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, producing often complex financial models as required and providing insightful guidance on financial structures, processes and regulations. They will work closely with colleagues in MPLS Division on long and
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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Charitable Trust program of research on DVA and MS. What we offer in return 26 days holiday plus approx.16 Bank Holidays/days that the University is closed by custom (including Christmas) – That’s 42 days a
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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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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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for household who stay indoors, and to prepare for emergency responses. Possible quantitative methodologies include concurrent time-series analysis of outdoor and indoor environment data, prediction model
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to work with international partners such as the WHO. The models developed will used to answer a series of substantial questions related to variation in exposure to air pollution over space and time
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spread over five months (October 2025-February 2026). The duties will include: Observing a series of training sessions, in-person at University of Nottingham. Assisting with the design of a schedule of
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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
state-of-the-art wearable devices. Applicants should have strong experience in data collection in applied settings, advanced statistical analysis skills (particularly in time-series data), and proficiency
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visualisation results will be tested by examining how well it can assist a series of decision making tasks through collaborating with experts from the problem domain. Applicants should have, or expect to achieve