ARC Researcher (A) – AI Agents & Reinforcement Learning

Fixed term - Full-time - Level A - Based in School of Computer and Information Technology (Mawson Lakes) - Full-time (1.0 FTE), 2-year fixed term with a possibility for +1-year extension - Salary Range: $102,024 - $109,307 per annum (plus 17% superannuation)

At Adelaide University, we create the opportunities you need to achieve your ambitions – because when you thrive, we thrive. We are transforming education for contemporary learners and global citizens. Building on a proud legacy and shaped by bold ambition, it's a place of excellence and equity, where our vibrant community of staff are united by our purpose to inspire Australia's future change-makers and create a better tomorrow.

Work that matters

Advance the frontier of AI by developing multi-agent systems capable of reasoning, planning, and autonomous execution. The role requires the ability to produce high-quality peer-reviewed outputs, develop and evaluate innovative AI methods, and contribute to the supervision of research students. Strong communication and collaboration skills are essential, as is the ability to work effectively both independently and within multidisciplinary teams, engaging with academic and industry stakeholders. This role will deliver impactful research outcomes and contribute to real-world applications, including virtual satellite agent systems.

The team

Reporting to the Principal Investigator, this role is part of a leading AI research group specialising in reinforcement learning and intelligent systems. The team is focused on producing world-class research while collaborating with industry to translate innovation into practical solutions. Visit the AU website to learn more about the School of Computer and Information Technology.

Our people

Our people are guided by purpose, curiosity and a commitment to lifelong learning. We embrace authenticity, innovation and collaboration, and harness diverse thinking in our pursuit of excellence. This role is ideal for someone who thrives in a dynamic, research-intensive environment. You will collaborate with academic and industry partners, contributing to innovative projects that bridge cutting-edge theory with real-world deployment. Learn more about our people, what we stand for and what we offer at Careers at AU.

Experience

To join our community and thrive in this role, you will likely have the following skills and experience:

Qualifications

• PhD in Computer Science, AI, Machine Learning or related field

Experience

• Strong track record of publications in top-tier venues (e.g. CORE A)
• Expertise in reinforcement learning, AI agents, and LLM reasoning
• Advanced programming and experimental research skills
• Experience developing, implementing, and evaluating AI methods
• Capability to contribute to supervision of research students

Our commitment to inclusion and diversity

We are committed to fostering a culture of inclusion where diversity is celebrated and everyone feels respected and valued. Adelaide University is an equal opportunity employer, committed to creating a safe, inclusive, and equitable workplace where everyone can thrive. We strongly encourage applications from Aboriginal and Torres Strait Islander peoples, people with disability, and people of all ages, genders, cultural backgrounds, sexual orientations, and gender identities. We are committed to supporting flexible working arrangements and providing reasonable adjustments throughout the recruitment process.

Launch your future with Adelaide University now

Applying is simple. Simply click on the Apply Now button and upload:

• your current CV
• a cover letter that tells us why you're excited about the role

The online application form will list the specific selection criteria that you need to address. Please note that the role description is not attached to this advertisement as it is currently being finalised.

Submit your application by 11.30pm Monday 20 April 2026

The University reserves the right to close this advertisement before the closing date if a suitable candidate is identified.

For further information about this opportunity, please contact (quoting reference number 492761):

Simone Patterson
Talent Acquisition Adviser
+6* * *** ****|c***@***********