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efficient IoT systems. Please state your entry requirements plus any necessary or desired background First or Upper Second Class UK Bachelor (Honours) or equivalent Subject Area Computer Science & IT
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researcher will become part of the Corrosion and Mineral Scaling Research Team within the Institute of Functional Surfaces (University of Leeds), a vibrant and diverse research group with expertise in
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of whole-body and tissue-organ composition and energy expenditure with physiological and psychological measures of appetite, and free-living energy balance tracking technology is used to measure energy
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taken up by 1st October 2024. Applicants must live within a reasonable distance of the University of Leeds whilst in receipt of this scholarship. Lead Supervisor’s full name & email address Dr. Wuhu Feng
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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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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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Funding A highly competitive EPSRC Quantum Technologies Doctoral Training Partnership Studentship offering the award of fees, together with a tax-free maintenance grant of £19,237 per year for 3.5 years. Training and support will also be provided. Lead Supervisor’s full name & email...
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A highly competitive EPSRC Quantum Technologies Doctoral Training Partnership Studentship offering the award of fees, together with a tax-free maintenance grant of £19,237 per year for 3.5 years. Training and support will also be provided. Lead Supervisor’s full name & email address Professor...
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-set. You will be funded for 3 years and will pursue a doctoral degree during this time. This DR position is based at the University of Leeds and will involve expanding and developing our iSIM (instant
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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