The MRC Biostatistics Unit is a leading centre of innovative biostatistics research. An opportunity has arisen for a MRC Postdoctoral Fellow to work with Dr Jessica Barrett on risk prediction for cardiovascular disease (CVD). This project will address the question of when an individual undergoing a cardiovascular risk assessment should optimally return for their next assessment using data from electronic health records. The aim is to develop methodology which can be used to inform personalised screening schedules for CVD. The project will make use of recent developments in statistical methods for dynamic risk prediction, such as landmarking, with longitudinal modelling of CVD risk factors and survival modelling of CVD events. There is also scope for methodological development in the use of cutting-edge statistical models, such as joint models, in big data. The project will involve close collaboration with colleagues at the nearby Cardiovascular Epidemiology Unit, including Dr Angela Wood and Dr Michael Sweeting.
The successful candidate will have a PhD (or be in the final stages of obtaining their PhD) in statistics and experience of statistical methods for the analysis of longitudinal data and survival data, preferably using statistical software such as R or Stata. Strong programming skills and knowledge of prediction modelling and/or statistical methods for dynamic risk prediction (e.g. landmarking or joint modelling) would be highly desirable. Willingness to collaborate with others and an open-minded approach to problem solving are essential. The successful applicant will be supported in their career development with a range of formal courses and on-the-job training.
If you have any questions about this vacancy, please contact Andrea Wadeson at email@example.com.
Fixed-term: 3 years.
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.
Closing Date: 13th January 2019
Interview Date: 28th January 2019
Please quote reference SL17468 on your application and in any correspondence about this vacancy.
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