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computational recourses for limited duration yet highly accurate particle-in-cell (PIC) modelling. Kingston University has developed a simulation model, dubbed PERSEUS, that narrows the gap between these two
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Overview: This exciting PhD opportunity is at the intersection of aerospace engineering and cutting-edge technology. It focuses on developing an innovative ground-based robotic inspection system
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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. Further information about the University can be found here The Role and Department The School of Education at Durham University is a leading centre for educational research and teacher development, with a
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drives tumour development, childhood cancers lack the extended time frame needed to accumulate the mutations required for tumorigenesis by those routes. Therefore, endogenous mutagenic processes are a
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aims to develop a novel theoretical framework for nonlinear and robust control of dynamical systems from a phase perspective. You will have the opportunity to freely explore multiple research directions
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. Project Background This project directly supports QCI3's vision of integrated and interconnected implementations by developing essential benchmarking tools that bridge across all three themes of the Hub
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering
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to talented prospective or mid-study students towards their PhD studies in Research and Development Management. Tenable period Up to three years (pro-rata for part-time students) Continuation of award
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field