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to air pollution in the future, and planning further policy changes. This PhD project will develop statistical modelling frameworks that are able to handle large-scale, complex, and correlated time series
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nature-based solution opposed to traditional ‘grey’ engineering, offer catchment-level solutions by using natural processes to slow and store water through a series of diffused interventions. Historically
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drives tumour development, childhood cancers lack the extended time frame needed to accumulate the mutations required for tumorigenesis by those routes. Therefore, endogenous mutagenic processes are a
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to air pollution in the future, and planning further policy changes. This PhD project will develop statistical modelling frameworks that are able to handle large-scale, complex, and correlated time series
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or as soon as possible thereafter. For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £20,780 for 3.5 years full-time, or pro rata for part-time
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, Skills and Experience • You will have substantial technical experience in time series analysis, ideally either in neurophysiology data or wearable sensor data • You will have experience of at least
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operations such as machining. This is driven by the need to complete repair tasks without disassembly of industrial installations. We developed a series of continuum robots in both short and long versions