National Heart and Lung Institute PhD Studentship in Medical Statistics, Imperial College London
The National Heart and Lung Institute of Imperial College London is seeking applications from candidates with a Master’s degree (or equivalent) in Medical Statistics or Epidemiology or a related discipline, for a 3 year PhD studentship. The candidate will apply novel statistical methods to data from a longitudinal clinical database to assess whether early life growth and nutrition predict later health in children with cystic fibrosis.
This project will use data from cystic fibrosis registries in the UK, Canada and Denmark. Candidates will use and develop novel statistical methods for longitudinal growth curve analysis to identify differences in growth trajectories between children with cystic fibrosis, identify factors that may explain such differences and determine whether these differences influence long term prognosis. We are particularly interested in applications from those with experience working with large and complex epidemiological datasets arising from surveys or health utilisation records and who envisage a career in medical statistics.
The studentship will be funded for 3 years with a tax free bursary of £22,278 per annum. Tuition fees at the Home/EU rate will also be paid. International students should note that those who are not UK/EU citizens will need to provide evidence that they have financial resources to pay the difference between the Home/EU and the overseas tuition fee rates.
Any enquiries relating to the project and/or suitability should be directed to Prof. Debbie Jarvis(email@example.com) or Dr Sanja Stanojevic (firstname.lastname@example.org).
How to apply
please send a CV, a one page personal statement, and the names and addresses of at least two academic referees to Deborah Jarvis by email on email@example.com. Please note that all candidates must fulfil College admissions criteria.
Application deadline: 5pm, 28 February 2016
Start date: At a time between 04 April and 03 October 2016 (latest)