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collaboration that has mapped emotional hotspots in four cities in the UK and EU using spatial analysis of social media data. The next phase of the project aims to incorporate explainable AI (XAI) to interpret
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community. Required Skills and Qualifications: Minimum PhD in computer science/ engineering or related fields. Proficiency in Python is a must. Experience with other programming languages such as Java, C/C
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techniques to enable large-scale data search across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both keyword-based search and SPARQL querying. EPRESSO will build on and
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, large-grant project on the epidemiology of bovine tuberculosis in wild badgers, using state-of-the-art Bayesian modelling approaches to study the drivers of infectiousness and transmission of infection in
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meetings.Qualifications: · PhD in the social sciences in hand by July 1, 2025. Preference given to PhDs in Sociology or Religious Studies with dissertations based on primary field data. · Demonstrated research
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on HK-dir's GSU list We offer a PhD education in a large, exciting and societally important organisation an ambitious work community which is developing rapidly. We strive to include employees at all
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. The NOMIS-ISTA Fellowship Program provides postdocs with the freedom to work on big unanswered questions and high risk research at the intersection of two or more scientific disciplines. ISTA offers
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UKESM1 or similar models, advanced data analysis and machine learning, would be advantageous. Grade E: You will be near completion of a relevant PhD or have equivalent research experience, and be able
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to contribute to a world-leading project on Survey Data Collection Methodology Survey Futures https://surveyfutures.net/ . Survey Futures is a collaboration between nine universities and three survey
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the direction of Dr Maslovskaya, you will be part of a large multi-institution team of survey data collection methods experts in the UK. You will analyse probability-based NatCen online panel data collected using