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Field
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The rapid growth of the data economy and the privacy implications accompanying it have motivated a new paradigm shift towards decentralisation of data on the Web, which aims to foster data
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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of contact (e.g. online chat, e-mail or telephone) and explore potential linkage to other helpline datasets (e.g. AgeUK). In the 2nd and 3rd year of the PhD research, the data will then be used to conduct
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Organization (WHO) estimates that 4.2 million premature deaths every year can be attributed to fine particulate ambient air pollution (PM2.5) [1]. Comprehensive information is required on air quality to provide
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Fixed-term: The funds for this post are available for 12 months A position is available for a Postdoctoral Research Associate (Postdoc) in the forthcoming Aspirational Computing Lab in
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-critical decisions in real time. These systems rely heavily on sensor data (e.g., GPS, pressure transducers, image processors), making them vulnerable to stealthy threats like False Data Injection (FDI) and
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November 2025 or as soon as possible thereafter. This PhD project aims to explore how emerging datasets could provide value to the UK’s insurance industry through a combination of data analytics, modelling
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are increasingly using self -funded services via pharmacies, getting both medicines and health advice to treat common infections without seeing a doctor. The vast “smart data” that these interactions are producing
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
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the population from infectious diseases and other hazards. UKHSA does this by monitoring infectious disease trends and outbreaks using systems that collect information over time and allow unusual changes to be