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of quantitative analysis and statistical modelling to support the project’s aims of assessing the contribution of An. stephensi to malaria transmission relative to native malaria vectors across a range of
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research. You will be responsible for designing and implementing proteomic data analysis, with opportunities to apply your skills to integrating this with other data types (e.g. genomic and transcriptomic
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and share knowledge of endangered archaeological sites across eleven African countries using a combination of remote sensing, historical map analysis, records-based research supported by ground
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(mammalian cell culture, lentiviral transduction, flow cytometry and FACS, Illumina sequencing and bioinformatic data analysis. You should have (or be close to completion of) a PhD in molecular/cell biology
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The interplay of TCS with Harmonic analysis and additive combinatorics There will be opportunities for collaboration with faculty members and PhD students and to engage with the broader quantum computing and
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interest and research in the field of economic and experience in data management and analysis. Demonstrable experience of working with quantitative data and relevant software (Stata, R, Python, or similar
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involving complex methodologies and statistical analysis. Your responsibilities will include data management, cleaning, and analysis using advanced statistical techniques, as well as drafting reports and
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interest and research in the field of economic and experience in data management and analysis. Demonstrable experience of working with quantitative data and relevant software (Stata, R, Python, or similar
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-equilibrium conditions. The project is a UKRI/NSF collaboration with Virginia Tech, and the use of direct numerical simulation, modelling and analysis will be complemented with experimental data from
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generation and analysis, and contributing to the development of novel methodologies. In addition, they will support the wider activities of the research group by mentoring junior colleagues, liaising with