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Field
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econometrics, machine learning, and GIS for predictive housing price modelling Addressing Edinburgh and South East Scotland's Construction Skills shortfall The full description of the projects is available here
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
energy systems. The global focus on safety, predictive maintenance, and lifecycle cost reduction. The rising availability of high-fidelity NDT data and accessible machine learning tools. In summary
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sequestration, are poorly understood and require robust quantification if we are to improve our predictions of future responses to climatic changes. Research methodology: You will analyse ship-based and glider
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the Mauritius parakeet to develop an AI model that can predict the response to viral infection based on genomics data. Moreover, there is the option to conduct fieldwork in Mauritius to gather additional field
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may lead to the amplification of climate change. We predict that an increase in AMR in the Arctic will reduce microbial carbon use efficiency (CUE) because competitive interactions among microbes would
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and individual fitness, including determining the added value (beyond metrics of inbreeding) of such scores in predicting fitness 2) Quantify drift load (the reduction in fitness caused by deleterious
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effects on developmental plasticity of behavioural, cognitive and biological phenotypes.� Explore whether early-life gut microbiomes predict first-year fitness.� TRAINING� You will join a supportive
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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. This ‘omics approach will also enable the prediction of other pollutants that this organism can remediate in addition to any valuable biochemicals that may be extracted from the biomass. Number Of Awards 1
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://doi.org/10.1039/D2CC00532H ) that have potential applications in sensing, separations and catalysis. Our research focusses on three distinct challenges to achieving efficient material prediction: i