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. This PhD project will take advantage of recent developments in machine learning methods, to enable computer modelling of the mechanical behaviour of titanium alloys to produce a machine learning-based
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Learning to work closely with experimental techniques such as transmission electron microscopy, and to learn to simulate nucleation and electrochemistry processes. In this project, we will use machine
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. This PhD proposal would ideally suit a student who was interested in machine learning techniques as well as developing novel tools and software for studying materials properties. The student will benefit
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. The need to predict the transition state structure as input for quantum chemical barrier predictions adds further complications. Machine learning (ML) models of quantum chemistry can achieve fast and
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numerically either using classical optimisation approaches which select a single solution (that may be an artefact of the choice of optimizer) or using tools from statistics and machine learning such as
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of their properties, facilitating direct comparison with experiments. The PhD candidate in our group will utilise state-of-the-art computational modelling methods such as Density Functional Theory (DFT) and machine
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-interaction (HCI), and more. Among various sensing technologies, Radio Frequency (RF) signals such as WiFi can be applied in a less intrusive manner, offering significant potential in smart home environments
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tools from statistics and machine learning such as Bayesian inference which mitigate the ill-conditioning of the problem by incorporating prior information. Many machine-learning models for interatomic
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consequences of mobile ions diffusing around interfaces, for example those at grain boundaries and contact layers. This project will make use of ab initio and machine learning techniques to provide in-depth
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), connect this to engineering-scale mechanical properties and have the opportunity to apply machine learning image processing techniques to guide theory with experimental analyses. Your research will lead to