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global change, damaging critical infrastructure resilience. This project is part of the prestigious Loughborough University Vice Chancellor’s PhD Cluster – RAINDROP (Resilient eArthwork INfrastructure
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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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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the 'Apply' button above. Under programme name, select School of Architecture, Building and Civil Engineering. Please quote the advert reference FCDT-26-LU8 in your application. This PhD is being advertised as
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-26-LU4 in your application. This PhD is being advertised as part of the Centre for Doctoral Training for Resilient Flood Futures (FLOOD-CDT). Further details about FLOOD-CDT can be seen at https
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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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lithology, climate, catchment size), with sediment and laser scanning data offering a secure and rapid start to the work. This PhD has an international supervisory team providing expertise in volcanic island
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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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should be made online . Under programme name, select School of Architecture, Building and Civil Engineering. Please quote the advert reference FCDT-26-LU9 in your application. This PhD is being advertised