Project Description

A major emerging challenge in wheat breeding is how to stack desirable alleles for disease resistance, drought and heat tolerance, and end-use quality into new varieties with elite high yielding backgrounds in the minimum time. As the number of known desirable alleles for these traits increases every year, the number of possible crossing combinations that need to be considered increases exponentially. We will use evolutionary computing algorithms, widely used for solving highly combinatorial problems, to address this challenge. In a large scale trial with our  project partners we will evaluate the decrease in variety development time that can be achieved with this approach compared to traditional breeding approaches.

The successful applicant will enrol through the Queensland Alliance for Agriculture & Food Innovation (QAAFI).

Preferred educational background

Background in at least one of the following fields would be preferred: quantitative genetics, statistics, plant breeding, animal breeding, human genetics, bioinformatics/computer science

Please contact the Chief Investigator to check on this project's availability.

*The successful candidate must commence by Research Quarter 3, 2020. You should apply at least 3 months prior to the research quarter commencement date. Due to time constraints, only Domestic and on-shore International applicants will be considered.

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Chief Investigator
Professor Ben Hayes