AVR3 is currently inviting expressions of interest from talented and motivated students to join our interdisciplinary research team.
Headquartered at the Queensland University of Technology (QUT), AVR3 is a pioneering research hub dedicated to advancing automated vehicle (AV) technologies specifically tailored for the unique challenges of rural, regional, and remote Australian roads.
AVR3 fosters a collaborative network of experts from multiple academic partners (including QUT, the University of Sydney, UTS, UWA, Deakin, and Swinburne), and industry leaders such as Ford Australia, RACQ, and Seeing Machines, government, and end users.
Our research is organised into four core themes:
Technology
Focuses on engineering challenges such as localisation, navigation, sensing, and digital twin technology for rugged terrains.
Human Interaction
Investigates human factors, driver/operator engagement, community acceptance, and infrastructure adaptation.
Regulation
Addresses policy development, safety assurance.
Business
Workforce transition, and economic modelling for sectors like agriculture, mining, and emergency services.
What We Offer Students
Successful candidates will be part of a world-class research environment that bridges the gap between academia and real-world application. Key benefits include:
Competitive Financial Support
Access to scholarships and funding for travel, data collection, and project-related expenses.
State-of-the-Art Facilities
Opportunities to utilise prototype automated vehicles, new test tracks, and advanced digital twin infrastructure.
Industry Integration
Direct collaboration with industry leaders and government stakeholders, enhancing career prospects and providing real-world experience.
Professional Development
Mentorship from leading experts and the opportunity to showcase findings in high-impact journals and at international conferences.
Qualifications & Skills
We welcome applicants with a strong academic background and a passion for transformative technology. Requirements include:
- Education: An Honours or Master’s degree (or equivalent) in Engineering, Computer Science, Human Factors, Psychology, Data Science, Robotics, or a related Policy/Business discipline.
- Research Skills: Familiarity with empirical research methods, experimental design, or technical modelling relevant to your field.
- English Proficiency: Strong English literacy skills across writing, reading, speaking and listening.
- Preferred: A demonstrated publication record or potential in peer-reviewed conferences or journals is highly advantageous.
How To Apply
PhD recruitment for AVR3 occurs on a rolling basis throughout the year. Interested applicants should submit a cover letter outlining their research interests and motivation, a detailed CV, and academic transcripts to avr3@qut.edu.au
Headquartered at the Queensland University of Technology
ARC Training Centre for Automated Vehicles in Rural and Remote Regions (AVR3)
Connect With Us
Linkedin: AVR3
Email Us
avr3@qut.edu.au
Call Us
0427 537 712
Find Us
QUT, O Block, A Wing, Victoria Park Rd, Kelvin Grove, QLD 4059, Australia.
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