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, measure transport and machine learning on developing a novel mathematical framework for identifying reduced dynamical models of high-dimensional complex multi-scale systems. The project will develop fast
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density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data, including with the use of machine learning use this knowledge to design
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collection and management for research, as well as basic knowledge of both quantitative and qualitative data analysis principles. Demonstrate high levels of computer literacy, including proficiency in learning
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an equivalent discipline) expertise in statistical and machine learning approaches, with the ability to apply advanced methods to complex environmental and agricultural datasets proficiency in R and/or
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: Using big data insights to optimise the manufacturing process The second phase of this project will focus on processing and utilising machine-learning techniques to analyse large volumes of data from
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draws on large-scale data collection and archival records, and applies a diverse set of methodologies such as text analysis and machine learning to assess the impact of colonisation. About you PhD in