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Field
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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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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. Experimental studies will be performed in wind tunnels with advanced measurement techniques with high spatial and temporal resolutions. Realistic car models (DrivAer models) will be considered in this study and
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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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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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, partial differential equations and scientific computing, to name a few. There are competing LC theories e.g., molecular-level models with molecular-level information, mean-field models that average
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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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will contribute to the field by: Developing a conversational AI interviewer capable of conducting real-time adaptive interviews. Building an automated candidate ranking model based on interview
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process conditions. Furthermore, this research will focus on the development of a model, allowing for virtual testing and optimisation of the chemical recycling process. This includes potential
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for household who stay indoors, and to prepare for emergency responses. Possible quantitative methodologies include concurrent time-series analysis of outdoor and indoor environment data, prediction model