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Sequential Monte Carlo Methods for Bayesian Inference in Complex Systems Department of Automatic Control and Systems Engineering PhD Research Project Self Funded Prof Lyudmila Mihaylova Application
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, including sequential Monte Carlo methods, Gaussian processes and Bayesian compressed sensing. Applicants from different backgrounds are encouraged to apply depending on the specific nature of the project
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the brain regulates its blood supply in health but also in diseases such as Alzheimer’s. The main focus of this project will be using theoretical methods such as Monte Carlos simulations to generate
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structure and its effect on their properties. This project will use theoretical modelling (density-functional theory and Monte Carlo calculations) to investigate the structures of functionalised graphene