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, driving exciting research that enhances our existing strengths, and we will support you in the development of an independent and aspirational research programme. You will already appreciate that training
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-Sierra et al. ACS Appl. Mater. Interface 2021, 13, 35506), the Soft Matter Engineering group is leading an European research consortium in developing sustainable antimicrobial surface coating (https
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quantitative data analysis of large secondary datasets and be based at the University of Bristol. There are opportunities to work on several other ongoing and upcoming research projects to help develop your
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these interactions we are working to develop better diagnostic tests and future vaccines and novel therapeutics. Staphylococcus aureus is a major opportunistic pathogen and the leading bacterial cause of death in most
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/chemistry/slater-peter.aspx https://www.birmingham.ac.uk/staff/profiles/chemistry/allan-phoebe.aspx and will work on the development of recycling strategies for Li ion battery materials, in particular using
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://www.birmingham.ac.uk/staff/profiles/chemistry/slater-peter.aspx https://www.birmingham.ac.uk/staff/profiles/chemistry/allan-phoebe.aspx and will work on the development of recycling strategies for Li ion battery
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to: rhizosphere and phyllosphere microbiology microbial evolution molecular and/or structural aspects of plant-microbe or plant-fungal interactions the molecular biology of soil-dwelling bacteria or fungi
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at 0.5fte for the final six months of the post. Across these two projects, the Research Fellow will collect objective and subjective sleep data from children with neurogenetic syndromes and develop and
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Limited. The Knowledge Transfer Partnership project will focus on developing technically and commercially viable gas diffusion layers for high-volume applications using recycled carbon fibre, creating a
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. The project will define new near miss and severe morbidity definitions allowing us to identify electronically when significant events happen. We will then develop a large multi-centre maternity routine dataset