Higher Degree by Research Application Portal

The Yilgarn Craton in Western Australia is one of the world's premier regions for gold mineralisation.  

Using new geophysical and regional geochemical data this project will develop new knowledge of the crust and uppermost mantle of the Yilgarn Craton. Lithospheric structure in the region will be analyzed to identify potential trans-lithospheric structures, and apply extensive quantitative analysis to define how deep-seated faults control gold mineralization.

As the PhD student you will:

1) Apply scale-integrated analysis to regional datasets to identify key structures and build 3D understanding of the lithospheric architecture of the Yilgarn Craton.

2) Apply multi-scale geostatistical approaches to define the spatial relationship of deep-seated structures with gold endowment and to identify measures to support improved exploration targeting.

3) Develop novel network analysis approaches to map the 3D connectivity structure of major fault networks and to define new measures that support improved exploration targeting.

4) Work with the project team and government and industry sponsors to express the findings in the context of developing a holistic understanding of gold mineralization in the Yilgarn Craton

Yilgarn 2030 offers a novel, multi-disciplinary approach to investigate gold mineralising systems across the Eastern Goldfields Superterrane using a scale-integrated (from the lithosphere down to the mineral scale) holistic source-to-sink approach. The generation of pre-competitive data and concepts during this collaborative research project aims at supporting exploration strategies for targeting gold resources.

A/Prof Alan Aitken:  alan.aitken@uwa.edu.au (Project Supervisor)

Dr Quentin Masurel: quentin.masurel@uwa.edu.au (Yilgarn2030 Leader)

The student will have a strong background in Earth Sciences with good exposure to hard-rock geology and quantitative data analysis, ideally including geostatistics and/or machine learning.

The student will be willing to learn new quantitative numerical and spatial analysis methods (implemented in Python, R, Matlab) as required by the project.

For eligible candidates, the project is supported by a full scholarship. The project includes opportunity for a 6 month internship with industry or government sponsors.

The Doctor of Philosophy (PhD) is a program of independent, supervised research that is assessed solely on the basis of a thesis, sometimes including a creative work component, that is examined externally. The work presented for a PhD must be a substantial and original contribution to scholarship, demonstrating mastery of the subject of interest as well as an advance in that field of knowledge. 

Visit the course webpage for full details of this course including admission requirements, course rules and the relevant CRICOS code/s.