13 associate-professor-computer-science-"https:"-"https:"-"https:"-"https:" Fellowship positions at King's College London in United Kingdom
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, and with expertise in quantitative and qualitative methods, to develop a training and capacity-building programme and lead research projects working on large datasets. On training and capacity-building
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, engineering, psychology/HCI, computer science, or related discipline). For the appointment as the Research Fellow, a PhD degree is essential. Demonstrable experience coordinating complex projects or programmes
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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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of the UK-Irish Atopic Eczema Systemic TherApy Register (A-STAR). A-STAR is the UK’s flagship register of atopic eczema patients on systemic therapies, under the leadership of Professor Carsten Flohr, Chair
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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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and diagnostic applications, including clinical translation to benefit patients. The Programme is mainly hosted by the Research Department of Imaging Chemistry and Biology within the School
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Job id: 142026. Salary: £53,947 - £74,613 per annum including London Weighting Allowance. Posted: 25 March 2026. Closing date: 08 April 2026. Business unit: Dentistry, Oral & Craniofacial Sciences
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and academic and/or external networking Desirable criteria Teaching in Higher Education qualification (such as fellowship or associate fellowship of the Higher Education Academy) Knowledge and/or
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details:Sam Norton (Professor of Medical Statistics & Applied Health Research). sam.norton@kcl.ac.uk Location: Guy's Campus & Denmark Hill Campus. Category: Research. About us: King’s College London is one
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clinical base at the Maudsley Hospital and involves affiliated laboratories across King’s Health Partners. The programme is strongly lead by statistical modelling to predict not just Parkinson’s disease (PD