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researchers to join the laboratories of Prof Michael Browning and Prof Jacinta O’Shea, to work on a large-scale project, sponsored by a Wellcome Mental Health Award. About the Role The posts are funded for 2
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comfort and would be interested in a fixed term role to support a large project looking at developing outdoor thermal comfort models for children? If so, we would welcome your application to this full-time
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means, data acquisition (primarily through individual semi-structured interviews), data analysis, and working with the research team and PPI co-researchers to interpret the data and disseminate findings
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information of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award
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, collaborative research that combines lab-based experiments with large-scale data handling and analysis. The post is available for up to 25 months in the first instance with a preferred start date of July/ August
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, which involves building a large corpus of Latin texts (data collection and pre-processing), mining dictionary data, and developing novel algorithms for time-sensitive word sense disambiguation (WSD) in
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, and computational humanities. The postholder will lead the curated stream of the project, which involves designing a large corpus of Latin texts, curating it (correction of pre-processed data and corpus
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of cosmology will be considered, candidates interested in collaborating with Professor Blake Sherwin on CMB or large-scale structure cosmology (ideally on areas related in some way to CMB lensing or kSZ science
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. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus. You will join an interdisciplinary team of researchers spanning imaging science, machine learning
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of therapeutic genomics, leveraging large-scale functional genomic datasets and cutting-edge computational resources, including university HPC clusters and AWS. The post-holder will advise colleagues on data