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PhD: Digital Optimisation of Rail Grinding EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering for Manufacturing PhD Research Project Directly Funded UK Students Dr
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Engineered for Excellence: Developing Advanced Traction and Braking Particles to Enhance Rail Sustainability and Safety (C4-MAC-Tomlinson) School of Mechanical, Aerospace and Civil Engineering PhD
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accessible measure of location. One option is to use skew versions of know distributions that leave the mode or median of the distribution at the origin. The main objective of this project is to explore, from
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Bayesian risk quantification for accelerated clinical development plans (C4-MPS-Oakley)
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both Bayesian and frequentist methods), and creating automated statistical reports and other relevant output from within statistical software. Application & interview 5 Track record of publications in
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experience/expertise in transfer learning for SHM data; preferably, kernel-based, neural network and Bayesian. Essential Interview Experience and track record in code writing for engineering problems in e.g
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. Training will cover modelling, quantitative analysis, and laboratory methods. OBJECTIVES O1. Build a spatiotemporal lineage atlas of the pre-implantation human embryo. The student will assemble high-content
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quality, avoiding the paralysis that troubles artificial algorithms when options seem equally good. This project asks: what objective functions do such biological systems optimise, and how can we use
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FAST-TRACK – Fast Alloy Screening for Next Generation Aerospace Superalloy Development
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physics-informed digital twin for offshore wind foundations, combining ultrasonic guided wave monitoring, high-fidelity finite element simulations, Bayesian inference, and machine learning. Guided waves can