7 machine-learning-"https:"-"https:"-"https:"-"https:"-"University-of-St" PhD positions at Loughborough University
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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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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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. Current XAI methods are often generic and overlook industrial realities. This project will embed user-centric explanations directly into machine learning workflows using structured, ontology-driven
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, programming, signal analysis or machine learning are particularly valuable. If you are keen to apply technology to improve global healthcare, we would be delighted to hear from you. Entry requirements
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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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of real-time adaptive 3D inspection, dynamically adjusting its measurement strategy based on data quality as well as environmental and scene cues. Positioned at the intersection of robotics, computer vision
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datasets across variable illumination, wave states and turbidity, enabling hybrid deep-learning and iterative optimisation solutions with clear lab-to-field transferability. Entry requirements: We