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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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-impact questions in environmental economics and labour economics. Key responsibilities for this role includes: Data collection, cleaning, and merging from very large-scale microdata sources (e.g., terabyte
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, interdisciplinary research. Our department remains at the forefront of engineering innovation, delivering sustainable solutions with global impact. As a large, multi-specialisation department, we thrive
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protocols for electrical biasing of samples in the microscope. A key task is to process and analyse large 4D-STEM data sets and extract information about domain wall structure and dynamics. The role involves
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quantitative data analyses. The role involves co-ordinating a large study and liaising with clinical participants, so the ideal candidate would have exceptional interpersonal and organisational skills. Further
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theory, and the analysis of large data ensembles. You will write papers for submission to academic journals, collaborate with academics and PhD students, and communicate your research at national
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optimization techniques, coding new algorithms, creating new mathematical theory, and the analysis of large data ensembles. You will write papers for submission to academic journals, collaborate with academics
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Responsibilities for the role include: Data collection, cleaning, and merging from large-scale microdata sources (e.g., patents, dissertations, bibliometrics). Conduct data analysis using econometric and statistical