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collaboration with Dr Whelan and the PhD students, machine learning tools for the handling of the Mauve and MUSE datasets. They will also be expected to lead the research into innovative ways in which the machine
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. The successful candidate will have the responsibility of developing, in collaboration with Dr Whelan and the PhD students, machine learning tools for the handling of the Mauve and MUSE datasets. They will also be
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expertise in energy systems, data analysis, and performance evaluation. They will contribute to the integration of hardware and software components from a research perspective, ensuring high-quality data
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assist with the technical research agenda, contributing expertise in energy systems, data analysis, and performance evaluation. They will contribute to the integration of hardware and software components
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the project under the supervision of the PI, with input from a wider project management group and a PPI steering committee. The successful candidate will have a PhD in Psychology, Social Science, Health or a
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will have a PhD in Psychology, Social Science, Health or a related discipline, with experience in a range of different methodological approaches, including quantitative and qualitative research methods