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statistical programming languages such as R and Python, and experience with Bayesian modelling and time series analysis. A track record of research outputs, including publications or presentations at national
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nodes and chemical bonds as edges. Analysis these networks are important as they may provide AI-based approaches for drug discovery. This project will focus on representing and inferring chemical or
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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
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motif, hence renders the identification of the binding protein difficult. Here we propose for the first time to apply the Bayesian information-theoretic Minimum Message Length (MML) principle to optimise
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This project focuses on brain network mechanisms underlying anaesthetic-induced loss of consciousness through the application of simultaneous EEG/MEG and neural inference and network analysis
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of statistical signal processing, inference, machine learning and dynamical systems theory to develop new semi-analtyical filtering approaches for state and parameter estimation to infer neurophysiological
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horticultural data from digital images by analysing their content. The aim is to infer information that might not be immediately apparent, even to the photographer, in order to improve our understanding of animal
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polycrystalline material during plastic deformation in order to eventually predict the manner in which materials deform and fail. As a first step, we wish to infer a distribution of the directions of deformation
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data, make sound inferences, interpret and apply complex resolutions and policy, and communicate results in written reports effective and tactful communication skills (both verbal and written), strong
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for mathematics across the CWTS Leiden, ARWU, USNews, and QS rankings. In Statistics, the School has research strengths in Bayesian and Monte Carlo Methods, Biostatistics and Ecology, Combinatorics, Data Science