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from motion blur, defocus, and imaging artefacts, which hinder accurate diagnosis. This project aims to restore image clarity by designing intelligent algorithms that recover fine anatomical details
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DEPARTMENT OF HEALTH TECHNOLOGY AND INFORMATICS Research Assistant Professor in Medical Laboratory Science / Biomedical Science / Medical Imaging and Radiation Science / Medical Physics / Medical
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. You will need to meet the minimum entry requirements for our PhD programme . You will have a strong interest in audio and demonstrate a high level of academic achievement in relevant subject areas and a
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decarbonisation, and advanced propulsion systems. The group plays a key role in shaping the future of marine digitalisation, intelligent maritime systems, and clean shipping technologies. About the role
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering
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-2026 JANUARY 2026 start ONLY For April and October starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme
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-2026 April 2026 start ONLY For January and October starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme
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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Behaviour-Based Anomaly Detection
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that can be independently transmitting, receiving, or both. By acting in unison, rather than in isolation, they can utilise temporal and spatial diversity whilst simultaneously exploiting shared, intelligent
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
intelligent methods that integrate large language models (LLMs) and knowledge graphs to interpret technical documentation and structure complex engineering knowledge. The goal is to create digital twins