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TypeFixed-termWorking TypeHybridAvailable for SecondmentNoClosing Date30-Apr-2026JD_Param11NoJD_Param12No Two NIHR UCL UCLH BRC Studentships in Artificial Intelligence in Medicine or Health Data Science Two
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. Further information about the University can be found here . Find out more about the benefits of working at the University and what it is like to live and work in the Durham area on our Why Join Us
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Midlands Graduate School Doctoral Training Partnership | Warwick, England | United Kingdom | 10 days ago
datasets, such as the Millennium Cohort Study (MCS) and Longitudinal Education Outcomes (LEO). There will be scope to tailor the project focus and decide on the most appropriate source(s) of data. A key
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and hence open to UK nationals and those of equivalent status. [More information here ]. Applicants that do not meet UK home fees requirements are also encouraged to apply for this position, however
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reliable transmission of demanding multi-modal data such as haptic feedback, video, and 3D sensing data. This project will develop AI-driven predictive network intelligence to anticipate delay and network
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first-opinion practice. As part of this project, you will gain mixed-methods research experience, including data collection and analysis using both quantitative and qualitative methods. Prior experience
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a grant for living costs. Awards are made for the full duration of your fee liability for the agreed course. For more information and details on how to apply please visit the Oxford-Taiwan Graduate
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Selden Studentship Regulations . Further information may also be obtained from the Secretary of the Society, School of Law, Queen Mary University of London, Mile End Road, London, E1 4NS, selden-society
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tradeable points can be used under the rules. Information on other visa options is available at www.gov.uk/check-uk-visa . Please do not hesitate to contact Grant Rae, HR Adviser (e-mail: grant.rae@abdn.ac.uk
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trigger redesigns across multiple groups. The challenge is compounded by the fact that each discipline uses different data models and representations, making system-level interdependencies difficult