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MONASH UNIVERSITY

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PhD in Machine Learning for In Situ Materials Characterisation Monash University in Australia

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded PhD scholarship available for an outstanding domestic or international candidate; remuneration is AUD 41,100 per annum tax-free stipend (2027 rate).

Deadline

Apr 30, 2027

Country flag

Country

Australia

University

MONASH UNIVERSITY

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Keywords

Computer Science
Mechanical Engineering
Chemical Engineering
Materials Science
Computer Vision
Metallurgy
X-ray Diffraction
Material Characterization
Transmission Electron Microscopy
Physics
ML

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About this position

This PhD project at Monash University focuses on developing machine learning methods for in situ materials characterisation. The student will work on modern experimental datasets that capture microstructure, crystallography, phase evolution, chemistry, and morphology, with the aim of learning physically meaningful representations that help explain how materials evolve during processing and phase transformation.

The project is based in the Department of Materials Science and Engineering within the Faculty of Engineering at Monash’s Clayton campus. Research activities will draw on data from techniques such as electron microscopy, EBSD, X-ray diffraction, X-ray imaging, and in situ characterisation. Depending on the student’s background and direction, the work may involve computer vision, representation learning, graph neural networks, multimodal learning, and scientific machine learning.

The research has a strong materials engineering focus, with applications primarily in metals, phase transformations, and materials processing, including emerging low-emission metallurgical processes. The project aims to build quantitative links between processing, material evolution, microstructure, and properties, placing machine learning directly at the interface of experimental materials science and computational analysis.

The candidate will be supervised by Dr Yuxiang Wu in a multidisciplinary environment spanning materials science, advanced characterisation, computational modelling, and artificial intelligence.

Funding details

Fully funded PhD scholarship available for an outstanding domestic or international candidate; remuneration is AUD 41,100 per annum tax-free stipend (2027 rate).

What's required

Applicants must meet the PhD admission criteria at Monash University, including Monash's English language proficiency requirements. Preferred applicants are those who graduated in the top 10% of their year level, graduated from a well ranked university, and have authored peer-reviewed research publications. Strong written and verbal English skills are required, and applicants must demonstrate strong quantitative and problem-solving skills, excellent communication and teamwork skills, and the capacity for self-motivated research. A background in materials science, metallurgical engineering, mechanical engineering, physics, computer science, data science, chemical engineering, or a related discipline is preferred, along with interest in machine learning, materials characterisation, or computational materials science. Experience with machine learning, computer vision, graph neural networks, Python, SEM/EBSD, XRD, image analysis, microstructure characterisation, or materials modelling is desirable. Applicants who already hold a PhD are not eligible.

How to apply

Check your eligibility, including PhD entry and English language requirements. Email Dr Yuxiang Wu with your CV, academic transcript, and a brief statement of interest. Then submit a full application through My.App and list Dr Yuxiang Wu as your preferred supervisor.

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