About QIMR Berghofer:
QIMR Berghofer is a world-leading translational medical research institute focused on improving health by developing new diagnostics, better treatments and prevention strategies, specifically in the areas of cancer, infectious diseases, mental health and complex disorders. Based in Herston, Brisbane and working in close collaboration with clinicians and other research institutes, QIMR Berghofer is home to more than 600 scientists, students and support staff
About the Statistical Genetics Laboratory:
The Statistical Genetics laboratory at QIMR Berghofer comprises staff and students working on statistical methods development and on applications to data and is part of the Computational Biology department.
Role Purpose / Responsibilities:
Your role will focus on the use of statistical genetic approaches in causal inference. Whilst observational studies suggest that a range of modifiable risk factors may alter risk of cancer, observational studies can only demonstrate association between a risk factor and cancer, and causality cannot be assumed. Randomized trials are the gold standard for causal inference but these are frequently prohibitively expensive and/or impractical or unethical. There is hence a need to assess causality more cost effectively. We believe this need can be met using Mendelian randomization, an approach to causal inference using genetic data.
For a range of combinations of risk factor and cancer type, you will conduct causal inference using Mendelian Randomization. The Statistical Genetics Laboratory is uniquely placed to lead this analysis due to its leading role in consortium-based genetic analysis of cancers of the skin, oesophagus and ovary. You will conduct statistical genetic analysis of these large scale data sets and interpret and publish the findings. Additionally, there is also scope within the role to contribute to a range of statistical genetic projects in the laboratory.
Describe your research interests
Indicate your level of competence in statistics, in computing/programming and in biology/genetics
Include details of 3 academic referees
The post is ideally suited to someone with a PhD in genetic epidemiology, epidemiology, statistics or bioinformatics. Experience in the analysis/manipulation of large datasets and a good knowledge of computing is desirable. Preference will be given to applicants with a very good publication record relative to opportunity. Experience in Mendelian Randomization and cancer genetics advantageous but not essential. Non-statistical applicants must be able to demonstrate some knowledge of statistics. For statistical applicants, some knowledge of genetics is required.
In your application please address the following selection criteria/requirements: