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Field
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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multiscale metamaterials with sub-200 nm resolution. The research spans fundamental optical physics through to applications, and the student will develop skills in electromagnetic simulation, nanofabrication
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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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.), including full fees and bursary. Main Copy (advised structure) Green hydrogen has been presented as an important aspect of the renewable energy future not only to decarbonise many industries including steel
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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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fluid dynamics (CFD) simulations, Finite Element Analysis, manage and execute the procurement of the build, run the aerothermal testing and process and communicate the results. The skills, qualifications
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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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nonlinear effects. These nonlinear effects will be generalised via correction terms discovered by machine learning from a large numerical simulated dataset. This dataset also allows for extending the theory
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scenarios. By enabling more realistic and dynamic adversarial simulations this project will support the creation of more effective cybersecurity testing, consequently strengthening organisational resilience
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to the project. Degree transcripts/certificates and, if English is not your first language, a copy of your English language qualification if completed must be uploaded. Contact Details Prof. G.Tasca, giorgio.tasca