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of the Faculty of Computer Science of the University of Vienna. This group is distinguished by excellent research in Visualization and Data Science, as well as applied research in Human-Computer Interaction and
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We are seeking a well organised and self-motivated researcher to work on the Faraday Institution funded SOLBAT and/or LiSTAR projects, reporting to Prof. Mauro Pasta. Applicants must hold PhD/DPhil
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for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets
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Sciences (HSPS) and also has a vibrant MPhil and PhD programme. There are currently about 80 students working on PhDs on a diverse range of topics in sociology. Further information about research interests
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We are seeking a well organised and self-motivated researcher to work on the Faraday Institution funded SOLBAT and/or LiSTAR projects, reporting to Prof. Mauro Pasta. Applicants must hold PhD/DPhil
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of Reading, focussed on the development of novel synbiotics for improved gut health. They will join a research group of 5 academics and around 20 PhD students. The main duties and responsibilities will be
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scholars in Law and two PhD students (one in Law and one in Computer Science/Data Analytics), as well as with international, European and national stakeholders involved in the CURE project. The post-holder
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research culture. You will have 1) a completed PhD in a Humanities subject, preferably History, Cultural/Literary Studies, or Social Sciences, 2) Expertise relevant to the topic of refuge/asylum in the UK in
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robots are therefore required. One of the goals of this project is to commercialise. You must have a strong computer science background and have experience in one or more of the following areas: Computer
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fluorescence microscopy, CRISPR/Cas9 and cryo electron microscopy. You will join our enthusiastic lab in the Department of Biochemistry. We aim to upskill all our members and work together to answer important