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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
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modelling. This exciting project involves the application of innovative methods such as high-throughput experimentation to expediate the syntheses (and bioanalysis) of life-saving pharmaceuticals
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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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transformer in operation. On the other hand, the Total Cost of Ownership (TCO) model is widely used to measure the whole lifetime cost of the transformer. In addition to the capital cost, cost of losses
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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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models. This theoretical project will facilitate close collaboration with experimental groups and enable benchmarking of theoretical predictions. The PhD researcher will be part of the Correlated Quantum
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ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling to pioneer innovative sealing solutions. What We Offer Full 4-year Funding for UK applicants
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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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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