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New ways to deal with selection bias in genetic studies of disease progression

Project Description

In this project you will develop and apply new statistical methods to identify which genes affect survival time with idiopathic pulmonary fibrosis, and which genes affect growth rates of abdominal aortic aneurysms. The findings will indicate new approaches to treatment and management of these diseases.

Such studies of disease progression can be biased by unknown factors that affect both the risk of developing disease and the course of disease once established. Our group has recently developed new statistical approaches to correct this bias, using the results of genome-wide association studies. A substantial part of this project will be evaluating and developing improved methods building on our initial approaches. This will require programming of statistical analyses and computer simulations, and you should therefore have a demonstrated aptitude for statistical programming.

You will also analyse large datasets in Leicester and Nottingham on disease progression in idiopathic pulmonary fibrosis and abdominal aortic aneurysm. You should therefore have an aptitude for working with big data and for presenting results to cross-institutional collaborators clearly and succinctly.

You will join one of the largest genetic epidemiology groups in the UK, with excellent opportunities for networking and career development in a fast moving and high profile area.

Interviews will be held in the week commencing the 11th February 2019.

Entry requirements

Applicants are required to hold/or expect to obtain a UK Bachelor Degree 2:1 or better in a relevant subject. The University of Leicester English language requirements apply where applicable.

How to apply

Please apply via:

Project / Funding Enquiries: Prof Frank Dudbridge, , 0116 252 5474
Application enquiries to
Closing date for applications 20th January 2019

Funding Notes


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