PhD Scholarship - ARC Industrial Transformation Research Hub for Future Digital Manufacturing

Full job description
AI & Digital Twins for Advanced Digital Manufacturing
Full-time, fixed-term position at our Hawthorn campus
Stipend Rate - $40,00 per annum for 3 years


About the Role
Swinburne University of Technology is leading the new ARC Industrial Transformation Research Hub for Future Digital Manufacturing (DMH), a five-year initiative funded by the Australian Research Council. In collaboration with partner universities and industry leaders, the Hub aims to advance manufacturing productivity, resilience, and global competitiveness through innovative digital solutions powered by Digital Twins, Artificial Intelligence, and Open Digital Manufacturing Platforms.

We are seeking a talented and motivated PhD candidate to join this exciting initiative. The project, in partnership with Krueger Transport Equipment Pty Ltd—a leader in truck trailer manufacturing—will focus on developing AI and Digital Twin technologies to assess welding consistency and quality. The research will contribute to smarter, data-driven manufacturing practices with real-world industry application.

This full PhD scholarship is based at Swinburne’s School of Science, Computing and Engineering Technologies in Melbourne. The successful candidate will work within a dynamic, multidisciplinary research environment, with access to state-of-the-art facilities and direct industry engagement.

About You
To be suitable for this role you will need to have experience in the below key accountabilities:

Comfortable working both independently and as part of a team, and enjoy collaborating with others.
Strong problem-solving and organizational skills, with the ability to stay on top of tasks and meet deadlines.
Confident writer with solid verbal communication skills, and experienced in working with external research partners to get great outcomes.
Good knowledge and hands-on experience with AI and computer vision.
Solid programming skills in Python, especially with PyTorch.
Practical experience with deep learning projects, including working with attention mechanisms and transformer models.


Qualifications
Bachelor’s degree with First Class Honours (or equivalent) and/or a research master’s degree in computer science, AI or Computer Vision; or an equivalent combination of professional experience and academic qualifications in IT, Engineering, AI/ML, or related disciplines.
Meet the entry requirements for the relevant Higher Degree by Research at Swinburne University of Technology.


About Swinburne University of Technology
Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and different university – one that is truly of Technology, of Innovation and of Entrepreneurship. We are committed to a differentiated university proposition in education and research.

To Apply
Please include all the following documents:
Curriculum vitae indicating qualifications and experience, including publications (if any).
A cover letter addressing your suitability and research interests.
Academic transcripts (note: these must be certified if you progress to the next stage).

Please note that only shortlisted candidates will be contacted. Shortlisted applicants will be invited to attend an interview and will be required to provide referee reports.

The selected candidate must apply for and successfully enroll in a Higher Degree by Research (HDR) candidature at Swinburne University to receive the scholarship.

If you are viewing this advert from an external site, please click ‘apply’ and you will be redirected to Swinburne’s Jobs website to access the Position Description at the bottom of the page.

Please Note: Appointment to this position is subject to passing a Working with Children Check.

If you are experiencing technical difficulties with your application, please contact the Swinburne Talent Acquisition Team on talentacquisition@swin.edu.au

Applications Close: Tuesday 15 July 2025, at 11.00pm (AEST)

Swinburne offers flexible working options contained in our leave and parenting/carer policies to support work-life balance.

Diversity, Equity and Inclusion
Swinburne has become a world-class university, driving social and economic impacts through science, technology, and innovation. As a dual-sector university, our vision is for people and technology working together to build a better world.

Central to our vision is our commitment to diversity, equity, and inclusion. We pride ourselves on being an equal opportunity employer focused on attracting, retaining, and developing great talent. We work to remove barriers related to gender identity, culture, ethnicity, ****** orientation, disability, and age.

We strongly encourage applicants from diverse Aboriginal and Torres Strait Islander communities. Our Moondani Toombadool Centre leads our Indigenous education and culture at Swinburne, guided by community wisdom and leadership.

We support applicants with disabilities. Adjustments can be requested at any time during the recruitment process. For Reasonable Adjustment requests, including accessible formats for the PD, application form or any other document, please contact DCR@swin.edu.au or call +61 3 +214 3550.

Please note the above number and DCR email address are for disability or reasonable adjustments queries only. General enquiries about the role can be sent to talentacquisition@swin.edu.au (general enquiries will not be answered by phone).

Victoria’s Commitment to Action: Improving international student employment outcomes.
As a signatory to Victoria’s Commitment to Action, Swinburne seeks to remove barriers to international graduate employment. We welcome and encourage applications from international graduates.
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