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PhD studentship in Computational Chemistry – Training force fields for computer-aided drug design with machine learning. Award Summary 100% fees covered, and a minimum tax-free annual living
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IAPETUS DLA PhD Studentships – Geography, Natural and Environmental Sciences, Mathematics, Statistics and Physics, Civil Engineering, Computing, & Geoscience Award Summary 100% of tuition fees paid
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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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properties of representative sediment classes. · Evaluate methods for predicting sediment type and physical properties from geophysical data using machine learning. · Assess the reliability
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properties of representative sediment classes. · Evaluate methods for predicting sediment type and physical properties from geophysical data using machine learning. · Assess the reliability
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. You’ll gain experience in spatial analysis, fieldwork, soil and vegetation monitoring, and potentially numerical modelling. The project is a close collaboration with its sponsor, the Environment Agency
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and presents the opportunity to investigate semiconductors, composites, waveguides and resonators. The student will explore synthesis and fabrication strategies and develop methods for advanced optical
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resonators. The student will explore synthesis and fabrication strategies and develop methods for advanced optical characterisation. The student will be provided training and access to advanced
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built to identify and correct errors, apply bias adjustments, and assess data quality. State-of-the-art multisource blending methods will then be applied (e.g. kriging, probabilistic merging, machine
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and adapting existing simulation models of transport systems and development of methods for resilience analysis. The PhD project will suit students from any quantified background, including engineering