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insights from geometry and topology to discover new applications of machine learning. Multiple positions may be available. Role Requirements The successful candidate must have a PhD (or close to submitting
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physiology etc. This PhD project is suitable for applicants with a background in Electrical and Electronic Engineering or closely related fields. Candidates with a strong interest in RF engineering and/or
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catalytic process. In addition, it is important to improve the student the experimental skill, materials characterization skill and data analysis skill. Student who joins our group will learn the fundamentals
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the successful candidate embarking on a PhD programme at LSHTM. It is anticipated that the role will lead to a further 18 month funded opportunity at Max Planck Institute for Demographic Research (MPIDR), in
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projects. The role will also provide the opportunity to learn and develop medicinal chemistry skills as applied to drug design. The role is ideal for someone who has, or is about to be awarded, a PhD in
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, 'illogical' outcomes can sometimes be generated due to biases, gaps or pollution of the training sets. They typically lack the ability to generalise and to reason beyond what it has been trained over. It is
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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PhD studentship: Understanding the retention and treatment of highway runoff pollutants within roadside bioretention systems – and implications for design and long-term maintenance Award Summary
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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skilled graduates through research projects that use industrial challenges as the catalyst for methodological advance. Work directly with leading industry partners Many of our PhD projects are developed and