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Field
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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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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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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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identifications from the synchrotron X-ray data. The data acquired will be compared with existing transformation kinetics models to assess their reliability and, where necessary, will provide the data needed
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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
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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critical, to ensure expected engine performance is achieved. To predict this complex flow and heat transfer, next-generation Computational Fluid Dynamics (CFD) solvers using Large-Eddy Simulation (LES) and
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million individuals has never before been possible in genetics research, not even in model organisms, and promises to transform the way we think about evolution. The student will receive broad training in
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will be tasked with the development of new models for the early detection of CIN cancers, applying bleeding edge computational methods and machine learning approaches to improve detection and
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architectures (cassette and containerised). Use CFD modelling and lab pilots to optimise hydraulics, mass transfer, and electrode configurations. Energy Integration Quantify full energy balances of MEC operation