# Project Description
Mendelian randomization (MR) uses genetic data to probe questions of causality in epidemiology within the instrumental variable (IV) framework. Statistical methods for MR analysis are well developed and understood for continuous and, to at least some degree, for binary outcomes. Developing methods for time-to-event outcomes, such as all-cause mortality, has proved much more challenging.
The aim of this PhD will be to develop MR methods that are tailored to time-to-event data, by accounting for biases that accrue due to censoring over the life course. Additive hazard and frailty models will be investigated, as well as rank-preserving structural failure time models developed for IV analysis of clinical trials.
The PhD will also develop methods to investigate whether non-linear associations observed between health exposures and survival outcomes are: truly non-linear; a product of confounding; or a sign of invalid instruments. Local Average Treatment Effect and pleiotropy robust methods will be investigated for this purpose. Methods will be motivated by, and applied to, cohort data from the UK Biobank study and ALSPAC.
# Candidate requirements:
Applications are welcome from high performing individuals who have, or are expected to obtain, a 2.i or higher degree (or equivalent) in Mathematics, Statistics or related quantitative discipline. Possession of a relevant research Masters degree or experience within medical research will be an advantage.
# Funding:
This studentship is funded by the Medical Research Council. The studentship consists of full UK/EU tuition fees, as well as a Doctoral Stipend of £14,553p.a. for 2017/18 (updated each year) as well as £2000 per year for research costs and training. Only applicants from the EU and UK are eligible for this programme.
# Supervision
The PhD student will be primarily supervised by Dr Jack Bowden and based within the MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, starting in October 2018. The IEU is an exciting, multi-disciplinary research environment that brings together world leading epidemiologists, statisticians, bioinformaticians, molecular biologists and psychologists to understand causal mechanisms of disease.
# Apply
For further details on how to apply please go to
https://www.findaphd.com/search/ProjectDetails.aspx?PJID=94869
The deadline for applications is Wednesday, March 21st, 2018
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