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View All Vacancies Chemistry Location: UK Other Closing Date: Sunday 12 May 2024 Reference: SCI266 Uncertainty quantification for machine learning models of chemical reactivity In this PhD
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View All Vacancies Chemistry Location: UK Other Closing Date: Monday 15 July 2024 Reference: SCI277 Applications are invited for an industrial led PhD studentship aimed at developing new
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background in chemistry, materials, engineering and/or data science and are interested in this multi-disciplinary PhD opportunity please get in contact with Dr Karen Robertson ([email protected]
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motivation to develop a world-leading expertise. The successful candidate will have a background in chemical engineering, chemistry, materials sciences, or a related field but be willing to learn new
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other countries) in Chemistry or a related subject (such as Natural Science, Materials Science, Physics, Engineering). If English is not the candidate’s first language, they must provide evidence before
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: This position is only open to UK students. The candidate must have at least an equivalent of a UK 2.1 class degree in materials/mechanical/ manufacturing/chemical engineering/physics/chemistry or any related
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Research Group in the Faculty of Engineering, focusing on harnessing the power of digital twins to revolutionise bioprocesses for waste treatment and high-value chemical production. Vision and Motivation
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: Chemistry, Biochemistry, Physics, Material Science, Natural Sciences, Biotechnology, Pharmacy, Chemical Engineering, Environmental Engineering, Pharmacy, Synthetic Biology, Computational Biology/Chemistry or
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by Prof Neil Oldham and Dr Luisa Ciano, from the School of Chemistry, and Dr Doug Roberts and Prof Greg Challis from Erebagen. It will provide training in biosynthetic engineering using state
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completion of a Master's degree in Medicinal Chemistry, Chemical Engineering, or a related field. A background in flow chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming