Sort by
Refine Your Search
-
Listed
-
Field
-
this Fellowship. The Fellowship will be for a period up to 6 months (normally between January and June 2026), based in Paris or London, or split between the two cities. As a Fellow, you will develop a programme of
-
computational research projects and data infrastructure carried out in the research group. The post-holder will be able to develop research questions within Statistics, Population Data Science, Computational
-
of the research project and develop new areas of research. The post-holder will be expected to undertake a higher degree such as a PhD during the fellowship. About You The applicant must be a medically qualified
-
, in a relevant topic and relevant experience with mathematical modelling of infectious diseases. Strong knowledge of a programming language (e.g. R, Python) is essential. Experience in mathematical
-
PhD) while conducting highly policy relevant research. Applicants should have a postgraduate degree with MRCP or MRCS. Relevant clinical experience in providing cancer treatments, co-ordinating clinical
-
, Professors Ruth Keogh and Kate Walker. Applicants should have a postgraduate degree, ideally a PhD, in medical statistics, epidemiology, health economics or a related field. Relevant experience in applying
-
team of seven investigators at Royal Holloway, where this post will be based, and RHUL/NPL joint PhD students. Royal Holloway is a partner in the Oxford-led QCI3 Quantum Hub. We are collaborating with
-
team of seven investigators at Royal Holloway, where this post will be based, and RHUL/NPL joint PhD students. Royal Holloway is a partner in the Oxford-led QCI3 Quantum Hub. We are collaborating with
-
environment, home to around 450 staff, 100 PhD students and 500 postgraduate taught students. It harnesses expertise across a wide range of population-based research and education activities and aims to be
-
analytic codes to investigate the benefits and harms of medications. Candidates must have a doctoral degree (or be within 3 months of anticipated completion of a PhD) in medical statistics or epidemiology