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agricultural science with a quantitative focus (or an equivalent discipline) expertise in statistical and machine learning approaches, with the ability to apply advanced methods to complex environmental and
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focus on processing and utilising machine-learning techniques to analyse large volumes of data from sensors installed in Phase 1. The aim will be to merge the QC points and tracking system developed in
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experience experience in molecular biology or genetic engineering techniques ability to learn how to conduct protein purification and characterisation ability to operate and maintain biological equipment (e.g
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, economic growth, inequality, and culture. The project draws on large-scale data collection and archival records, and applies a diverse set of methodologies such as text analysis and machine learning
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into brain function. Apply state-of-the-art software tools and methodologies for neuroimaging data pre-processing and analysis; with a motivation to learn new techniques and keep up-to-date with best practices