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of sustainable hydrogen production. The successful student will have access to the University of Sheffield laboratories and to the High Performance Computing (HPC) clusters (ShARC and Bessemer). Our group has
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Fanran Meng, Prof A Ryan Application Deadline: Applications accepted all year round Details Life cycle assessment is increasingly used to assess environmental performance, identify “hot spots” in
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Bio-inspired micro-electromechanical sensors (MEMS) to measure high-order acoustic pressure derivatives for condition assessment of buried water supply pipes School of Electrical and Electronic
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PhD student to develop high-performance avalanche photodiodes for detecting weak infrared optical signals. The PhD student will gain a range of valuable skills for semiconductor research (e.g. wafer
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supplemented by Continuing Professional Development (CPD), which is embedded throughout your 4-year research scholarship. In addition, the successful candidate will also develop skills in: High performance
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to support smart manufacturing, operation and monitoring of industrial processes and equipment. Digital twins (DT) are multiphysics, multiscale, high-fidelity simulation that emulate in real-time the state
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withstand the high loads and start-stop nature of operation. This project is about supporting those developments. Some questions that will need to be addressed: will conventional bearing facing materials
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at application). Proficiency in teaching computer science topics and assessing student performance (assessed at application, presentation and interview). Project-management skills to ensure timely delivery
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that operate with minimal computing, sensing, and actuating resources—essential features for implementation in real-world scenarios. To this end, we will leverage sophisticated mathematical tools such as
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modelling, ideally with a track record of technical skills in these areas. Your main responsibilities will be to generate new immune cell specific transgenics and perform in vivo experiments to assess