Senior Research Associate in Medical Statistics
Division/School Bristol Medical School
Contract type Open Ended
Working pattern Full time
Salary £38,017 - £42,792 per annum
Closing date for applications 30-Oct-2019
We have an exciting opportunity for a talented medical statistician (or a closely related field with strong quantitative skills) to evaluate statistical methods that examine causal questions, and to create easy to use software to implement these statistical methods. Funded by the Wellcome Trust, the post holder will conduct research on statistical methods and software tools that assess the sensitivity of a study’s conclusions to common sources of bias such as unmeasured confounding, missing data, non-random selection and measurement error.
The successful applicant will have a PhD (or equivalent research experience) in medical statistics or a related quantitative discipline. You will have used a variety of statistical methods and have an interest in the background of these statistical methods; for example, the advantages and limitations of a method. In addition, you will have a keen interest in computer programming, with a clear understanding of basic programming concepts (e.g., if else statements, for loops and while loops).
The post holder will work on this project with Dr Rachael Hughes and Professor George Davey Smith, and with collaborators from within the University and externally. The role will be based at the MRC Integrative Epidemiology Unit (http://www.bristol.ac.uk/integrative-epidemiology/), which is an internationally recognized institute of excellence in epidemiology in the UK, with research programmes encompassing causal modelling, genetic and epigenetic epidemiology.
For informal enquiries please contact Rachael Hughes, email: firstname.lastname@example.org
Interviews are planned for Thursday 28th November 2019.
We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT+ and BAME communities, to join us.