668 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "University of London" positions at University of Sheffield
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skills, experience of delivering presentations Essential Application/interview Excellent record keeping and data management skills, with appropriate IT experience Essential Application/interview Ability
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and responsibilities Conduct a comprehensive review and synthesis of existing air quality, health and economic data, applying quantitative and computational techniques where appropriate to ensure robust
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the organisation and delivery of a range of marketing activities Develop, manage and maintain processes, tools, databases and spreadsheets to store information in the most appropriate format, adhering to GDPR
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and applications, responding to queries, collaborating closely with other Professional Service teams, contributing to the smooth set-up of successful research applications and maintaining data in
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for evidence of ultra-light particles (e.g. axions) and beyond Standard Model physics in astronomical data. The student will undertake one or more projects in the areas above. In conjunction, the student will
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'. For further information about the project please contact the supervisor at martin.jackson@sheffield.ac.uk. fusion_cdt Funding Notes Students will receive a 4-year studentship including home tuition fees, UKRI
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managed together. The challenge is to develop modelling approaches that can be applied across populations of structures. Instead of building a bespoke model for each asset, information can be intelligently
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the subsequent quality of the parts produced. Ultimately this information will be used to produce a thermal model of the process, to help develop specific guidance for future component and/or equipment design
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foundational training in fusion engineering as part of the cohort, and supported to complete a portfolio to support CEng status. For more information about the CDT programme please visit www.fusion-engineering
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, personalised treatments, and systematic evidence verification. This is a complex information integration problem, where clinicians must analyse vast, heterogeneous, and fragmented clinical knowledge. Clinical