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pellets. To do this we need to develop magnetic resonance imaging methods that spatially resolve chemical species present with the catalyst pellet while the conversion is occurring. This, in turn, will be
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aims to develop and apply the cutting edge of Bayesian analysis and machine learning to the optimisation of satellite configurations for GNSS-R. Combining the data science expertise of Dr Handley's
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ice) of signals originating from GNSS (Global Navigation Satellite System) signals. The proposed project consists of educating a new generation of experts, at doctoral level, able to bring a qualitative
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on the ground (or sea, or ice) of signals originating from GNSS (Global Navigation Satellite System) signals. The proposed project consists of educating a new generation of experts, at doctoral level, able
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social stories have yet to be explored. Together with the team of supervisors, the successful candidate will develop a project to interrogate the history of these collections or some parts of them with
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computational modelling of a wideband, light and steerable antenna for GNSS-R applications (also contributing to the prototyping and test of "best" design according to the metrics developed); and to develop
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the best instructions to use for given intermediate code fragments and alleviating manual engineering effort. The successful candidate will develop new code-generation strategies using machine-learning
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, will be a game changer in the tabletting field. Develop an experimental protocol to investigate the effect of the compression speed, tablet composition and powder characteristics on the tabletting
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strategies to prebiotic chemistry by transforming primitive lipids into modern lipids through non-enzymatic chemical strategies. The student will design and develop novel synthetic methods to generate
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, Education Supervisor [email protected] . Enquiries regarding the scope of the PhD or funding should be directed via email to Professor Graham Murray ([email protected] ) and Dr Christelle Langley (cl798