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developing Generation IV nuclear reactors. With the complication of Salts chemistry and the extreme conditions to operate, the material degradation behaviour when the components are subject to mechanical
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overall porosity increase and volume expansion have only been observed in unconfined cases, where reaction rates are appreciable. This PhD project will work alongside leading teams within the University
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Bachelor’s Degree in an appropriate field will also be considered. Subject Area Analytical Chemistry, Physical Chemistry, Machine Learning, Mechanical Engineering, Chemical Engineering, Materials Science
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Degree in an appropriate field will also be considered. Subject Area Applied Chemistry, Physical Chemistry, Fluid Mechanics, Mechanical Engineering, Chemical Engineering
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considered. Subject Area Environmental Chemistry, Industrial Chemistry, Chemical Engineering
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with a First Class Bachelor’s Degree in an appropriate field will also be considered. Subject Area Applied Chemistry, Industrial Chemistry, Atomic Engineering, Chemical Engineering, Energy Technologies
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the Schools of Chemistry and Chemical Engineering at the University of Leeds, will investigate flow chemistry and machine learning approaches for the development of an automated reaction screening platform
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Daniel Marsh – [email protected] Project summary The School of Chemistry is offering a PhD studentship, funded by the Science and Technology Facilities Council (STFC), in the general areas of planetary
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School/Faculty Chemistry, Faculty of Engineering & Physical Sciences, University of Leeds Closing Date: 29 April 2024 at 23:59 Eligibility: UK Applicants only Funding EPSRC Doctoral Training
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@leeds.ac.uk Project summary Ligand/material discovery has been carried out through laborious trial-and-error approaches. Recent advances in high throughput computational chemistry and AI/Machine Learning