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production in the context of circular economy. The research activities in this doctoral thesis are planned with the view of developing a comprehensive multi-perspectives analysis approach, essential to track
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, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform statistical analyses to assess stability and plasticity of multisensory
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visual and auditory cortices using techniques such as cross-modal decoding, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform
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, gather relevant data for modelling, and ensure accurate data collection. Conduct comprehensive bioinformatic analysis utilising established methodologies and tools (e.g. R, Python, MATLAB and other
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to/ lead the development and implementation of quantitative analysis and statistical modelling to support the project’s aims of assessing the contribution of An. stephensi to malaria transmission relative
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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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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