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of the research programme as discussed with the fellowship supervisor. Contribute to research group planning. Coordinate and liaise with other members of the research group over work progress. Supervise research
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researchers regarding legal, ethical and other compliance requirements for research in the public benefit. ● Ensure Y&H SDE maintains legal and ethical compliance with the Secure Data Environments programme
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researchers through a structured programme of activities. Main duties and responsibilities Take a leading role in shaping how the Planning for Nature project communicates its research findings to a wide and
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such as temperature and pesticide use. There is scope for you to drive the direction of the project to suit your interests. Genetic variation underpins the ability of species of adapt to environmental
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Modelling Neutrino Interactions for Next Generation Neutrino Experiments School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Patrick Stowell Application Deadline: Applications accepted all year round Details Neutrinos play a crucial role in our understanding of the...
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Simulation of particle physics experiments on graphical processing units School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof D Costanzo Application Deadline: Applications accepted all year round Details In this project you will combine state of the art software...
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facing the UK’s programme of remediation and restoration of the Sellafield site, expected to be complete in the next century. The PUMaS hub will support ~20 PhD students along with research staff, creating
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Overview Are you experienced in using applied maths to model an acoustic problem and analyse data? Do you enjoy working collaboratively? This role offers an exciting opportunity to apply your modelling and analytical skills in building and testing an acoustic monitoring tool to detect hidden...
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programme grant on hybrid energy storage systems for grid-independent EV charging stations and there will be significant opportunities for the successful candidate to interact with the interdisciplinary team
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Early-stage failure prediction in fusion materials using machine learning