Organisation/Company SWINBURNE UNIVERSITY OF TECHNOLOGY Research Field Computer science Engineering Chemistry Engineering Physics Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Application Deadline 8 Sep 2026 - 00:00 (UTC) Country Australia Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

- Join the Department of Mechanical and Product Design Engineering
- Full-time, 6-months fixed term position at our Hawthorn campus
- Academic Level A salary + 17% super and staff benefits

About the Role

Swinburne University is seeking a highly motivated Research Fellow with a strong research track record in artificial intelligence, machine learning, scientific data engineering and/or computational materials science to join our team and work across disciplines and in close partnership with Laserbond LLC on the Advanced Manufacturing CRC (AMCRC) Project: Development of crack-free Titanium Carbide and Tungsten Carbide-Composite reinforced laser clad coatings.

In this role, you will lead the development of the project’s digital knowledge and modelling infrastructure, which includes integrating SUT and Laserbond’s proprietary experimental and computational datasets with peer-reviewed literature, patents, technical reports and standards; developing a structured HEM knowledge base and evidence-grounded chatbot; creating predictive machine-learning and surrogate models; and integrating these tools with in-house computational tools and generative multi-objective optimisation.

You will have the opportunity to work closely with CIs and industry partners from Laserbond to develop a validated, metal matrix composite cladding with a secure supply chain.

About You

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

- Demonstrated experience developing and evaluating machine-learning, natural-language-processing or large-language-model systems, supported by strong programming capability in Python and relevant frameworks.
- Demonstrated experience with one or more of the following: Retrieval-Augmented Generation, embeddings, vector search, structured outputs, scientific information extraction, document-processing pipelines,



knowledge graphs or domain-specific chatbots.
- Experience designing reproducible research data workflows, including data schemas, databases, metadata, provenance, version control, quality assurance, privacy, security and access management.
- Experience in conducting independent research within a large team of a research group.
- Demonstrated success in publications (or papers in press) in peer reviewed journals and/or high repute international conferences.
- Experience applying AI/ML to materials science, chemistry, metallurgy, manufacturing, engineering or another data-intensive scientific domain is preferred.

Qualifications

- A doctoral degree in artificial intelligence (AI), machine learning (ML), data science, computer science, computational materials science, materials engineering, mechanical engineering or a closely related discipline, with demonstrated application of AI/ML to scientific or engineering problems.

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.

OurAd Astra strategy is the cornerstone of Swinburne’s bold ambition to lead globally in technology-driven education and research. This strategy positions us to create transformative solutions, empower learners, and partner with industry to thrive in an ever-changing world.

What We Offer You!

- Work your way with flexible working arrangements, including hybrid options and generous parental leave to support a balanced lifestyle.
- Exclusive staff discounts, including discounted Medibank health insurance, 50% off Swinburne courses and other partner offers.
- Swinburne offers 17% super and salary packaging options, including car leasing and extra super contributions.

Applications Close: Tuesday,



8 September 2026 at 5:00pm.

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 [email protected]

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 excellent talent. We work to remove barriers related to gender identity, culture, ethnicity, sexual orientation, disability, and age.

Swinburne is proud to be recognised as an AWEI Gold Employer, reflecting our commitment to creating an inclusive workplace where LGBTQIA+ employees, students and communities can thrive.

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, and reasonable adjustments can be requested at any stage of the recruitment process.

For reasonable adjustment requests - including accessible formats of the position description, application form, or other documents, please [email protected] or call+61 3 9214 3550. Please note: this phone number is for disability and reasonable adjustment enquiries only. General enquiries about the role can also be emailed [email protected] .

Victoria’s Commitment to Action: Improving international student employment outcomes.

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

As a Circle Back Initiative Employer, we commit to responding to every applicant.

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