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. Yet, many stellar and planetary parameters remain systematically uncertain due to limitations in stellar modelling and data interpretation. This PhD project will develop Bayesian Hierarchical Models
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, allowing smaller objects to be detected further away, as well as target feature extraction, which is the stepping stone to reliable target classification at further distances. This will be the first attempt
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pathways, whilst their omission can introduce significant systematic biases in parameter estimation, detection pipelines, and tests of fundamental physics. In this PhD project, you will develop a
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of genome-wide association methodologies, discover novel resistance genes or mutations, primarily those that contribute to resistance against antibiotics that are currently used for the treatment of CDI
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described. In this project, we will investigate the roles of NLR genes in the fungal immune system. Our overall objective is to understand how NLR genes contribute to self/non-self recognition and to
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frameworks that can maximise the performance, efficiency, and emissions reduction potential of such new fuels through intelligent design, modelling, and experimental validation. Research Objectives Investigate
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systems, providing early detection of adverse events such as infection and inflammation. The project will involve sensor design and modelling, prototype development, electrochemical characterisation, and
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. To achieve the project aim will require the following objectives to be fulfilled: Problem definition, including the derivation of synchronisation requirements for a maritime radar network of moving platforms
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exposure, and thermal fluctuations. Key Objectives: - Develop and characterize low-carbon materials with multi-functional properties - Assess mechanical performance and long-term durability under simulated
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cysteine handling intersect with ferroptosis in ageing muscle. Objectives Characterise mitochondrial Fe–S biogenesis and cysteine metabolism in aged myoblasts Determine ferroptosis sensitivity in aged