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to interact professionally with participants, team members, and external stakeholders attention to detail and accuracy in data collection, entry, and management competence in basic computer applications (e.g
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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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computer systems and applications, including REDCap, NVIVO, and Excel demonstrated superior interpersonal communication skills, including with people with lived experience of neurodisability, to initiate and
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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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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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-in, and performance or creativity degradation in socio-technical decision processes design and implement quantitative methods (for example, learning-based, network-based, or agent-based approaches