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health, funded by UKRI. This post will be situated at KCL, working with and across this large disseminated UK-wide partnership spanning 10+ universities and other organisations across the country
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; London School of Economics and Political Science | London, England | United Kingdom | about 5 hours ago
-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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) for different scientific applications, including simulations, large-scale data analyses and AI. This will involve designing test protocols, building test benches to track power and energy usage, and running
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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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the effectiveness of anticipatory cash transfers in response to climate disasters, using large-scale RCTs in Bangladesh and other countries. It investigates how early interventions can mitigate the impacts of extreme
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data analysis, with opportunities to apply your skills to integrating this with other data types (e.g. genomic and transcriptomic). The position is full-time and available for a duration of 4 years
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such approaches would be cost effective. To achieve this, you will be supported to undertake analyses using large data registries such as the Clinical Practice Research Datalink. This is an exceptional opportunity
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generations of research and development professionals, data specialists, technology experts, inventors, and scientists for industry and society. The Macroscopic Quantum Optics (MQO) Group at the Department
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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