Funded PhD opportunity
Alex Lewin and Jonathan Bartlett from the London School of Hygiene and Tropical Medicine are currently advertising a funded studentship (in association with AstraZeneca), which will use and/or implement Bayesian and machine learning approaches to using data from historical trials to supplement current trials.
Deadline is Monday 8 April. Please contact Alex Lewin (alex.lewin@lshtm.ac.uk) for informal discussion and further details of how to apply.
- Project title: Increasing efficiency of Randomised Trials via Bayesian borrowing and prognostic covariates.
- Academic supervisors: Alex Lewin, Jonathan Bartlett (LSHTM)
- Co-funded by: AstraZeneca (Statistical Innovation Group)
Project description
Randomised clinical trials are considered to be the gold standard in research, since they eliminate many sources of systematic bias between comparison groups. However, they are expensive and time-consuming to carry out.
In order to maximise the benefit from trials, researchers increasingly try to combine the information from a new trial with information already gained from earlier trials. It can be especially beneficial to use the data from the placebo arm of previous trials to supplement the data in a new trial.
This PhD will consider two different ways of doing this. The first is Bayesian Borrowing, in which results from earlier trials are converted into informative priors on the parameters for the placebo arm in the current trial, which reduces the uncertainty on those parameters, increasing efficiency of the current analysis. The second is to adjust for a Prognostic Covariate, which is also estimated using a model based on the earlier trial.
The project will implement both methods, and compare results using synthetic data to investigate in which situations one or both of these methods can be used.
Studentship details
The project is available under the 3.5 year scheme. It will include a 3-month placement at AstraZeneca.
Candidate requirements
Ideally, applicants should have an excellent undergraduate degree (first or upper second) in mathematics, statistics or a related field, and have or be currently studying for an MSc in statistics, medical statistics, health data science, or a related field, or equivalents for qualifications gained outside the UK.
UK and international students are eligible to apply.
How to apply
Apply to ESRC Studentship
Studentship Applications must be submitted via the online application survey. Applications received in any other format will not be considered.
Read more information and further guidance about applying.
Deadline
Closing date: Monday 8 April 2024 at 23:59 (BST).