Postdoctoral Research Fellow/Research Fellow – Intelligent Traffic Analysis & Simulation
SWINBURNE UNIVERSITY OF TECHNOLOGY, Australia
- Institution
- SWINBURNE UNIVERSITY OF TECHNOLOGY
- Country
- Australia
- Position type
- Postdoc
- Subject area
- Computer Science & AI
- Application deadline
- 17 September 2026
- Hours
- Full Time, Part Time
- Location
- Boroondara, Victoria, AU
- Funding
- Fully funded position
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About this position
- Shape the future of intelligent transport and incident management
- Part or full-time (0.8 – 1.0) until 17 Dec 2026 at our Hawthorn campus
- Academic Level A.6 – B.1 salary + 17% super and staff benefits
About the Role
Join Swinburne University of Technology’s Intelligent Data Analytics Lab and contribute to an ARC-funded project developing innovative, data-driven solutions for managing incidents across complex, multi-modal transport networks.
Working within the Department of Computing Technologies, you’ll undertake original research spanning machine learning, data analytics, optimisation, spatial data management and traffic simulation. You’ll develop advanced simulation and impact analysis techniques, alongside optimisation approaches to identify effective incident response strategies under dynamic traffic conditions.
You’ll collaborate with researchers across disciplines and external academic, government and industry partners, while contributing to the implementation and evaluation of a proof-of-concept system.
At Level B, you may also contribute to the supervision and development of higher degree research students, honours research students and capstone projects.
About You
You’ll have expertise in areas such as data analytics, simulation modelling, machine learning, AI, spatial data management or optimisation.
You’ll also bring:
- A strong publication record in top-tier journals and/or conferences in areas such as machine learning, data mining, optimisation, traffic simulation modelling, transport data analysis, intelligent transport systems, spatial data management and algorithm design. This is essential for appointment at Level B and preferred at Level A.
- Hands-on experience applying machine learning, data mining and/or optimisation techniques to real-world data analysis problems.
- Experience working collaboratively across academic, government and/or industry environments.
- Strong analytical, organisational and communication skills, with the ability to work independently and as part of a multidisciplinary team.
Desirable for both Level A and Level B:
- Experience building spatial data management systems, HCI systems and/or working with traffic simulation modelling platforms.
- Knowledge and skills in spatial data management, traffic simulation modelling, transport data analysis, machine learning and/or optimisation.
Qualifications
You’ll have a PhD in Computer Science, Computer Engineering or a related discipline. A PhD is essential for appointment at Level B and preferred for Level A.
To Apply
Please submit your CV and cover letter addressing the Key Selection Criteria and your suitability for this position.
To review the Position Description and to apply, please scroll down to the bottom of the page.
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 Talent Acquisition team at talentacquisition@swin.edu.au
Applications Close: Thursday 17 September 2026, at 11.00pm
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, 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 contact talentacquisition@swin.edu.au 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 to talentacquisition@swin.edu.au.
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.
As a Circle Back Initiative Employer, we commit to responding to every applicant.
Please click here for Position Description - Level B
Please click here for Position Description - Level A
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