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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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effective delivery of expertise, equipment, and medical resources in response to complex and large-scale emergencies across the United Kingdom. In its initial phase, the research will examine past and
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will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show challenging properties of uncertainty, irregularity and
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with, or keen interest in, large data sets Funding notes: This scholarship covers (UK home) tuition fees and stipend. The stipend is the national UK standard.
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opportunity for a motivated scientist to unpick the impact of host factors on tumour structure. To lead this research as a doctoral student you will be passionate about using large-scale data to address
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. The student will perform ‘big data’ analysis of patient cohorts including time-based evaluation of the impact of introducing CT-FFR as a national health intervention into a healthcare system. Exploratory
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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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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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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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team of researchers using operational and information-theoretic tools to gain insights into quantum foundations, causality, and space-time physics. We are convinced that further progress on open problems