19 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"M.V" PhD positions at University of Birmingham in United Kingdom
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interpretation of the data generated and that’s where this project comes in. You’ll be applying metagenomic bioinformatics techniques to respiratory samples and developing analysis and interpretation approaches
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surveillance of pathogens through samples such as respiratory infection samples. One such UKHSA project is MScape, which is using deposition of metagenomic diagnostic sequencing data to perform surveillance
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breaking towards achieving silent aircraft design? Applications are invited for one funded 3.5-year PhD studentship for the project titled ”Data-driven modelling and control of turbulence-generated noise” in
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the Birmingham MC40 cyclotron facility. This experimental campaign and the new data/insights will allow you to validate structural integrity models of ASSs linking meso- and macro-scales. During this PhD project
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the rich, unstructured information found in clinical notes and cannot effectively gather data on lifestyle and social determinants of health. This PhD project will pioneer a novel, hybrid AI framework
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of Dr Zhong-Nan Wang at UoB. The research of the group is focused on developing high-fidelity CFD and data-driven approaches for aerodynamics and aeroacoustics. The PhD project is expected to start in
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the context of stress, leading to better cognitive performance and improved mood in middle-aged healthy adults. These data will establish whether dietary polyphenols are effective to minimize the impact of
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. The project will thus reveal whether bacterial factors are driving the recent increase in CDI rates. This information can be used to develop novel prevention and treatment strategies. The project will be
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are found in the context of airway-derived metagenomic data. The project will be supervised by Dr David Cleary (UoB), Prof. Alan McNally (UoB) and Dr Meera Chand (UKHSA). Applications of a two page CV and
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collected regularly from sewage-impacted rivers and from properties affected by flood events. Data will be analyses using advanced bioinformatics to characterise community structure, resistance genes and