Lecturer in Mathematics/Quantitative Science

• Diverse, supportive, and family-friendly work environment
• Base salary will be in the range of AUD$119,462 - $141,545 + 17% super (Academic Level B).
• Based at our St Lucia location 

About this opportunity

The School of Mathematics and Physics and the Faculty of Science are committed to ensuring that our graduates are equipped to succeed in a rapidly changing, highly technological world. The ability to think critically and solve problems, as well as to apply sophisticated quantitative reasoning and appropriate computer programming techniques, are fundamental skills for 21st century science graduates. Within science programs at UQ, the foundations for these skills are developed through two courses SCIE1000/1100 “Theory and Practice in Science” and STAT1201/1301 “Analysis of Scientific Data”.

This is an exciting opportunity for a teaching-focused Lecturer to grow their teaching impact through leadership in embedding a technical background of generative AI and machine learning into Science and Mathematics programs at UQ. The appointee will also be expected to:

• Teach and coordinate courses;
• Engage in research and/or other appropriate activities, for example in the Scholarship of Teaching and Learning or a discipline appropriate to their background;
• Supervise research projects for both undergraduate and postgraduate students;
• Perform administrative and other activities associated with the School, Faculty and wider university.

In the longer term, the appointee will expand their teaching activities, help determine the long-term strategic direction of mathematics and statistics education at UQ, and develop a broader leadership role in the scholarship of teaching and learning. They will innovate and contribute to the continued development and improvement of a variety of teaching programs across the School, Faculty and wider university. 

About You

Applicants should possess a PhD or equivalent in mathematics, statistics, or a closely related field. Additionally, you will demonstrate the following four criteria:

• Evidence of high-quality university teaching across a variety of settings, such as small and large groups, and preferably including course coordination responsibilities.
• An understanding of generative AI and machine learning, which may include evidence of successful incorporation of learning activities that develop students’ understanding of generative AI and machine learning.
• An emerging profile of teaching impact in the discipline and/or emerging profile in scholarship of teaching and learning in the discipline and/or emerging research profile with high-quality outputs in the discipline.
• Well-developed communication, interpersonal and consultative skills, and the ability to work collaboratively with colleagues in teaching and learning.

We recognise candidates bring different strengths and experiences. The following criteria are desirable rather than essential, and we encourage you to highlight any relevant experience in your application:

• Participation in curriculum development at the program and/or course level in the discipline area.
• Evidence of involvement in the supervision of honours and Research Higher Degree students in scholarship of teaching and learning research and/or discipline research.
• Participation in projects that improve curriculum, pedagogy, or assessment practices of others, with funded projects being particularly desirable and/or a record of contributing successfully to applications for research funds.

Interested?

For more information and to submit an application for this role, please click on the 'Apply' button above.

Applications close Wednesday 26 August 2026 at 11.00pm AEST (R-67099).

Please note that mock lectures, teaching seminars and interviews have been tentatively scheduled for the week commencing 21 September 2026.

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