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experiments; supporting other group members with data analysis and interpretation from both simulations and experimental data; and use the developed framework to design new materials with optimised performance
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Start Date: October 1 2025 Introduction: This PhD project in Aero-Thermo-Structural Simulation and Optimization of Mechanical Interfaces in Hypersonic Vehicles will be carried out under the UK
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million in losses each year, with landslides during earthquakes leading to over NZ$1 billion in damage for a single event. While landslide susceptibility modelling is an essential tool in risk management
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Generative machine learning models have made significant progress in recent years. Typical examples include, for example, high-quality image or video generation using diffusion models (e.g
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within the energetics field. Whilst many reactive burn models have been developed to simulate this behaviour, they are generally designed for ideal explosives and are mostly engineering models fitted
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. The within-host model will be linked to: a clinical trial simulation, an essential tool in drug development, to inform the clinical trial design of novel treatments, an individual-based transmission model
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candidate will drive the development of the FSI CMF model to simulate the effect of fluid-solid coupling on the vibration of the structure. The successful candidate will work with the multidisciplinary
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address Dr. Chunwei Xia: c.xia@leeds.ac.uk Co-supervisor’s full name & email address Professor Zheng Wang: z.wang5@leeds.ac.uk Project summary Large Language Models (LLMs) have profoundly transformed
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Trust. The successful candidate will work closely with the PI and a PhD student within a larger cross-disciplinary team to construct a quantitative computational model of carbonate biomineralisation
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modelling and simulation techniques and software packages would be an advantage. Programming skills in languages such as Python, C++, MATLAB, are desirable, as is an awareness of machine learning or other AI