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.
Found 12 matching student topics
Displaying 1–12 of 12 results
Modelling the osteoid: A quantitative experimental–mathematical platform for osteocyte network formation and transport
Project Reference: #4MPQC-NATP3Preferred Project Start: Late 2026/Early 2027How does a newly formed bone matrix develop into a mineralised tissue containing a functional osteocyte network, and how does this transformation affect the movement of nutrients and signals?During bone formation, osteoblasts produce a soft, initially unmineralised extracellular matrix known as osteoid. Some osteoblasts gradually become embedded within this matrix and transition into osteocytes, extending dendritic processes that connect them into an intricate three-dimensional network. As the osteoid matures and mineralises, its architecture, …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
Asymmetric information in social dilemmas
Information about the state of the environment can be critical for promoting environmentally friendly and socially beneficial behaviors when people are facing social dilemma choices. However, it is not clear if individuals will be willing to spread this information for the benefit of everyone else. This project aims to understand how socially beneficial actions propagate when information is asymmetric.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Making predictions using simulation-based stochastic mathematical models
Stochastic simulation-based models are very attractive to study population-biology, disease transmission, development and disease. These models naturally incorporate randomness in a way that is consistent with experimental measurements that describe natural phenomena.Standard statistical techniques are not directly compatible with data produced by simulation-based stochastic models since the model likelihood function is unavailable. Progress can be made, however, by introducing an auxiliary likelihood function can be formulated, and this auxiliary likelihood function can be used for identifiability analysis, parameter estimation and …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Curvature dependence of reaction-diffusion wave front speed with nonlinear diffusion.
Reaction-diffusion waves describe the progression in space of wildfires, species invasions, epidemic spread, and biological tissue growth. When diffusion is linear, these waves are known to advance at a rate that strongly depends on the curvature of the wave fronts. How nonlinear diffusion affects the curvature dependence of the progression rate of these wavefronts remains unknown.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
Optimising bone shape with memory networks
Bone is a dynamic tissue that optimises its shape to the mechanical loads that it carries. Bone mass is accrued where loads are high, and reduced where loads are low. This adaptation of bone tissue to mechanical loads is well-known and observed in many instances. However, what serves as a reference mechanical state in this shape optimisation remains largely unknown.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
Efficient parameter estimation for agent-based models of tumour growth
Cancer is an extremely heterogeneous disease, particularly at the cellular level. Cells within a single cancerous tumour undergo vastly different rates of proliferation based on their location and specific genetic mutations. Capturing this stochasticity in cell behaviour and its effect on tumour growth is challenging with a deterministic system, e.g. ordinary differential equations, however, is possible with an agent-based model (ABM). In an ABM, cells are modelled as individual agents that have a probability of proliferation and movement in each …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Surrogate models for accurate prediction and inference in mathematical biology
High fidelity mathematical models of biological phenomena are often complex and can require long computational runtimes which can make computational inference for parameter estimation intractable. In this project we will overcome this challenge by working with computationally simple low fidelity models and build a simple statistical model of the discrepancy between the high and low fidelity models. This approach provides the best of both worlds: we obtain high accuracy predictions using a computationally cheap model surrogate.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Mathematical modelling of brain cancer informed by patient data
In this research project, you will develop a mathematical model, known as an agent-based model, to capture the development of a brain cancer in a patient. The model will then be matched to clinical samples from patients and used to make predictions around treatment efficacy.
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Mathematical modelling of spatial plant patterns in a sub-Antarctic island
Various spatial patterns naturally emerge in ecology. These include stripes, spots, hexagons, and donuts, to name just a few. However, it can be puzzling to figure out how these patterns form.Systems of partial differential equation models can be used to simulate these patterns, and thereby provide ecologists with testable hypotheses for how these patterns formed.
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for the Environment
Mathematical modelling of ecosystem feedbacks and value-of-information theory
Ecosystems respond to gradual change in unexpected ways. Feedback processes between different parts of an environment can perpetuate ecosystem collapse, leading to potentially irreversible biodiversity loss. However, it is unclear if greater knowledge of feedbacks will ultimately change environmental decisions.The project aims to identify when feedbacks matter for environmental decisions, by generating new methods that predict the economic benefit of knowing more about feedbacks. Combining ecological modelling and value-of-information theory, the outcomes of these novel methods will provide significant and …
- 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
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
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
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