"Research Fellow - Control of Multiagent Systems"

Shape the future of intelligent control systems

We are seeking a talented and motivated Research Fellow to join a high-impact research team advancing the theory and application of learning, control and optimisation in multiagent and complex networked systems.

This is an exciting opportunity for an early-career or emerging researcher to contribute to cutting-edge work in:

• Multiagent systems and distributed control
• Learning and optimisation
• Variable structure and sliding mode control
• Smart power and energy system applications

Working alongside leading academics and industry collaborators, you will help deliver innovative solutions with real-world impact across energy, automation and intelligent systems.

About the Role

You will design and lead high-quality research projects aligned with the School and University research strategy, while building strong national and international collaborations.

Key responsibilities include:

• Conducting independent and collaborative research in learning, control and optimisation of multiagent systems
• Publishing in leading journals and top-tier conferences
• Developing competitive research funding proposals (including Category 1 grants)
• Collaborating with industry and academic partners
• Co-supervising postgraduate research students
• Contributing to project delivery, dissemination and research leadership within the team

To be successful in this position, you'll have:

• Demonstrated research track record in learning, control and optimisation of multiagent systems.
• Publications in top-tier conferences and journals relevant to the above fields.
• Demonstrate ability to clearly communicate research results, concepts and knowledge.
• Demonstrated initiative in research and problem solving.
• Demonstrated ability to work effectively both as a member of a research team and independently when required, to meet project outcomes and milestones.

Qualifications

Mandatory: PhD or equivalent in electrical and electronic engineering and/or applied mathematics, in particular, in one or more areas of learning, control and optimisation of multiagent systems. Experiences in dealing with complex networks and/or variable structure systems and/or sliding mode control and applications would be desirable.

Eligibility requirement: Australian Citizen or Permanent Resident.

Please Note: Appointment to this position is subject to passing a Working with Children and National Police Check.

Position details:

• Full-time, Fixed Term position for 12 months (extension subject to available funding)
• Salary Academic Level B ($115,303 - $136,925 p.a.) + 17% Superannuation and Flexible Working Arrangements
• Based at the Melbourne CBD campus, but may be required to work and/or be based at other campuses of the University

About the School of Engineering

The School of Engineering comprises a diverse range of disciplines: Aerospace Engineering & Aviation; Chemical & Environmental Engineering; Civil & Infrastructure Engineering; Electrical & Electronic Engineering, Biomedical Engineering; Manufacturing, Materials & Mechatronic Engineering; Mechanical & Automotive Engineering.

As a top 100 university in the world for engineering (2015 QS Rankings by Faculty; Engineering and Technology), RMIT Engineering provides students with work-relevant education programs, access to excellent research facilities and opportunities to engage in creative real-world project work through robust relations with local and international industry leaders.

RMIT Engineering's education is based on innovation and creativity. Key discipline areas in the School of Engineering provide programs with flexible pathways to global careers or postgraduate research.

Details relating to the School/College Office may be found on at: www.rmit.edu.au/stem-college

To Apply

Please click the 'Apply' link below and upload the following documents:

• Your CV
• A cover letter
• A separate document addressing the Key Selection Criteria

For further information about this position, please see the Position Description hyperlinked below or contact Distinguished Professor Xinghuo Yu via email xinghuo.yu@rmit.edu.au

For further information regarding recruitment processes, please contact Jennifer Pham, Senior Talent Acquisition Advisor via email at jennifer.pham2@rmit.edu.au Please do not share your application to this email address.

Position Description - Research Fellow - Control of Multiagent Systems

Please note, if you are viewing this advert from an external site, please click 'apply' and you will be redirected to RMIT's Jobs website to access the Position Description at the bottom of the page. Due to recent upgrades, position description links may not work on LinkedIn advertisements.

Applications close on Sunday 8 March 2026 at 11.59pm.