We currently have a PhD studentship available on statistical/epidemiological modelling of large scale health care databases (such as The Health Improvement Network – THIN), aiming to bridge from the findings of landmark randomised clinical trials (RCTs) into the real world population.
The major advantage of RCTs over observational studies is that confounders (known and unknown) are distributed between experimental groups on the play of chance, enabling unbiased estimation of treatment effects. Yet, RCTs are expensive, time consuming and generally designed to examine short-term or surrogate outcomes in highly selected populations. Therefore, there is a need to establish the extent to which we can bridge from RCTs to real world settings and address a broader range of efficacy, effectiveness, and related policy questions.
This PhD studentship would suite candidates with a numerical background and interest in the application of various statistical and epidemiological methods. The PhD student will be a part of a larger team of epidemiologists/statisticians and PhD students working with large clinical databases within the Department of Primary Care and Population Health, UCL. The studentship is funded by the National School of Primary Care Research and is awarded by open competition.
For further information and informal discussion please contact Prof Nick Freemantle [log in to unmask] as soon as possible (deadline - early April).
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