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Field
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
complex engineering data and deliver insights that are robust, adaptable, and applicable across complex, high-value, safety-critical domains. This research will contribute to shaping the next generation of
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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evaluation, policy advocacy, or better understanding the contexts and causes of such abuse. The student will use advanced data science and applied statistics to enable combined analysis of different modes
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insulation systems becomes critical to maintaining performance, reducing downtime, and extending asset life. Generator stator windings typically comprise multiple sub-level insulation systems, including Main
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. Understanding the process of droplet impact and freezing dynamics at high airspeeds, on textured and non-textured surfaces is critical to deciphering the physics behind ice adhesion and accretion. Previous work
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specific motifs within the glycan chains defining binding sites for critical signalling and structural molecules. Unravelling the ways in which these motifs are encoded into GAGs by their biosynthetic
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global change, damaging critical infrastructure resilience. This project is part of the prestigious Loughborough University Vice Chancellor’s PhD Cluster – RAINDROP (Resilient eArthwork INfrastructure
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transcriptomics and histone mark profiling as well as by live imaging approaches. As part of this project, you will have the opportunity to gain computational data analysis skills. This studentship comes with
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T3 (Applications) through reliable quantum advantage assessment. Project Description The project addresses the critical need for reliable, scalable verification and benchmarking schemes in quantum
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metabolomic and lipidomic analysis. References/further reading Stockis J, Yip T, Raghunathan S, Garcia C, Lee S, Simpson C, Pinaud S, Schuijs MJ, Araos Henríquez J, Png S, Raddi G, Bricard O, So TY, Mack S