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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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available computational tools for automated imaging analysis of neurodevelopmental disorders. Genetic testing has transformed our understanding of neurodevelopmental epilepsy. Identification of common genetic
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to refereed journals and to attract external research funding. What you would be doing Main Duties: Using characterisation techniques such as ToF-SIMS, SEM, etc. to investigate rechargeable batteries. Analysis
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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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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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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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-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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(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