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Field
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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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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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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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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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(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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-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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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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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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) in quantitative biology, statistics, or a related discipline, and have experience using statistical modelling and data analysis to address predictive or inferential questions in ecological