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be close to the completion of a PhD/DPhil in epidemiology, biostatistics or big data, along with demonstrable experience of working with population registers and large datasets. With proven
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language processing, historical linguistics, and computational humanities. The postholder will lead the computational stream of the project, which involves building a large corpus of Latin texts (data collection and
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interests in the following areas: ERC post: Cosmological tests of dark energy and modified gravity (contact: Baojiu Li) UKRI post: The use of cosmological simulations in the analysis of large-scale structure
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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qualification/experience equivalent to PhD level in health data science or similar field. Experience working within multidisciplinary teams and in the preparation and analysis of large healthcare datasets such as
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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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At the University of Vienna more than 10,000 personalities work together towards answering the big questions of the future. Around 7,500 of them do research and teaching, around 2,900 work in
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proven expertise in seismic data processing and analysis, knowledge of volcanic/ geothermal processes, strong quantitative skills, and proficiency in Python for scientific computing. You should be
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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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of routinely collected maternity data and can be linked with other health datasets in south London such as the records of the local mental health Trust using the Clinical Record Interactive Search