About This Opportunity

Join us as a Postdoctoral Research Fellow/Research Officer and contribute to cutting-edge research on AI preparedness and the evaluation of AI deployments across public and private sectors. You’ll develop frameworks to assess organisational and data barriers to AI adoption, evaluate implementation outcomes, and analyse the impact of emerging AI policies, standards, and governance guidelines.

This role is mainly based at the ARC Industrial Transformation Training Centre for Information Resilience (CIRES) at The University of Queensland, working closely with leading experts and industry partners. You’ll be supported by senior academics with opportunities for increasing autonomy over time.

Key responsibilities will include:

Research:

• Lead and execute high-quality, independent research projects related to AI preparedness, and evaluation with a particular focus on standards, assurance, risk management, and compliance.
• Collaborate with industry and government professionals to ensure the practical relevance of developed approaches and validate their performance.
• Participate in regular meetings to discuss project objectives, progress and outcomes.
• Disseminate research findings through high-quality publications in top-tier journals and conferences in the fields of information systems, data management and artificial intelligence.
• Create practical research translation artefacts and training for wider adoption in industry and government
• Participate in the development of open-source tools and frameworks to support the wider research community.
• Contribute to the preparation and submission of research grant proposals to secure future funding.

Supervision and Researcher Development:

Supervise Honours and Higher Degree by Research students (as appropriate), supervise and manage researcher development, provide performance feedback and training, resolve conflicts, and ensure correct remuneration and benefits.

Citizenship and Service:

Develop partnerships, demonstrate leadership through mentoring, engage in internal service roles and committees, perform administrative functions, provide support to colleagues, and uphold university values.

This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic Performance.

About You

• Completion or near completion of a PhD in Computer Science, Data Science, Information Systems or a related field.
• Demonstrated expertise in empirical methods, proficiency in data analysis, and deep knowledge of contemporary AI tools and techniques
• Experience in conducting research projects, demonstrating high-level written and oral communication skills.
• Peer-reviewed publications in high-impact journals or premiere conferences.
• Ability to work both independently and as a member of a cross-disciplinary research team.

The successful candidate may be required to complete a number of pre-employment checks, including: right to work in Australia, education check.

You must maintain unrestricted work rights in Australia for the duration of this appointment to apply. Employer sponsored work rights are not available for this appointment.

Questions?

For more information about this opportunity, please contact Professor Shazia Sadiq s.sadiq@uq.edu.au and Professor Marta Indulska m.indulska@uq.edu.au.

For application inquiries, please reach out to the Talent Acquisition team at talent@uq.edu.au, stating the job reference number (below) in the subject line.

Want to Apply?

We welcome applications from all individuals and are committed to an inclusive and accessible recruitment process. To be considered, please ensure you upload:

• Resume
• Cover letter responding to the ‘About You’ section

Other Information

UQ is committed to a fair, equitable and inclusive selection process, which recognises that some applicants may face additional barriers and challenges which have impacted and/or continue to impact their career trajectory. Candidates who don’t meet all criteria are encouraged to apply and demonstrate their potential. The selection panel considers both potential and performance relative to opportunities when assessing suitability for the role.

Applications close Sunday 1 February 2026 at 11:00 pm AEST (R-59030). Please note that interviews have been tentatively scheduled for mid February.