape-sensor unit
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deliver this service, and on what scale? This PhD project will provide the tools to answer that question. Building on data and findings from the UK’s CONVEX seascape survey, this studentship will
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industries. Using existing plans, remote sensing and laser scanning field-surveys, they will build lab-based digital replicas of UK post-extractive underground and overground landscapes. Then they will import
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
representations and embedding techniques that allow LLMs to natively interpret spectrum-related information, capturing the unique temporal, spatial, and physical characteristics of 6G signals. Building
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. The ML will use 500,000 fundus images from open-source and customised retinopathy datasets. We will compare retinopathy grading accuracy by NHS clinician vs ML algorithm. This will build on Exeter’s
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crop conditions. Building on our European Space Agency (ESA)-funded project to correct InSAR phase bias, we will investigate: (1) whether loop closure-derived time series can reveal phenological changes
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This project is a fully funded MSc by Research Scholarship in Medicinal Chemistry / Synthetic Organic Chemistry and builds on a successful decade-long research programme at the University of Exeter