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Field
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to modulate pathological cell behaviour in vitro, with potential for progression to in vivo testing in a rodent model of glaucoma. Candidate Profile Applicants should hold (or expect to obtain) a 1st or 2:1
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dynamics and tissue morphogenesis during embryo development using cellular, molecular and mechanical approaches. Cell movements underlie tissue patterns and shapes. Using chick embryos as the model system
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assessment. Stress testing & model robustness. Generative imaging models. Please see job description for a full list of requirements. *Candidates who have not yet been officially awarded their PhD will be
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models used in component scale CFD assessments. In particular, this concerns quantifying the effects of the heat transfer surface’s detailed topography, porosity and wettability on near-wall bubble
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search strategies 3) How to leverage the spatio-temporal diversity of multistatic radar observations At the end of the PhD an over-arching modelling environment will be built, where the parameters above
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emissions and are being implemented to provide a carbon efficiency assessment of farm enterprises. The contribution and management of ensiling at the farm scale to these models has not been fully explored
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treatment processes through advanced machine learning, validated against physics-based models and experimental data. 2. System Integration: Integrating the DTs into material and energy balance equations
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast
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including predictive modelling, computer vision and epidemiology. The student will join an established team of investigators, including statisticians, epidemiologists, image scientists, and clinicians
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fine-scale, fully distributed hydrological modelling, with the ultimate goal of optimising NFM strategies in moorland, to improve flood resilience for rural, upland communities. The studentship will be