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Field
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contributing effectively to a collaborative research team Knowledge, Skills and Experience Experience applying qualitative research methods for data collection (e.g., interviews or focus groups) and analysis
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sensors to deliver resilient, high-accuracy positioning. The project sits at the intersection of navigation, AI-enhanced signal and data analysis, and wireless communication systems, with applications in
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for household who stay indoors, and to prepare for emergency responses. Possible quantitative methodologies include concurrent time-series analysis of outdoor and indoor environment data, prediction model
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define observable events based on expert knowledge and available evidence. Development of a post-race analysis structure, process and data ‘toolkit’ that can build on historical understanding of race
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- or tissue-microenvironment. Our existing collaborations with AstraZeneca have yielded very interesting data specific metabolites that are involved in the migration and positioning of regulatory (Tregs) and
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on health and use economic methods to evaluate relative costs and benefits. This may include use of health impact assessment methods, statistical analysis of secondary data sources to estimate health impacts
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, analysis, and writing of their outputs, under the primary supervision of Dr. Sheina Lew-Levy. PhD students will be expected to undertake data collection in the UK, as well as at one of the international
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conducting the qualitative interviews with patients and analysing the interview data. You will be presenting that data to the study team at regular meetings and contributing to the intervention and app
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fuels (hydrogen, methanol, ammonia), simulation tools for marine engines and/or fires due to fuel leakages, data analysis methods and their applications for ships, sufficient understanding of appropriate
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, data analysis, and scientific writing and communication. Experience in working in an optics lab and programming in Python will be beneficial but is not necessary. Applicants should have, or expect