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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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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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(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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, 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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to determine what type of heat therapy protocols are well tolerated and can be well integrated into people’s life. Therefore, this programme of study aims to develop practical and feasible heat therapy protocols
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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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Science, Computer Science, Engineering, or an appropriate Master’s degree. English language requirements: Applicants must meet the minimum English language requirements. Further details are available
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University. How to Apply: All applications should be made online via the above ‘Apply’ button. Under programme name, select ‘School of Social Sciences and Humanities’. Please quote the advertised reference
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the above 'Apply' button. Under programme name, select ‘School of Social Sciences and Humanities’. Please quote the advertised reference number, ‘FCDT-26-LU2’, in your application. This PhD is being
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University. How to Apply: All applications should be made via the 'Apply' button above. Under programme name, select Department of Geography and Environment. Please quote the advertised reference number: FCDT