We are seeking two highly motivated PhD candidates for a fully funded interdisciplinary research cohort spanning the Faculty of Information Technology, the Faculty of Engineering, and industry partner NVIDIA.
Supported by the Monash AI Institute, the cohort will bring together academic and industry expertise to advance intelligent, adaptive, distributed AI and edge intelligence for autonomous robots.
The supervisory team includes Mohammad Goudarzi, Hamid Rezatofighi, Dana Kulić, and Trung Pham.
PhD project 1: Context-aware AI optimisation within autonomous robots
This project will develop efficient machine-learning and neuro-symbolic methods that enable robots to adapt their capabilities in response to contextual information and mission conditions.
PhD project 2: Distributed orchestration across robots, coordinators, and robot teams
This project will develop orchestration methods for coordinating AI execution within individual robots, between robots and a central orchestrator, and across teams of robots.
Funding package
- Annual stipend of approximately AUD 37,000 per year, indexed annually.
- Tuition-fee waiver for international students.
- Travel support for conferences and workshops.
- Full health insurance.
- Close collaboration with industry and academic supervisors.
- Access to cutting-edge research, mentoring, and collaborative opportunities.
Eligibility
- Domestic and international students are welcome to apply, subject to meeting the Monash PhD admission criteria.
- A strong academic background in AI/ML, robotics, distributed systems, systems for AI/ML, or a related area.
- At least one relevant publication in a top-ranked conference or journal, such as a CORE A/A* or CCF Rank A venue.
- Selected candidates will be invited to interview.
How to apply
- Complete the online application form.
- Email mohammad.goudarzi@monash.edu with the subject line “Prospective PhD Applicant - DistRobot - <Your Name>” and attach:
- your CV, including educational background, the WAM or equivalent result for each degree, and research outputs;
- copies of your academic transcripts.
After applications are reviewed, shortlisted candidates will be contacted to begin the interview process.