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Researcher will influence the direction of application areas and algorithm development, receiving direct training in InSAR processing, geospatial data science, and agricultural remote sensing. Co-supervision
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
generation of wireless communication (6G) to extend network coverage, supporting diverse data-intensive applications such as immersive extended reality and autonomous systems. However, aerial 6G networks will
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The University of Exeter has a number of fully funded EPSRC (Engineering and Physical Sciences Research Council ) Doctoral Landscape Award (EPSRC DLA) studentships for 2026/27 entry. Students will
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Geological Survey, Centre for Ecology and Hydrology, the Natural History Museum and Plymouth Marine Laboratory. The partnership aims to provide a broad training in earth and environmental sciences, designed
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are fundamentally limited by a "one model for one task" design philosophy. This approach incurs prohibitive engineering costs and yields brittle solutions with poor generalisation to new network conditions, trapping
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. This PhD project will investigate the interactions between wildfire disturbance and thermokarst dynamics across Siberia and other Arctic regions using multi-sensor satellite remote sensing data provided by
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: Advancements in biosensor technology are at the forefront of modern biomedical research, addressing the growing need for precise, real-time monitoring of biomolecules and overcoming critical challenges in
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the Southwest. Geospatial and engineering analyses will identify optimal sites and system configurations, while collaboration with the Law School will assess legal and regulatory frameworks, planning constraints
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), machine learning (ML), deep learning (DL) and Data science methods for medical image analysis, to autonomously grade the fundus images from large datasets. This will be supported by Professor Neil Vaughan
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to quickly quantify the damage to forest plantations after a cyclone or a tropical storm. There is unrealised potential in using multi-modal computer vision methods that synthesis multi-source Earth