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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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join a vibrant, supportive research community (around 20-25 people involved in fluids modelling research). Collaborate with the Leonardo Centre for Tribology: Work with top researchers on experimental
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, organisational and policy context of the National Health Service. The PhD research will focus on how bottom-up networks are involved in promoting change. In recent years, numerous networks of clinicians
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/emissions modelling preferred but not required Creative problem-solving skills and ability to work independently *Candidates with a PhD in other disciplines may be eligible if they can demonstrate exceptional
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
intelligent methods that integrate large language models (LLMs) and knowledge graphs to interpret technical documentation and structure complex engineering knowledge. The goal is to create digital twins
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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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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
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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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formulation. These models will enable rapid scenario testing, predictive analysis, and early decision-making, thereby reducing experimental workload and accelerating development timelines. Life cycle assessment