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participatory research, supported by supervisors in urban planning, climate adaptation, and social justice. It forms part of the Flood CDT and aligns with Loughborough University’s research on equitable
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under multiple environmental and socio-economic scenarios. You’ll develop sought-after skills in geospatial analysis, hydrodynamics, sediment transport, machine learning-assisted detection, and hydro
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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, the system will analyse data across multiple scales—from broad landscape views to microscopic symptom detection. Through vision–language AI models, the framework will interpret visual and textual data