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, breaking etc. This makes traditional methods particularly difficult to generalise based on all these driving factors, whereas this PhD project takes a novel and explainable data-driven approach – equation
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for health policy decision-making, these methods will be developed using a Bayesian framework. This PhD project will deliver a substantial contribution to original research in the area of health data science
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Research theme: Applied Mathematics, Continuum Mechanics, Liquid Crystals Application deadline: All year round The successful candidate will join the PhD programme of the Department of Mathematics
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in high-load fusion environments needs rigorous analysis. Brazing is another potential technique, particularly for complex geometries, though existing data highlight challenges such as V44 substrate
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aims: Develop end-to-end protocols for screening selected foods and nutraceuticals. Create advanced strategies for data integration using tailored algorithms and machine learning approaches. Demonstrate
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use, and public economics, the research will contribute both to academic literature and practical policymaking. The PhD candidate will develop advanced skills in economic/econometric analysis and
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, finance, and healthcare, where data integrity and system reliability are non-negotiable. This PhD project addresses the integration of robust security measures within AI-enabled electronic systems
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computing and analysis of data will enable the development of control mechanisms that will overcome one of the major barriers for exploiting the benefits of hybrid propellant propulsion systems. The project
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understanding of device function. The project will involve advancement and application of spectroscopic techniques and simulation tools for the measurement and analysis of the properties of spins and their role
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in correctly identifying high acuity cases within an increasing volume of lower acuity calls. This project will use mixed methods to assess the impact of this change. Data modelling and analysis will