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are fundamentally limited by a "one model for one task" design philosophy. This approach incurs prohibitive engineering costs and yields brittle solutions with poor generalisation to new network conditions, trapping
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Computational background: engineering, physics, maths, or computer science. How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and a 300-word statement explaining your motivation
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, few people are trained in its operation. This PhD project will involve training on, and the further development of native mass spectrometry technology. The student will operate within the Advanced Mass
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combining physical models, sensor data, computational methods, and damage and fracture mechanics concepts to create a virtual replica of the composite tank, enabling predictive maintenance, lifetime
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-informed theoretical framework that quantify the viability of the approaches. The PhD candidate should have completed (or about to complete) their undergraduate degree in engineering or physics (preferably
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Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code:8839F select PhD Physics Experimental (Full Time) as the programme of
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Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8839F select ‘PhD Physics (FT) (Experimental)' as the programme of study You will then need to provide
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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. Yet, many stellar and planetary parameters remain systematically uncertain due to limitations in stellar modelling and data interpretation. This PhD project will develop Bayesian Hierarchical Models
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rounded scholar: £20,780 annual maintenance grant* Full coverage of PhD programme fees HE teacher training and practice. GTFs are compatible with external bursaries, as well as other funds for postgraduate