192 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" positions at King's College London
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responsible for ensuring the maintenance of accurate training records and renewals, collaborates with data teams for reporting, and maintains compliance for all mandatory training. Additionally, they will
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Foundation Trust, and South London and Maudsley NHS Foundation Trust. The post-holder will ensure adherence to approved protocols and undertake effective source data verification. The post-holder will ensure
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. The post-holder will ensure adherence to approved protocols and undertake effective source data verification. The post-holder will ensure that all activities are conducted in accordance with applicable
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Development for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria Fluency in English Strong skills in
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at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Further information: We ask all candidates to submit a copy of their
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innovative solutions, and implementing new processes and systems. 4. Excellent communication skills, including experience of translating complex regulations, processes and information in suitable formats
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approaches for managing confidential spatial health data, including differential privacy and other secure geospatial data protocols. This research will advance our understanding of how major infectious
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to ensure data collection and analysis is conducted within timelines. The successful applicant must be able to work independently and collaboratively within a diverse broader research team. The project will
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are kept in the University's student record system (SITS), working with students, faculties, and other departments as necessary to resolve data issues through record interrogation and fact-finding Work
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of Biomedical Engineering & Imaging Sciences. About The Role The research associate will lead the development of cutting-edge multi-modal MRI foundation models. These models will leverage both imaging data and