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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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prostate cancer risk across diverse ethnic groups. This work aims to support more equitable risk stratification in cancer screening programmes. Using simulations based on multistate modelling framework
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project, which encompasses 4-6 PhD studentships across 5 research groups, you will be an integral part of a dynamic doctoral cohort. This unique opportunity provides the successful candidate with the chance
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moments. All these factors are highly dynamic in the way they interact to impact racing tactics and trends. The specific objectives include: Historical analysis of racing from the past 3-5 years across
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is characterised by complex and highly dynamic turbulent flows that define the performance and design of renewable energy systems and their infrastructure. This PhD project aims to enhance
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dynamically managing power flow, improving system flexibility, and mitigating transmission constraints. However, conventional methods for PST deployment often consider sizing, placement, and control in
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from the UK Health Security Agency and real-world outbreaks. This interdisciplinary project integrates microbiology, molecular biology, bioinformatics, and public health, offering hands-on training and
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to linked data. The overarching goal will be the integration of routinely collected data (e.g. molecular genomic data with clinical data from electronic health records) to address specific research questions
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and modelling techniques. Real-World Impact: Contribute to transformative technologies in clean energy and carbon capture. Future job opportunities: Digital modelling and computational fluid dynamics
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your PhD journey in the heart of London at the newly established City St George's, University of London, a dynamic institution formed from the merger of City, University of London and St George's