- Dulari Hakamuwa Lekamlage, QUT
Prostate cancer is one of the leading causes of mortality and is the most diagnosed cancer among men in Australia. The identification of novel biomarkers in prostate cancer could be valuable in the design of therapeutics and the identification of their molecular targets. Previous prostate cancer bioinformatic studies have recognised risk-associated genetic components as potential biomarkers.
This project will apply statistical and mathematical approaches to identify novel biomarkers in prostate cancer.
- Learning basic of genetics and biology of prostate cancer.
- Working and getting familiar with statistical methods applied in identifying genetic variants.
- Developing/customising statistical and mathematical methods to identify novel genetic biomarkers in prostate cancer.
- Learning to handle large-scale health datasets and repositories.
- Utilising high-performance computing in statistical analyses.
- Scripting in R to develop/repurpose statistical methods in genetic analyses.
This project will identify novel genetic biomarkers in prostate cancer using statistical and mathematical applications.
Skills and experience
- Highly motivated to apply and develop computational methods for discovering better medicines.
- Undergraduate in computational physics/chemistry, genetics, applied mathematics, or related fields.
- programming experience with R or python.
- Excellent communication skills and strong team player.
Additional desirable qualifications:
- Experience working with a diverse team on an ambitious project.
Contact the supervisor for more information.