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 88 matching student topics

Displaying 1–12 of 88 results

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
School
School of Exercise and Nutrition Sciences

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
School
School of Biomedical Sciences

Model predictive control of connected vehicle platoons

Control of connected vehicle platoons can ensure the swift movement of traffic through a city by sharing vehicles' states and desired actuation. This networked control design can alleviate traffic jams, reduce vehicle emissions, and reduce fuel usage through improved aerodynamics. Model Predictive Control algorithms are a natural solution to address constraints arising from both communications and system dynamics. A key challenge is to design distributed control algorithms that are robust to disturbances in the environment and to stochastic information from …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and 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

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

Using mathematics to understand multiple sclerosis: what causes the immune system to attack the brain?

Every day, we use our bodies to move, think, talk and eat, but for people with multiple sclerosis (MS) these tasks can be virtually impossible. MS is a chronic disease which develops because the immune system has started to attack the nerve cells in the brain. This causes the degradation of parts of the brain and irreversible impairment in physical and mental activity. Unfortunately, this disease has no cure, and while considerable therapeutic advances against this disease have been achieved, …

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

Optimising delivery of a novel nose-to-brain treatment for brain cancer

Glioblastoma multiforme (GBM) is an aggressive brain cancer with no curative treatment and poor prognosis. One of the biggest challenges with treating GBM is the inability of treatment to cross the blood-brain barrier resulting in poor drug distribution in the brain. Fortunately, scientists have recently developed a novel nose-to-brain delivery system that uses nanoparticles loaded with a chemotherapy drug called paclitaxel. Initial treatment investigations in vivo are showing significant promise in reducing and controlling the tumour burden. While exciting, before …

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

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

Modelling and managing uncertain Antarctic species networks

Antarctic ecosystems are complex, and data is limited since it is expensive to collect. Species interact in food webs which can be modelled as mathematical networks. The relationships between species are not always known, or we might know they interact but not how strongly. Noisy (or imperfect) data can be used to model these species interactions to give more certainty about how the ecosystem works as a whole – although the worse the data is, the less information it contributes. …

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

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

Modelling the response of expansive soil under wetting and drying

Expansive soils are those which can experience significant volume change when water content varies and as of this reason they are considered as problematic soils in geotechnical engineering. Expansive soils are widely distributed globally and cover a significant percentage of world land surface, especially in arid and semi-arid area.In Australia, expansive soil covers around 20% of surface soils and approximately 30% of the total ‘built-up’ land area is covered by expansive soils. This figure is expected to increase, as the …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Civil and Environmental Engineering
Research centre(s)
Centre for Materials Science

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