[R-jobs] PhD Studentship in Medical Statistics

Lin, Nan N@L|n @end|ng |rom exeter@@c@uk
Wed Jul 3 22:42:17 CEST 2013

PhD studentship in Medical Statistics (full time, 3 years) - University of Exeter Medical School

Applications are invited for a PhD studentship at the University of Exeter Medical School (UEMS). We are seeking to attract a PhD candidate of outstanding ability to join a rapidly expanding programme of internationally rated research.

The successful applicant will pursue a project investigating new statistical techniques for sensitivity analysis in medical research. This is an exciting opportunity to contribute to developing statistical methodology for quantifying bias when estimating the effectiveness of medical interventions. The studentship is due to commence in Autumn 2013 and is linked to a project funded by the Medical Research Council (MRC) Methodology Research Panel and forms part of a growing programme of work on sensitivity analysis methods.

Applicants should hold, or expect to obtain, an upper second-class honours degree or above in Statistics or Mathematics, or a degree with substantial quantitative component, such as Quantitative Health Sciences, Psychology, Economics, Engineering, Computer Science or Physics. A Masters degree or work experience in a relevant area would be an advantage. International applicants are welcome.  Non UK candidates must have IELTS [International English Language Testing System] score of at least 7 (or equivalent qualification) or a degree taught in a majority English speaking country.

Research area: Health statistics

Title: A unifying approach to quantifying bias in sensitivity analysis for treatment effects

Project outline: Risk of bias due to uncertainty about untestable assumptions is common in both observational studies and randomised controlled trials. Complete control for the risk of bias is unlikely in practice, but its impact can be estimated by means of sensitivity analyses. The aim of this project is to develop a unifying approach for sensitivity analysis, facilitate efficient implementation and make the proposed approach accessible. The unifying approach will make it possible to systematically integrate the assessment of bias into conventional analyses for a range of statistical models (including logistic regression, survival analysis, Poisson regression, meta-analysis) for both randomized and non-randomized studies.  Application of these methods will help facilitate better research planning, reporting and decision making.

Closing date for applications: Friday 19th July 2013. Start date: 23rd Sep 2013
Value:  �13,726 pa plus tuition fees at UK/EU rate
Further Particulars are available at http://www.exeter.ac.uk/studying/funding/award/?id=1238
Please contact Nick Church in the first instance for more details (N.J.Church using ex.ac.uk)

Informal discussion is welcomed and candidates are invited to contact Professor William Henley (Director of studies, W.E.Henley using exeter.ac.uk), Dr Nan Lin (N.Lin using exeter.ac.uk) or Dr David Llewellyn (David.Llewellyn using exeter.ac.uk)

How to apply:
Please send a CV, Covering letter (outlining your academic interest in Health Statistics and the research project, prior research experience, and reasons for wishing to undertake the project) and copies of transcripts of degrees/awards to Nick Church (N.J.Church using ex.ac.uk) by the closing date of midnight on Friday 19th July 2013. ***Please quote Health statistics and the project title on your application and in any correspondence about this vacancy.

Funding Notes: The starting stipend for this studentship will be �13,726 p.a.(tax-free). Tuition fees will be paid at the UK/EU rate. Candidates from countries outside the European Union will be liable for the difference between 'home student fees' and 'international student fees� which was �10,250 in 12/13 but is likely to increase slightly each year. If you wish to be considered for this studentship you must confirm that you are able to pay the international portion of the fee.  If you are selected you will be required to provide financial assurances.

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