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with long-standing vaccine programmes, disease remains a challenge. In this project the student will use genomic and novel computational approaches to examine the S. pneumoniae causing severe infections
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and spatial resolution, to make a leap in this field. The PhD research programme will squarely address these challenges. The PhD candidate should have completed (or about to complete
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for candidates with a background in meteorology, climatology, physics, engineering and any related discipline, and a strong interest in applying advanced physical and computational methods to real-world
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• Quantitative and computational skills but training will be provided • Interest in Bayesian statistics, stellar evolution, and exoplanet science Keywords Bayesian inference · hierarchical modelling · stellar
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of realising an optical-pump TeraHertz-probe polarisation-resolved near-field microscope, this PhD research programme will look at combining spintronic THz emitters and near-field photoconductive probes
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unsuitable, while the utility and performance of others remains an open question. The aim of the PhD is to derive synchronisation techniques suitable for deployment into a maritime radar sensor network
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, few people are trained in its operation. This PhD project will involve training on, and the further development of native mass spectrometry technology. The student will operate within the Advanced Mass
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-informed theoretical framework that quantify the viability of the approaches. The PhD candidate should have completed (or about to complete) their undergraduate degree in engineering or physics (preferably
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the wider PhD cohort in the group of meteorology and climate and the School of Geography, Earth, and Environmental Sciences. Supervisory team: Dr Gregor C. Leckebusch (University of Birmingham
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Project Description: This EPSRC-funded PhD project will investigate how next-generation electric and autonomous vehicles can operate as symbiotic agents within the urban ecosystem—intelligently