Prediction of complex traits in human populations

This Earmarked Scholarship project is aligned with a recently awarded Category 1 research grant. It offers you the opportunity to work with leading researchers and contribute to large projects of national significance.

Supervisor – Professor Naomi Wraynaomi.wray@uq.edu.au

Complex traits in humans, including quantitative traits such as height and diseases such as diabetes, are determined by genetic and environmental factors. Accurate assessment of the genetic and environmental contributors to a trait is therefore key to realising the potential of genomic information and its application in personalised medicine.  For example, accurate assessment of genetic risk to heart disease could identify candidates for increased or early screening programs.  The aim of this project is to develop and evaluate novel methods for polygenic risk prediction, including the use of haplotypes and family information.  The project will use data from large publically available sources, such as the UKBiobank.

The candidate will conduct their research as part of the Program in Complex Trait Genomics (PCTG).  This research group is based at the Institute for Molecular Bioscience, at the St Lucia campus of the University of Queensland.  The group is lead by Profs Naomi Wray, Peter Visscher and Jian Yang who are leaders in field of quantitative genetics and authors of many highly cited papers.  The candidate will have the opportunity to join a vibrant group of over 50 researchers with expertise in quantitative genetics, statistics, computer programming and population genetics.

Preferred educational background

Applications will be judged on a competitive basis taking into account the applicant's previous academic record, publication record, honours and awards, and employment history.

A working knowledge of quantitative/population genetics, statistics, mathematics and other quantitative fields would be of benefit to someone working on this project.

A background or knowledge of programming (R, C/C++) and prior experience in analysing genetic data (e.g. GWAS) is highly desirable.

*The successful candidate must commence by Research Quarter 4, 2022. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons.

Apply now