17 linked-data-"https:" "https:" "https:" "NTNU Norwegian University of Science and Technology" Fellowship research jobs at King's College London
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groundbreaking symbiosis of cutting-edge AI combined with human support. To learn more please visit https://www.kcl.ac.uk/research/embrace About the role The Research Fellow in Digital Health & Data Sciences is
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combined with human support. To learn more please visit https://www.kcl.ac.uk/research/embrace About the role The Research Fellow in Digital Health & Data Sciences is focused on the development and
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community?’, and ‘How have you contributed to broader society?’ See here for more information about these questions: https://royalsociety.org/topics-policy/projects/research-culture/tools-for-support/resume
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THIS VACANCY IS OPEN TO INTERNAL CANDIDATES ONLY About Us We are seeking a highly motivated and experienced researcher to work on the large-scale programme and associated projects of the Data
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THIS VACANCY IS OPEN TO INTERNAL APPLICANTS ONLY About Us We are offering an exceptional career opportunity for an accomplished Research Fellow to support the data analysis and data management team
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assessment of and reflection on the use of AI agents in science. About you – for a PDRA candidate The successful applicant will be able to present information on research progress and outcomes, communicate
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provide updates on the project; manage the budget; and supervise the research assistant who supports the project co-ordination on a part-time basis. In addition, the post holder will work on the data from
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-design workshops, interviews, requirements gathering, data curation/annotation activities, and contribute to the design and evaluation of human–computer interface prototypes through design sprints and
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document, provided at the bottom of the next page after you click “Apply Now”. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Further
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health. The post holder will develop innovative AI techniques approaches applied to oral healthcare, with a particular focus on Large Language Model-based multimodal data understanding and reasoning