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interference, while ensuring energy-efficient and scalable operation. This PhD project will focus on developing machine learning algorithms to enable robust channel estimation, intelligent user association
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Rising temperatures are intensifying climate-related risks in cities worldwide, with the greatest impacts often felt by marginalised communities. This PhD project investigates how nature-based
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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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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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) offering a secure start to the work. This PhD will be an inter-disciplinary, using expertise on meteorology and co-occurring hydro-meteorological hazards (Chen, Hillier, Bloomfield) and insurance industry
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invite applications for a limited number of fully funded PhD studentships at the School of Physics, Engineering and Computer Science of the University of Hertfordshire. This is an exciting opportunity
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electronics, enabling spontaneous gaits powered by a single onboard pressure source. The project’s vision is to establish embodied oscillator intelligence, where locomotion arises from the physics of coupled
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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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Clinical PhD Programme Fellows Who we're looking for We’re seeking applicants who are: Clinically registered in the UK – with evidence of licence to practice at time of application Academically excellent