"Postdoctoral Research Fellow - Numerical and Mathematical Optimisation"

• School of Mathematics and Physics
• Full-time fixed-term position for up to 2 years
• Base salary will be in the range $83,698.91 - $111,431.10 + 17% Superannuation (Academic Level A)
• Based at our picturesque St Lucia Campus

About This Opportunity

We are seeking a Postdoctoral Research Fellow to join an exciting research project at the intersection of mathematical optimisation, numerical linear algebra, and machine learning/artificial intelligence. This project focuses on the development of novel theoretical frameworks alongside cutting-edge computational techniques for large-scale optimisation problems, with direct relevance to modern machine learning and AI applications.

This role offers an outstanding opportunity for an early-career researcher to build depth and independence in mathematical and numerical optimisation, while contributing to a high-impact, internationally collaborative research program.

Key responsibilities will include:

• Research: Develop an emerging research program in mathematical optimisation and computational mathematics, collaborate on joint research projects, contribute to applications for competitive research funding, publish in high-quality journals and present at leading conferences, apply best-practice research methodologies, and contribute to knowledge translation and research discussions within the project team.
• Supervision and Researcher Development: Contribute to the supervision of Honours and Higher Degree by Research students, provide guidance and mentoring to support researcher development, assist with the effective management of research support staff as appropriate, provide constructive feedback, and support a positive and inclusive research environment.
• Citizenship and Service: Demonstrate behaviours aligned with UQ values, actively participate in internal service roles and administrative activities, contribute to committees and decision-making processes, collaborate effectively within the School and broader University, support colleagues as required, and begin to develop external relationships with academic, industry, and government partners.

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 applied or computational mathematics, computer science, or a related discipline.
• An emerging profile in research areas related to the project such as optimisation, numerical linear algebra, machine learning and artificial intelligence, numerical analysis, and computational mathematics.
• Evidence of publications in high-quality journals and presentations at leading conferences in relevant fields.
• Some experience in meaningful internal service roles and contributions towards external activities

Appointment to this role is subject to the successful completion of relevant pre-employment checks, which may include verification of the right to work in Australia and qualifications. This may also include checks relating to gender-based violence matters or other integrity and conduct requirements.

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 Fred Roosta at fred.roosta@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 (2 pages max)
• Cover letter addressing the ‘About You’ section
• Research Statement (2 pages max)

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 16 February 2026 at 11.00pm AEST (R-60373).