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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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other at policy-relevant scales, while ‘top-down’ estimates, based on atmospheric measurements and modelling, are hampered by large natural fluxes of CO2 between the terrestrial biosphere and the
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extending the existing VL dataset. Design and evaluate DL models capable of classifying marine litter types using multispectral data, with a focus on achieving robustness to varying spectral channel
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model to resolve wheat planting strategies that can be used to safeguard biodiversity and suppress rust outbreaks. Training You will be embedded in the international and multidisciplinary Saunders Lab
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; biogeochemistry and fisheries modelling). The PhD candidate will acquire and/or strengthen their understanding of interdisciplinary working, modelling and statistics applied to economics, trade-off analysis skills
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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knowledge gaps. The project involves both linear and nonlinear dynamics modelling and analysis, as well as experimental testing. An equivalent test structure will first be constructed in the vibration
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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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The University of Liverpool is seeking to appoint 1-2 motivated and enthusiastic postdocs to conduct research on making Generative AI (GenAI) more robust. You will enjoy a vibrant environment at
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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device