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local energy markets and provide demand-side flexibility within a data-driven net zero carbon energy system. The appointee will support the development of data architectures, analytics tools, and
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music analysis (with a PhD in musicology, music analysis or music theory) and/or in computational musicology, digital humanities, computer science, artificial intelligence, or mathematics/statistics, with
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of how planets form in the disks of Intermediate Mass Herbig Ae/Be stars. The successful candidate will have the responsibility of developing, in collaboration with Dr Whelan and the PhD students, machine
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contribute to the integration of hardware and software components from a research perspective, ensuring high-quality data collection, rigorous analysis, and evidence-based assessment of energy savings, user