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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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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 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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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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‘Architecture, Building and Civil Engineering’. Please quote the advertised reference number CENTA2026-LU02 in your online application. During the online application process please upload the CENTA studentship
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degree and/or industry experience in construction, infrastructure delivery, or sustainability – particularly with an understanding of lifecycle processes in the built environment – will be an advantage