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computational fluid dynamics and numerical modelling will be used to simulate performance under varying runoff scenarios, pollution loads and climate conditions. By developing advanced road gully designs with
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to the design of aircraft, wind turbines and medical devices, and for modelling the environment. Remarkable advances in computing driven by the exponential miniaturisation of transistors (Moore’s law) have
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intensifying upper ocean mixing processes. However, major gaps in our understanding remain due to challenges in observing and modelling the Arctic Ocean. Research Methodology The aim of this project is to
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vegetation monitoring, and potentially numerical modelling. The project is a close collaboration with its sponsor, the Environment Agency, meaning your findings will inform future levee design, inspection, and
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scientific computing, to name a few. Modern LC applications rely heavily on accurate and efficient mathematical modelling of confined LC systems. Typical questions are - can we theoretically predict physically
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observations and modelling of the physics and biogeochemistry of Antarctic shelf seas. You will gain experience in computer coding, statistics for environmental science, working with and piloting autonomous
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of how alternative land management practices impact greenhouse-gas fluxes through the development and application of sophisticated modelling tools. The work will involve model development on the Cambridge
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associated numerical methods and AI, will be used with High Performance Computing (HPC) to improve understanding of key flow physics and inform future HPT design. Skills and Experience Required: Applicants
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King's College London Department of Engineering | London, England | United Kingdom | about 1 month ago
arising from different vegetation fire types such as crown fires, shrub fires, and smouldering fires. A methodology to link lab-scale and field-scale fires. Numerical model of ignition with a database of
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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