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Field
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Master’s degree (or other equivalent experience). Suitable backgrounds for these PhD positions include, but are not limited to, power engineering, industrial engineering and operations research, mathematics
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mortality using traditional and new forms of data, with a focus on developing and low-income countries. The successful applicant will spend 18 months at LSHTM and enrol in the PhD programme, with fees funded
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This self-funded PhD opportunity focuses on assured multi-domain positioning, navigation, and timing (PNT), integrating data from space-based, terrestrial and platform-based sources of navigation
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Supervisors: Dr Tim Halim and Dr Gregory Hamm Course start: 1st October 2026 Overview The project will be supervised by Dr Tim Halim, Dr Albert Koulman (Institute of Metabolic Science) and Dr
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the PhD student in high-performance computing, computer programming, applied mathematics, fluid mechanics, mathematical modelling and data analysis for large datasets -of the order of 100 Terabytes
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background in biostatistics or data science, and a clear interest in applying these skills to questions of causal inference in longitudinal observational designs. Please note the funding is only available
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, as well as for their babies. You will work with large, complex datasets from national surveys and routinely collected health data to support impactful research. You will manage your own research
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dedicated PhD student with a 1st class or 2:1 degree in the field of Engineering, Mathematics, Physics, Architecture or Computer Science. A MSc degree in a relevant area is desirable though not necessary
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microbiome and welfare of retired racehorses (randomised controlled trial). This project will provide the scholar with training and experience in animal welfare assessment, microbiome science and advanced
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goals. Organise and facilitate interactive workshops and stakeholder meetings as part of the research process, generating qualitative and quantitative data to test and refine platform content and