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only for up to 4 years full-time or up to a maximum of 6 years if studying on a part-time (0.5 FTE) basis How to apply: Send a copy of your CV and a 300-word statement about why you are interested in
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experiments; supporting other group members with data analysis and interpretation from both simulations and experimental data; and use the developed framework to design new materials with optimised performance
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(or equivalent) in Physics, Mathematics, Mechanical or Aerospace Engineering, Computer Science or a related discipline. You should be highly motivated, and would be able to work independently as
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explore or optimise the flexible structures and manufacturing process of Litz wires. This studentship offers the opportunity for the PhD student to lead the development of innovative simulation tools
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alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic
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create a computational tool based on experimental input, simulated data, and machine learning methodology to extract 3D atomic structure information from 2D identical location STEM images. STEM image data
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in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
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simulations to model this process and, in conjunction with ongoing experimental studies, obtain design rules for the optimum crown ether, lithium counter-ion, and solvent, which will lead to enhancements in
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to the development of multiscale computational models for simulating crack propagation and establishing reliable methods to predict the residual strength of composite structures. The simulations, performed in Ansys
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capture technologies. In this project, you will: Develop a 3D Digital Model: Create an advanced computational model of high-pressure mechanical seals. Apply Computational Fluid Dynamics (CFD): Simulate gas