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emerging types of national emergencies and evaluate their spatial and operational implications. This will include an analysis of UK population distributions, terrain, infrastructure access, and airspace
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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longitudinal methods and cross-national data analysis to investigate the economic drivers and consequences of grey divorce. The project will explore how individual- and couple-level economic factors—such as
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ideal candidate will have an interest in ecological modelling, spatial analysis, and conservation planning, with experience in ecological fieldwork or quantitative data analysis being advantageous. Full
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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motivated and skilled candidate with a background in physics, biophysics, biological physics, or bioengineering. This PhD project will primarily focus on experimental research, which will include data
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Lead Supervisor name: Andrew Callaway, email: acallaway@bournemouth.ac.uk Project description: This PhD programme will determine the most clinically acceptable methods for emergency response teams
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). Experience in numerical modeling and data analysis. An interest in groundwater contamination, risk assessment, and sustainability. Programming experience (Python, MATLAB, or similar) is desirable but not
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analyses by age, ethnicity, and index of multiple deprivation will be performed. The second stage of the study will involve the analysis of prospectively collected EQ-5D-5L data from a cohort of patients to
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the analysis of the complex data and cellular models (Big Data and Kavli Institutes). The DPhil will provide the student with multidisciplinary skills including specialized training in bioinformatics, genetic