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 41 matching student topics
Displaying 25–36 of 41 results
Mathematical modelling of cell-to-cell communication via extracellular vesicles (EVs)
Extracellular vesicles (EVs) are membrane bound packages of information constantly being released by all living cells, including bacteria. There are many types and sizes of EVs. Each EV type contains its own distinctive cargo consisting of characteristic DNA, RNA, and proteins. We are just beginning to understand the many roles of EVs to maintain the health of the cell producing the EVs, and to communicate with other cell types that take up the EVs produced by neighbouring cells. Since EVs …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
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
Branching processes, stochastic simulations and travelling waves
Branching processes are stochastic mathematical models used to study a range of biological processes, including tissue growth and disease transmission.This project will implement a simple stochastic branching process to generate simulations of biological growth, and then consider differential equation-based description of the stochastic model.Using computation we will compare the two models, and use phase plane and perturbation analysis to analyze the resulting traveling wave solutions.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
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
How do healthy people sleep? Biomechanics, physiology, and environment - what matters most?
In the Westernized world a person typically spends one third of their life in bed, with more time spent sleeping in a bed than in any other single activity. Sleep amount and quality of sleep have a direct impact on mood, behaviour, motor skills and overall quality of life. Yet, despite how important restful sleep is for the body to maintain good health, there is a comparatively small amount of studies evaluating key multi-factorial and biomechanical determinants of restful sleep …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Image-based assessment of atherosclerotic plaque vulnerability: Towards a computational tool for early detection and prediction
Plaque characteristics and local haemodynamic/mechanical forces keep changing during plaque progression and rupture.Quantifying these changes and discovering the progression-stress correlation can improve our understanding of plaque progression/rupture. This will lead to a quantitative assessment tool for early detection of vulnerable plaques and prediction of possible ruptures.Our research project aims to combine medical imaging, computational modelling, phantom experiments and pathological analysis to investigate plaque progression and vulnerability to rupture in both animal models and patients with carotid stenosis.We will identify and …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Image-based computational model to predict intracranial aneurysm rupture
Intracranial aneurysms are bulging, weak areas of an artery that supply blood to the brain which are relatively common. While most aneurysms do not show symptoms, 1% spontaneously rupture which can be fatal or it can leave the survivor with permanent disabilities. This catastrophic outcome has motivated surgeons to operate on approximately 30% of aneurysms despite their rate of complications arising and cost of operation.The impact of aneurysm morphology on blood flow shear stress and rupture could educate surgical decision-making …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Mathematical and computational models for diffusion magnetic resonance imaging (dMRI)
In 1985, the first image of water diffusion in the living human brain came to life. Since then significant developments have been made and diffusion magnetic resonance imaging (dMRI) has become a pillar of modern neuroimaging.Over the last decade, combining computational modelling and diffusion MRI has enabled researchers to link millimetre scale diffusion MRI measures with microscale tissue properties, to infer microstructure information, such as diffusion anisotropy in white matter, axon diameters, axon density, intra/extra-cellular volume fractions, and fibre orientation …
- 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 Biomedical Technologies
Advanced numerical modeling to study dust deposition mechanisms on photovoltaic panels for the agrivoltaic industry.
The increase in global energy demand necessitates further advancement in photovoltaic (PV) systems. Advancements in PVs could potentially play a role to help meet the Paris Agreement of limiting global temperature increase to below 2 degrees Celsius. In conjunction with the rising demand for clean energy production, the global agricultural industry needs to keep pace with rising food demand which is expected to increase by 50% by 2050 to feed over a projected 10 billion people. The scarcity of fertile …
- Study level
- PhD, Honours
- School
- School of Mechanical, Medical and Process Engineering
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
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
Finite element modelling of 3D auxetic structures
Protection of structures has become a priority for saving lives and preventing structural collapses caused by increased natural or man-made disasters. Most injuries and mortalities in these disasters are caused due to fragmentation of structures, and therefore, structural protection through systems that can absorb more energy and effectively contain the fragments (debris) are needed. Additive manufacturing (such as 3D printing) can be used to develop special geometries called auxetic geometries and composites using sustainable bioplastics which can absorb shock energy …
- 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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