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. These components see applications in the transport, catalysis and bioengineering industries. The research will focus on wet chemical processes and the study of chemical reactions on the component's surface. We will
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proposal. This PhD will evaluate the efficacy and suitability of digital image collection and analysis for beach litter characterisation on heavily-littered coastlines, in partnership with community groups
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as early indicators of anthropogenic and climate-driven change. However, limited understanding of the processes shaping species’ biogeographic distributions constrains our ability to predict ecological
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). The successful candidate will design and prototype intelligent textile/wearable systems capable of sensing, communication, and stimulation. The project will integrate wearable electronics, advanced manufacturing
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, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
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This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
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heat flux. Design, modify, and test novel heating surfaces that more accurately replicate industrial conditions. Develop advanced post-processing methods to extract key local quantities associated with
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theories and models. This project aims to develop new insights into how bedrock incision processes interact with geological and climatic factors (i.e. spatially variable uplift, shield building, mega
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by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large
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familiarise yourselves with FLOOD-CDT before applying. During the application process candidates will need to upload: a 1 page statement of your research interests in flooding and FLOOD-CDT and your rationale