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Master’s degree (or other equivalent experience). Suitable backgrounds for these PhD positions include, but are not limited to, power engineering, industrial engineering and operations research, mathematics
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: The successful candidate will have access to a unique ESD-STM equipment to perform world-leading research. They will learn how to operate state-of-the-art sophisticated experimental setups working closely with
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Engineering have a well-developed research support base including NET2Zero CDT, and EPSRC Centre for Doctoral Training in Resilient Chemistry: Feedstock to Function. The research programme will use a mixture
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or computational modelling is desirable but not essential; applicants should demonstrate strong academic performance, resilience in the face of research challenges, a proactive attitude to learning and a willingness
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research area, and work alongside your peers for the first 10 weeks of your studies, splitting your time between high-level training and laboratory rotations. You will also take part in a three-month
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markers. Develop machine learning models capable of predicting Category 1 emergencies based on real-time audio features extracted from calls. Work iteratively with YAS researchers to test and refine
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studentship. The preferred start date is 1st October 2025, but requests for a 1st January 2026 start date will be considered. This PhD studentship is offered by the Plymouth Health Determinants Research
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research area, and work alongside your peers for the first 10 weeks of your studies, splitting your time between high-level training and laboratory rotations. You will also take part in a three-month
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biology experience with laboratory-based research (e.g., cell culturing, molecular techniques, bioinformatics, flow cytometry) ability to work independently and as part of a research team strong analytical
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trials A key outcome will be recommendations on generally applicable operating characteristics for clinical trials in rare diseases, enabling researchers and funders to understand when trials are feasible