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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
generate vast amounts of operational and maintenance data, much of it remains fragmented and underutilized. Unlocking insights from this unstructured data could enable earlier fault detection, improved
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analyse large datasets such as the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics to identify activity related to the treatment of community acquired pneumonia. This will require
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, driven by future applications and services for 6G and beyond. Networks are also evolving to support a large variety of signals across larger access and metro network areas. For these novel scenarios
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-free stipend only (set by the UKVI, £20,780 for 2025/26). Killer waves or extreme waves are large (> 20 meters tall) and unpredictable surface waves that can be extremely dangerous to ships and other
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
intelligent reasoning and feedback mechanisms into digital twin environments, enabling them to interpret complex maintenance data more effectively. Using AI techniques, such as large language models, knowledge
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and colleagues located across the 4 nations of the UK. HDR UK’s mission is to unite the UK’s health data to enable discoveries that improve people’s lives. Its 20-year vision is for large-scale data and
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. They therefore contain critical information on the nature of the volcanic system, immediately prior to hazardous explosive events. Understanding them will generate critical information on the transition between
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atmospheric chemistry. To address these challenges, a large aircraft project will deploy advanced instrumentation aboard the FAAM BAe-146 research aircraft during a dedicated measurement campaign in
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such approaches would be cost effective. To achieve this, you will be supported to undertake analyses using large data registries such as the Clinical Practice Research Datalink. This is an exceptional opportunity