This is an exciting opportunity for an ambitious post-doctoral research associate to join the MRC Biostatistics Unit to carry out methodological research relating to Bayesian inference.
The post-holder will focus on developing novel Bayesian statistical methodology to improve the analysis and understanding of biomedical data, particularly relating to population health and/or patients in hospitals. Depending on their skills and interests, there are several potential directions that the postholder could pursue. See https://www.jobs.cam.ac.uk/job/43238/ for further details.
The MRC Biostatistics Unit undertakes research on statistical methods and their application to the design, analysis and interpretation of biomedical studies, to advance understanding of the cause, natural history and treatment of disease, and to evaluate public health strategies. It is one of Europe’s leading biostatistics research institutions and includes many internationally renowned statisticians. The Unit is situated on the Cambridge Biomedical Campus, one of the world’s most vibrant centres of biomedical research, which includes the University of Cambridge’s Clinical School, two major hospitals, the MRC Laboratory of Molecular Biology, and the world headquarters of Astra Zeneca. The Unit provides a privileged environment for conducting research within the Cambridge biomedical environment.
The Unit is actively seeking to increase diversity among its staff, including promoting an equitable representation of men and women. The Unit therefore especially encourages applications from women, from minority ethnic groups and from those with non-standard career paths. Appointment will be made on merit. The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. We welcome applications from those wishing to work part-time. The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
Fixed-term: The funds for this post are available for 3 years in the first instance.
For further details and to apply see: https://www.jobs.cam.ac.uk/job/43238/