QUT offers a diverse range of student topics for Honours, Masters and PhD study. Search to find a topic that interests you or propose your own research topic to a prospective QUT supervisor. You may also ask a prospective supervisor to help you identify or refine a research topic.

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Found 510 matching student topics

Displaying 169–180 of 510 results

AI in Entrepreneurship

Artificial intelligence (AI) is transforming entrepreneurship in profound and far-reaching ways, yet our scholarly understanding of this transformation remains nascent and uneven. AI is not only reshaping how entrepreneurs create and grow ventures, but is also challenging the very foundations of how we study entrepreneurship — questioning long-held assumptions about agency, creativity, opportunity, and what it even means to be an entrepreneur in an AI-driven world.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Business and Law
School
School of Management

Mathematical and statistical methods for change point detection in precision fermentation

Precision fermentation uses microorganisms such as yeast to produce valuable biological products for food, biotechnology and synthetic biology. A major challenge is that microbial growth and production can change when cells switch between different metabolic regimes. These changes may occur because of nutrient depletion, stress responses, dilution conditions, or shifts in how cells allocate resources between growth and product formation.This PhD project will develop new mathematical and statistical methods for detecting these metabolic change points from experimental data. The project …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences

Detecting metabolic regime switching using dilution-resolved growth data: mathematical modelling, statistical inference and uncertainty quantification

Microbial populations rarely grow according to a single fixed physiological program. As nutrients are consumed, waste products accumulate and environmental stress changes, cells can transition between distinct metabolic regimes associated with growth, maintenance, fermentation, respiration and survival. These transitions are biologically important and industrially relevant, but they are often difficult to detect directly from standard growth curve summaries such as maximum growth rate, lag time, carrying capacity or area under the curve.This project will develop new mathematical and statistical methods …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Mathematical Sciences

Trust formation in generative AI–supported mental health Services

Generative Artificial Intelligence (GenAI) tools such as chatbots and AI companions are increasingly positioned as accessible forms of mental health support. However, user engagement with these services depends heavily on trust, particularly in contexts characterised by vulnerability, stigma, and emotional risk. Trust in mental healthcare differs from trust in other service settings, raising important questions for marketing and service researchers.This project investigates how trust is formed and evaluated in GenAI‑supported mental health services from a consumer and service marketing perspective. …

Study level
Master of Philosophy
Faculty
Faculty of Business and Law
School
School of Advertising, Marketing and Public Relations

Volcanic stratigraphy of mineralised Precambrian terranes

This research examines the geological evolution of mineralised terranes, with a particular focus on the stratigraphic, volcanic, and tectonic controls on mineralisation. By reconstructing the geological history of mineral systems, I seek to improve exploration models.These projects are done in collaboration with industry partners and supported through industry-sponsored projects, providing opportunities to address both fundamental scientific questions and applied exploration challenges.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Earth and Atmospheric Sciences

AI, data, and mathematical thinking in education

This project explores how emerging technologies, including artificial intelligence, influence mathematical thinking, teaching, and learning. It focuses on how students and teachers engage with data-rich and AI-supported environments.The project aligns with ongoing work in quantitative reasoning, modelling, and educational innovation, including research on adaptive learning technologies.

Study level
PhD, Master of Philosophy
Faculty
Faculty of Creative Industries, Education and Social Justice
School
School of Education

Mathematics Teacher Education Across the Primary–Secondary Continuum

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

Developing teacher capability in statistical reasoning and modelling

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

Bridging Real-World Modelling and Secondary Mathematics 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

Modelling educational equity and access pathways

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

Data-informed decision-making in education systems

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

Modelling student engagement and success using Bayesian networks

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

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