In-Demand / machine learning Jobs in Dandenong, Vic

PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning
Monash University —Clayton VIC
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Lead Development Representative - SYDNEY
The Data Foundry —Malvern East VIC
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GPC Asia Pacific (APAC) —Rowville VIC
- Full-time
- Azure
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- Communication skills
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Lecturer/Senior Lecturer in Computational and Applied Mathematics
Monash University —Clayton VIC
- $150,841 - $173,931 a year
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Research Fellow, Data Analyst - Centre of Research Excellence in Bipolar Disorder
Monash University —Clayton VIC
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Deakin University —Burwood VIC
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Kmart —Chadstone VIC
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Quick Apply
Platform Manager (ML)
Coles Group —Hawthorn East VIC
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Research Fellow - Federated & Multimodal Learning
Monash University —Clayton VIC
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Head of Delivery Enablement
Kmart —Chadstone VIC
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Kmart —Chadstone VIC
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Coles Group —Hawthorn East VIC
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Senior Engineer - International Supply Chain Technology (Fixed Term Contract)
Kmart —Chadstone VIC
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Senior Platform Engineer
Coles Group —Hawthorn East VIC
- Full-time
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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning

Monash University -
Clayton VIC

Apply Now

Job Details

Full-time

Qualifications

Bachelor honours degree
Engineering
English
Research
Master's degree
Bachelor's degree
Machine learning
X-ray
AI
Communication skills

Full Job Description

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 ([email protected]), 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 available at www.monash.edu/engineering/future-students/graduate-research/how-to-apply.

Your application will be looked upon favourably if you:

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.

Application Process

To apply for a graduate research degree and/or scholarship at Monash Engineering please follow the following steps:

Check your eligibility, including the PhD entry requirements and Monash's English Language Proficiency requirements.

Contact Dr Yuxiang Wu by email with your CV, academic transcript, and a brief statement outlining your interest in the project.

If your Expression of Interest is supported, you will be supplied with an Invitation to Apply.

After you have received an invitation to apply, submit an application via the online application portal.

Enquiries

For enquiries about the project, please contact Dr Yuxiang Wu at [email protected].

Further enquiries about the scholarship or application process should be directed to the Graduate Research Office at [email protected] or visit www.monash.edu/engineering/future-students/graduate-research.

Applications Close: Wednesday 31 March 2027, 11:55pm AEDT

Supporting a diverse workforce

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/ machine learning jobs in dandenong, vic

PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning

AI / Machine Learning Architect

Senior Machine Learning / ML Engineer

Machine Learning Engineer

Lead Development Representative - SYDNEY

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QA Manager (Fixed Term Contract)

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Platform Manager

AI Business Strategy Lead

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Senior Platform Engineer

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