Student topics

This project examines how mathematics teacher education develops across primary and secondary contexts, focusing on curriculum, pedagogy, reasoning, and assessment.The project builds on current research examining how teacher education is designed differently across contexts and schooling levels.

Study level

PhD, Master of Philosophy

Faculty

Faculty of Creative Industries, Education and Social Justice

School

School of Education

This project investigates how teachers develop confidence and capability in teaching statistics, probability, and modelling. It focuses on strengthening pedagogical and content knowledge in complex mathematical domains.This project builds on extensive experience in pre-service teacher education and research on strengthening statistical reasoning and conceptual understanding.

Study level

PhD, Master of Philosophy

Faculty

Faculty of Creative Industries, Education and Social Justice

School

School of Education

This project explores how authentic modelling approaches (for example Bayesian reasoning and systems thinking) can be integrated into secondary mathematics classrooms to enhance engagement and conceptual understanding.

Study level

PhD, Master of Philosophy

Faculty

Faculty of Creative Industries, Education and Social Justice

School

School of Education

This project examines how pathways of disadvantage and success develop across schooling. It focuses on identifying how socio-economic, wellbeing, and contextual factors interact over time to shape outcomes.This project extends ongoing research into student engagement trajectories and aligns with faculty priorities in inclusive and socially just education.

Study level

PhD, Master of Philosophy

Faculty

Faculty of Creative Industries, Education and Social Justice

School

School of Education

This project explores how advanced statistical modelling can support decision-making in complex education systems. It focuses on modelling uncertainty, interdependencies, and policy-relevant insights to guide planning and practice.The project aligns with research applying Bayesian networks to real world decision-making under uncertainty across infrastructure, health, and education contexts

Study level

PhD, Master of Philosophy

Faculty

Faculty of Creative Industries, Education and Social Justice

School

School of Education

This PhD project investigates how academic, wellbeing, family, and school-context factors interact to shape student engagement, retention, and academic success in secondary schooling. Using large-scale longitudinal datasets, the project will develop advanced probabilistic models to identify key predictors and pathways that explain diverse learner trajectories.The research will contribute to evidence-based strategies for improving student engagement and reducing attrition, with strong relevance to policy and practice in Australian and international contexts.This project builds on ongoing work applying advanced statistical modelling to …

Study level

PhD, Master of Philosophy

Faculty

Faculty of Creative Industries, Education and Social Justice

School

School of Education

Two full PhD scholarships are available at Queensland University of Technology (QUT), Brisbane, Australia, focusing on machine learning for power quality analysis in low-voltage distribution networks.These PhD projects are part of an Industrial Transformation Training Centre (ITTC), providing students with access to a strong interdisciplinary research environment and collaboration opportunities with leading academic researchers and industry partners.The projects will investigate how solar inverters and electric vehicle (EV) chargers affect harmonic distortion, impedance, and resonance behaviour in the 2–9 kHz range. …

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

This research topic explores the use of journey mapping as a research and design methodology to better understand, analyse and improve student experiences in engineering education. The project investigates how students navigate key stages and touchpoints across the academic lifecycle including transition into university, curriculum progression, assessment, engagement, wellbeing and career development. By systematically mapping these journeys, the research aims to reveal patterns, barriers, and opportunities that shape student engagement, experience and success.Situated at the intersection of engineering education research, …

Study level

PhD

Faculty

Faculty of Engineering

School

School of Civil and Environmental Engineering

This research topic examines educator capability development and recognition in engineering education, with a particular focus on the misalignment between the skills increasingly required of educators and the ways those skills are formally recognised and rewarded in higher education.Building on contemporary scholarship in engineering education and academic career development, the project explores how expectations around teaching quality, digital capability, assessment design, and evidence‑based practice have expanded—while promotion, workload, and recognition frameworks have not always kept pace.The research aims to inform …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Mechanical, Medical and Process Engineering

This research topic explores the use of emerging technologies and data‑driven approaches to enhance learning and teaching in engineering education. The project investigates how diverse educational data sets can be leveraged to support evidence‑based decision making across multiple levels of the institution—from individual educators and course teams to faculty leaders and senior executives. The work sits at the intersection of engineering education, learning analytics, and strategic use of educational data to improve student engagement, experience, and success.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Mechanical, Medical and Process Engineering

Research centre(s)

Centre for Data Science

Despite substantial advances in science, the translation of research findings into commercial products and services remains limited and uneven. Many promising ideas stall in the “valley of death” between laboratory discovery and market adoption, resulting in under-realised economic and societal impact.This research topic examines how scientific knowledge can be more effectively transformed into entrepreneurial ventures and innovations that deliver tangible outcomes. Positioned at the intersection of entrepreneurship and innovation, the topic explores the organisational, institutional, and individual factors that enable …

Study level

PhD, Master of Philosophy

Faculty

Faculty of Business and Law

School

School of Management

Research centre(s)

Centre for Future Enterprise
Australian Centre for Entrepreneurship Research

The carbon footprint of computing globally is estimated to be comparable with that of the aviation industry. With the advent of generative artificial intelligence, there is a growing awareness of this environmental impact both in terms of the carbon footprint and other environmental impacts including e-waste and water consumption, predominantly through the use of power-hungry graphics processing units (GPUs).These are particularly relevant issues to many fields that rely on computationally intensive simulations for data analysis or calibration of statistical machine …

Study level

PhD

Faculty

Faculty of Science

School

School of Mathematical Sciences

Research centre(s)

Centre for Data Science