621 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation" "U.S" Fellowship positions in United Kingdom
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Fixed term – 48 months Full time, 37 hours (37 hours per role) Closing date: 27/08/25 at 23:30 Are you passionate about supporting the development of resilient and well-connected communities? Do you
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research-intensive university in North England, UK. Our university’s 2030 strategy is to develop and shape a fairer, brighter and carbon-neutral future. Our mission is to advance education, scholarship
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analysis. Ability to communicate complex information clearly, orally and in writing (including for academic publication). A PhD in relevant field (e.g. sociology, politics, social policy). A developing
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related field, an emerging track record of outstanding publications, and well-developed plans for new research projects. This post is generously funded by the A. G. Leventis Foundation and is therefore
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. The project will define new near miss and severe morbidity definitions allowing us to identify electronically when significant events happen. We will then develop a large multi-centre maternity routine dataset
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Foundations of Computing Position Summary: HIIT provides funding for two types of researchers: Research Fellows and Postdoctoral Fellows. These positions are meant to support the career development of excellent
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this role you need to be able to show a body of research outputs and the level of thought leadership and development towards independence required to be competitive as a future research leader. In this role
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intracellular bacteria replication or control and how antibacterial chemotherapies impact efficacy. We are interested in developing new technologies to dissect the complex dynamics of mycobacterial infection
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/non-clinical partners. Your research strategy will have a strong emphasis on developing ex vivo models to mimic in situ normal breast facilitating compound screening for translational prevention trials
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electronically when significant events happen. We will then develop a large multi-centre maternity routine dataset for the first time. This will allow us to work out the best vital-sign-based early warning score