Research Associate in Machine Learning

Advance the theoretical foundations of machine learning, publish in premier venues and help shape the next generation of AI research.

· Annual salary package: $104,481 (ACA Level A.4) - $112,550 (ACA Level A.6/ PhD awarded rate) plus 17% superannuation & annual leave loading
· Full-time, fixed term appointment until end of July 2027
· Macquarie University, Wallumattagal Campus, North Ryde

Machine learning is moving beyond centralised data and single models. Deep variational and decentralised learning sit at the frontier of this shift, and the theory that underpins them is still being written. This is an opportunity to help write it.

The Role

We seek a highly motivated and competitive research associate to work on foundational research in deep variational and decentralized learning. This role gives you unique opportunities to

• Explore deep variational and decentralized machine learning theories
• Develop theoretical foundations and publish results in competitive venues
• Work with a competitive team with wide global representativeness

Under the supervision of the project leader, you will contribute to a focused program of foundational AI research. Key responsibilities include, but are not limited to:

• Develop fundamental models for deep variational and decentralized learning.
• Conduct relevant modelling, analytical and visualization tasks.
• Publish the findings in top-tier events.

About Us

We are a group of highly active, dynamic and productive research team based in the AI Lab in the School of Computing and the Frontier AI Research Centre at Macquarie University. The team is committed to high-profile research activities relating to major grants, industry engagement, and international collaboration. The team consists of hierarchical diverse profiles of stakeholders from senior leaders to active academic staff, HDR students, postdoctoral researchers, to visitors.

About You

You are an experienced researcher with relevant qualification in the areas relating to AI, data science, and machine learning; demonstrated experience in coordinating a research team and assisting research leaders and academic staff; demonstrated outcomes in applied statistics, advanced analytics, machine learning, optimization methods, information theory, visualization, etc. areas through contributing to research projects; skills and satisfactory results in communicating with broad stakeholders including intensive publication experience.

Selection Criteria

• Master by Research or higher level of qualifications in the areas of AI, data science, machine learning, or relevant areas,
• Demonstrated research expertise in areas including applied statistics, machine/deep learning, information theory, visualization, and data analytics,
• Evidence of research outputs such as a strong track record in continuously publishing at top-tier venues as the main contributor, and an
• Ability to collaborate with relevant teams, partners, participants or stakeholders.

Role Specific Requirements

The successful candidate must be able to work within any applicable project confidentiality, contracting and security requirements.

The successful candidate will be required to undergo a National Police/ Criminal History Check and a qualification check. An international police/ criminal history check may also be required, depending on the candidate's circumstances.

*** Appointment will also be subject to compliance with applicable Defence-related legislation and project security requirements, including Defence Export Controls and Safeguarding Australia’s Military Secrets legislation where relevant.

How to Apply

To be considered, please apply online with your CV and a cover letter outlining how your experience meets the selection criteria above.

Applications close: Wednesday 14 Oct 2026 at 11:59 p.m. (AEST)

Role Enquiries: For further information about the role, please contact Prof Longbing Cao at [email protected].

Note: Candidates must be onshore and have valid Australian work rights for the duration of the appointment.

*** We reserve the right to progress or decline applications prior to the application closing date.

The Faculty of Science and Engineering at Macquarie University aims to increase the engagement of women, Aboriginal and Torres Strait Islander peoples, and people from diverse backgrounds in STEMM roles. Applications are considered holistically, and candidates are encouraged to apply even if their experience does not meet each individual selection criterion.

Pre-Employment Checks

Macquarie University cultivates a workplace defined by safety, ethical conduct, and strong integrity. Prior to completion of an offer of employment, preferred candidates will be required to participate in a combination of pre-employment checks relevant to the role they have applied for.

Your employment is conditional upon the completion and maintenance of all role-required pre-employment or background checks in terms satisfactory to the University.

Why Join Us?

We rank amongst the top employers in the Australian Workplace Employers Index. Explore the fantastic benefits available to you when you become part of the team at Macquarie University.

Our prime location is just a short walk from Macquarie University Metro Station and Macquarie Shopping Centre. Enjoy the benefits of working at a campus that offers:

• 17% Superannuation
• Subsidised onsite parking options
• Flexible working options
• Training and professional development
• Onsite childcare facilities
• Discounted health insurance (Medibank)
• Onsite vacation care
• Employee Assistance Program
• Subsidised membership at the Sport & Aquatic Centre
• Onsite GP, imaging & physio clinics

If you're already part of the Macquarie Group (MQ University, U@MQ, MQ Health, MGSM), you'll need to apply through your employee Workday account. To apply for this job: Login to Workday and go to the Careers App > Find Jobs.

Applications Close:

14/10/2026 11:59 PM

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A Place Where You Belong
At Macquarie, we believe diversity makes us stronger, inclusion drives our success, and belonging inspires us to do our best work. We are proud to foster a community where different backgrounds, identities, and experiences are valued, and where our people are empowered to thrive through supportive leadership, shared responsibility, and a deep commitment to genuine care and respect for our community. Find out more about our vision for a truly inclusive workplace in our Diversity, Inclusion and Belonging Framework.