Research Associate in Machine Learning

mq; Sydney; On-site; AUD 104,000 - 113,000; Full time

Benefits offered by this job

Superannuation 17%

Annual leave loading

Job summary

Macquarie University invites applications for a full-time, fixed-term appointment in machine learning research at the AI Lab, North Ryde. The role focuses on deep variational and decentralized learning, with opportunities to develop theory and publish results.

You will join a diverse, globally represented team, contribute to foundational models, conduct modelling and visualization tasks, and present findings at top-tier venues.

Qualifications

• Master by Research or higher in AI, data science, machine learning or related field.
• Demonstrated ability to publish research outcomes in top-tier venues.
• Experience coordinating a research team and supporting academic staff.

Responsibilities

• Explore deep variational and decentralized learning theories.
• Develop theoretical foundations and publish results in competitive venues.
• Collaborate with a globally representative, competitive research team.

Skills

Deep variational learning

Decentralized learning

Machine learning research

Data science

Education

Master by Research or higher in AI/Data Science/ML

Job description

Annual Salary & Benefits

Annual salary package: $104,481 (ACA Level A.4) - $112,550 (ACA Level A.6/ PhD awarded rate) plus 17% superannuation & annual leave loading

Contract & Location

Full-time, fixed term appointment until end of July 2027

Macquarie University, Wallumattagal Campus, North Ryde

Role Overview

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

• 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

Key Responsibilities

• 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

The Faculty of Science and Engineering is a community of discovery, dedicated to developing the next generation of science and technology innovators. Within the Faculty, the School of Computing brings together researchers, educators and students working across artificial intelligence, data science, cyber security, software engineering and information systems.

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.

Background Checks

• 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.

Applications

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 [e-mail] .

Eligibility

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.

Equity and Inclusion

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