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 101 matching student topics

Displaying 1–12 of 101 results

Novel therapeutic strategies to treat advanced colorectal cancer

Colorectal cancer is a very common disease, with over 15,000 new cases diagnosed in Australia annually. Metastatic colorectal cancer describes advanced disease that has spread beyond the primary site. This is very aggressive and incurable in the vast majority of these patients. To improve outcomes for colorectal cancer, we are using cutting edge genomic and cell biology techniques to understand disease heterogeneity and optimise drug response. We are developing novel therapeutic interventions based on unique molecular signatures and are testing …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Health
School
School of Biomedical Sciences

Food literacy projects (see description for options)

Food Literacy is a collection of knowledge, skills and behaviours required to plan, manage, select, prepare and eat foods to meet needs and determine food intake. It is the scaffolding that empowers individuals, households, communities or nations to protect diet quality through change and strengthen dietary resilience over time. Areas for further research include, but are not limited to:identifying models to integrated food literacy into dietetic practice e.g. through the Nutrition Care Processdevelop population level indicators for food literacy that …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Health
School
School of Exercise and Nutrition Sciences

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

Water living lab: flood modelling and visualisation

Smart use of rich data sets and state-of-the-art models in a central framework provides opportunities to address problems that were previously out of reach. This is particularly true in managing and responding to flood scenarios where an integrated platform can gather forecasted and measured weather and streamflow data and use those data in foresting systems, enabling an integrated visualisation platform for data sharing and real-time decision making.The water engineering research team is developing analytical and visualisation frameworks that can support …

Study level
Honours
Faculty
Faculty of Engineering
School
School of Civil and Environmental Engineering

Addressing Australia's affordable housing demand through industrialised construction

Australia is facing an intense housing crisis. Access to affordable housing has sharply declined. Moreover, the average rental vacancy is at historically low, at around 1% in major cities. The Australian government has unveiled ambitious plans to boost housing supply by building thousands and thousands of new homes within the next 10 years. However, the construction industry's capacity is severely constrained to build and supply such as the local industry relies mostly in traditional in-situ construction methods and techniques.This research …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Architecture and Built Environment

Efficient predictive models using physics-informed machine learning

This research explores how advanced physics-informed neural network models can guide the development of simplified yet accurate predictive systems across scientific and engineering domains. The work spans machine learning, computational physics, and applied mathematics, addressing the critical challenge of creating efficient models that maintain physical consistency and predictive reliability.Recent advances in neural operator learning and physics-informed architectures have demonstrated potential for dramatically reducing model complexity while preserving domain-specific knowledge. This research investigates generalisable frameworks for developing simplified predictive models that …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

From feedback loops to actionable insights: system dynamics modelling for sustainable energy systems

Energy systems are becoming increasingly complex, shaped by fluctuating renewable supply, evolving user behaviour, and dynamic market structures. To navigate this complexity, system dynamics (SD) modelling (Sterman, 2000) offers a powerful lens to understand and influence the behaviour of energy systems over time. By visualising and simulating feedback loops, stock–flow structures, and interdependencies (Fang et al., 2018), SD modelling can help generate actionable insights for designing resilient, adaptive, and user-centred energy solutions.This project explores how SD modelling can support innovation …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)

Energy Transition Centre

Basic aircraft collision risk modelling and visualisation

Aircraft collision risk modelling is complex yet key to ensuring safe air transport (both crewed and uncrewed aircraft). Different collision risk models are better suited to different airspace environments which means model comparison and evaluation is an important research problem. This project takes a deeper look into a specific collision risk modelling approach: gas models.

Study level
Honours
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics
Research centre(s)
Centre for Robotics

Overcoming the challenges of sensitive data via synthetic data generation (case study)

In the 21st Century, there is an abundance of data, often containing insights that could benefit a number of stakeholders. However, despite this opportunity, it is often the case that the data is sensitive and can not be released by organisations or government agencies due to privacy concerns. One possible solution to the above dilemma is to instead carefully construct a 'twin' data set that contains similar information (and ideally, the same insights) as the original data set, but without …

Study level
Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Optimal conservation management in uncertain Antarctic environments

Species and ecosystems in Antarctica are threatened. Optimal biodiversity conservation is an interdisciplinary field combining mathematical modelling and optimisation with ecology and conservation. We can use mathematics to understand the system, model how management actions might impact it, and then optimise which actions should be used. For example, we can explore where protected areas should be placed, how species should be managed, or how tourist impacts should be reduced. However, the complexities of conservation in Antarctica necessitate the application of …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Modelling and managing uncertain Antarctic species networks

Antarctic ecosystems are complex, and data is limited since it is expensive to collect. Species including penguins, seabirds, invertebrates, mosses, and marine species interact in food webs which can be modelled as mathematical networks. These networks can be large, span across terrestrial and marine systems, and are changing in response to environmental changes.These ecological networks can be modelled using differential equation predator prey models like Lotka-Volterra to describe these interactions. However, the relationships between species are not always known, or …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Optimal ecosystem management in rapidly changing systems

Delays in acting in collapsing ecosystems can be catastrophic. With every passing year, the chances that the ecosystem has progressed past some point of no return increases. Yet the research and development needed to develop a new technology can take a long time. Balance between these two dynamic processes is needed to determine the optimal length and effort for developing new technologies. This project will develop a method for finding the optimal schedule for developing technological readiness, social acceptability, a …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

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