Job No.: 693787
Location: Clayton campus
Employment Type: Full-time
Graduate Research Degree: 3291 - Doctor of Philosophy (PhD)
Hiring: July 2026
Duration: 3.5-year fixed-term appointment
Remuneration: AUD 37,500 per annum (tax‐free stipend) (2025 rate)
Scholarship status: A scholarship opportunity may be available for this project.
Monash Engineering is a leading global centre for research consistently placing highly in international ranking lists. We engage with industry and other world‐leading institutes to carry out pioneering research that benefits society and changes the world around us. Our world‐class researchers are driven by a passion and commitment to leaving a more sustainable legacy for future generations.
We are committed to training the next generation of research leaders through our graduate research degrees. Our students have the opportunity to make an impact and solve real‐world issues in a stimulating, supportive environment with access to cutting‐edge facilities.
The Opportunity
Expressions of interest are sought from outstanding candidates for PhD study in the Department of Materials Science and Engineering within the Faculty of Engineering.
Project title:
Processing intelligence for green metals using in situ X‐ray characterisation and machine learning.
We are seeking a PhD candidate to develop advanced in situ X‐ray characterisation and machine‐learning‐enabled processing intelligence for green metals transformation. The project will focus on capturing time‐resolved structural and chemical changes during minerals‐to‐metals processing, including aqueous, electrochemical, thermal, and hybrid pathways relevant to extraction, refining, recycling, phase transformation, impurity evolution, and microstructure development.
The candidate will use advanced in situ X‐ray methods, including diffraction, scattering, spectroscopy, imaging, and complementary multimodal characterisation, to generate data‐rich descriptions of evolving materials and processing pathways. A central aim is to couple these experiments with machine learning, mechanistic modelling, and automated data analysis to extract processing‐structure‐property relationships and support predictive process optimisation.
The project sits within Monash's broader ambition to build physical‐digital capability for infrastructure platforms in minerals‐to‐green metals transformation. It will suit a candidate interested in combining experimental materials science, advanced characterisation, and data‐driven modelling to develop new forms of processing intelligence for low‐emission metals production and recycling.
The candidate will be supervised by Dr Yuxiang Wu (), with collaborators across materials engineering, X‐ray science, and artificial intelligence.
Project Details
* Start: July 2026
* Graduate research degree: Doctor of Philosophy (PhD)
* Location: Clayton campus
* Department: Materials Science and Engineering
* A scholarship opportunity may be available for this project.
Preferred Background
* Materials Science, Metallurgical Engineering, Mechanical Engineering, Physics, Chemical Engineering, Data Science, or related disciplines.
* Strong interest in phase transformations, process chemistry, materials processing, and advanced X‐ray characterisation.
* Experience or enthusiasm for machine learning, scientific computing, automated data analysis, or computational modelling.
Candidate Requirements
Applicants will be considered provided they fulfil the criteria for PhD admission at Monash University. Details of the relevant requirements are /engineering/future-students/graduate-research/how-to-apply.
Ability to Qualify
Applicants will be assessed based on the following criteria:
* Graduated in the top 10% of your year level.
* Graduated from a well‐ranked university.
* Have authored peer‐reviewed research publications.
* Possess excellent written and verbal English skills.
Note: applicants who already hold a PhD degree will not be considered.
Applicants must show excellent communication and interpersonal skills, and the ability to conduct self‐motivated research. They should have either completed, or be in the process of completing, a Bachelors H1 Honours Degree or already hold an H1E Bachelors and/or Masters degree. Candidates who are in the process of completing their H1 degree will be considered.
Enquiries
For enquiries about the project, please contact Dr Yuxiang Wu at .
Further enquiries about the scholarship or application process should be directed to the Graduate Research Office at or visit www.monash.edu/engineering/future-students/graduate-research.
Applications Close: Wednesday 31 March 2027, 11:55pm AEDT
Supporting a diverse workforce
#J-18808-Ljbffr