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Prospective candidates will be judged according to how well they meet the following criteria: A first-class honours degree (or equivalent) in Engineering, Physics or Materials Science Excellent written and
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, including Engineering, Physics, Mathematics, and Computer Science – candidates with experience with Machine Learning and/or Crystallography would be particularly suited for this project. This project will
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awarded a first class or 2.1 honours degree (or equivalent if from other EU countries) in materials science, chemistry, physics, chemical engineering, mechanical engineering, manufacturing, or a relevant
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sequencing (a process termed next generation phage display, NGPD). The studentship will apply NGPD to target cell surface GAGs from breast cancer cell populations, identify specific binders, clone and express
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View All Vacancies Engineering Location: UK Other Closing Date: Wednesday 07 August 2024 Reference: ENG1773 Electrical System Study and Modelling Based on 25kV Railway AC Electrical System
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, navigation, rotation sensing, spectroscopy, interferometry, Rydberg atoms) Quantum technologies for fundamental physics Quantum Information and Quantum Computing (G. Adesso, M. Guta, et al.) Quantum technology
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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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will explore the use of fibre Bragg gratings (physical sensor) in combination with photoplethysmography (physiological sensor) for applications in rehabilitation. For example for people recovering from
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(thickness of a human hair) that can be used to measure a person’s physical and physiological properties. This PhD will explore the use of fibre Bragg gratings (physical sensor) in combination with
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performance and green innovation. It also explores how these effects change when combined with environmental regulations and innovation incentives. The project will employ statistical analysis and econometric