23 algorithm-development-"Multiple" "Prof" Fellowship positions at University of London
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is Prof Cally Tann. We are seeking a Research Fellow in Early Child Development & Disability to coordinate the development, implementation and evaluation of the programme, including: mixed methods
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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analysis to join a dynamic team that has, for the past 8 years, developed an extensive body of research on corruption, governance and anti-corruption strategies. In the Accountability in Action project
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to join the Environment & Health Modelling (EHM) Lab (https://www.lshtm.ac.uk/ehm-lab ) led by Prof Antonio Gasparrini. The successful candidate will work on the project CONNECT – Cohort and environmental
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the College’s small animal referral hospital by further developing and delivering advanced cardiac surgical therapies through the open heart surgery programme, at the Royal Veterinary College. We are looking
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to cancer treatment delays. The successful candidate will join 50 researchers on 10 National Cancer Audits https://www.natcan.org.uk/ . The postholder will report to Prof Ajay Aggarwal (co-PI, TACTIC and
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-led by Queen Mary University of London. PharosAI is set to revolutionise AI-powered cancer care, accelerating the development of breakthrough therapies, advancing clinical applications, and improving
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including malaria, have experience and understanding in using multiple metrics for analysis, experience with design and implementation of study protocols, experience of data analysis in Stata and programming
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countries, centering on Zambia, Zimbabwe, Ethiopia, The Gambia, and Uganda. Successful applicants will develop their potential to become global health leaders within a structured and mentored training
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research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models