Shaping the Future of Mobility in Rural and Remote Regions PhD Scholarship

The Queensland University of Technology (QUT) is offering the 'Shaping the Future of Mobility in Rural and Remote Regions' PhD Scholarship, hosted by AVR3—a pioneering research hub advancing automated vehicle (AV) technologies for rural, regional, and remote Australian roads. AVR3 brings together experts from QUT and academic partners including the University of Sydney, UTS, UWA, Deakin, and Swinburne, alongside industry leaders such as Ford Australia, Seeing Machines, RACQ, and government stakeholders. The research environment bridges academia and real-world application, providing state-of-the-art facilities, prototype automated vehicles, new test tracks, and advanced digital twin infrastructure.

Successful candidates will benefit from direct industry integration, professional development opportunities, mentorship from leading experts, and the chance to showcase research in high-impact journals and international conferences. The research themes span technology (localisation, navigation, sensing, digital twin), human interaction (human factors, driver/operator engagement, community acceptance, infrastructure adaptation), regulation (policy development, safety assurance), and business (workforce transition, economic modelling for agriculture, mining, and emergency services).

The scholarship provides a stipend of $41,555 per annum (tax-exempt, indexed annually) for up to 3.5 years, with possible extension (6 months for PhD, 3 months for MPhil). Tuition fees are fully offset for up to 4 years for doctoral studies or 2 years for masters studies. Candidates must meet QUT research degree entry requirements, including English language proficiency, and enrol as full-time internal students unless otherwise approved. Applicants should hold an Honours or Master’s degree (or equivalent) in Engineering, Computer Science, Human Factors, Psychology, Data Science, Robotics, or a related policy/business discipline, and be familiar with empirical research methods, experimental design, or technical modelling. A publication record or potential in peer-reviewed venues is highly advantageous.

To apply, candidates should review available supervisors at AVR3's website, select one aligned with their research interests, and email the proposed supervisor (copying [email protected]) with their academic background, motivation, and CV. If supported, submit an Expression of Interest (EOI) for admission and scholarship consideration, following QUT's guidance. Alternatively, submit an EOI directly to [email protected] with details of the proposed supervisor, research background, cover letter, and CV. Applications close 30 September 2026.