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of developing a computational model to simulate hydro-sedimentary dynamics and morphology between restored patches to explore conditions favourable for restoration. Validated with data on vegetation cover and
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the environmental noise sources, aerofoil noise is one of the major contributors, including noise from aircraft wing, aeroengine fan and wind turbines. Therefore, it is crucial to effectively reduce them for a quiet
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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and use the results to iteratively refine devices and models. You should have the ambition to publish you work in top ranked international journals and at leading conferences and have a dedication to
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correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
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of users within mixed reality environments. Current research in XR security has predominantly concentrated on authentication procedures conducted at the beginning of a session, often in a static manner. This
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The Project: Are you passionate about materials science, numerical modelling and materials characterisation techniques? Do you want to work on cutting-edge research that will directly impact nuclear
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verification methodology and corresponding toolchain to detect and mitigate such threats to CPS at the design time making the CPS resilient-by-design. Typically, CPS are modelled as hybrid systems, comprising
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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for downstream tasks. In this project, you will develop novel unsupervised machine learning methods to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a