The National Tree Genomics Project (Western Sydney University, University of Adelaide, University of Queensland, Queensland University of Technology, Queensland Department of Agriculture and Fisheries QDAF, Jain Irrigation in India) is integrating new genomic, physiology, and molecular biology approaches for key model species (avocado, almonds, citrus, macadamia, mango) to breed the next generation of fruit and nut trees. To complement our team, we are seeking to support exceptional PhD students to lead projects within our portfolio.
The first project will use comparative genomic analysis of assembled genomes, in the context of our molecular breeding program, to determine what gene set makes a ’good’ fruit tree crop, developing new approaches for analysing (allelic) gene expression x genotype interactions, or investigating how environments can influence the development of complex tree traits.
The second project will use cutting-edge machine learning approaches to discover how complex biological traits evolve, develop, and respond to a changing environment. The aim is to generate fundamental knowledge on fruit tree development (such as flowering, branching, pathogen and drought resistance) by integrating diverse data types (genetic, physiological, ecological) in a mathematical framework of the student's design.
For both projects, the student will be mainly based at Western Sydney and co-supervised by the Hawkesbury Institute for the Environment, Centre for Research Mathematics (Western Sydney University) and University of Queensland (Brisbane).
It is a two stage application starting with a short EOI, deadline 12th of April.
You can find more details here:
Machine learning and computer science: