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 101 matching student topics
Displaying 73–84 of 101 results
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
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 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
Supporting Boundary Management in Young People’s AI Companion Interactions
We invite applications for a PhD position within an interdisciplinary research team examining how young people engage with AI companion chatbots (e.g., Character.AI, Replika) and how they manage risks and boundaries in these interactions.AI companions have grown in popularity since the COVID-19 pandemic and are increasingly used by young people seeking connection. This trend raises important concerns, including exposure to harassment, misinformation, and self-harm, as well as the potential impact on human relationships when reliance on AI companions becomes significant.This …
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Computer Science
Enhancing 3D visual understanding through multimodal data fusion
The demand for 3D scene understanding through point clouds is rapidly growing in diverse applications, including augmented and virtual reality, autonomous driving, robotics, and environment monitoring. However, the field faces challenges due to limited data availability and predefined categories. Training deep 3D networks effectively for sparse LiDAR point clouds requires significant amounts of annotated data, which is both time-consuming and expensive. Building on the advancements in 2D models that leverage the power of image and language knowledge, our project aims …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Interactive (and collaborative) robot programming using language (Project 2.5 - Joint CSIRO/ACC)
Programming robots to carry out desired tasks is difficult and time-consuming. This PhD project focuses on collaborative and instructional dialogue agents to help human operators program robot tasks.In this collaborative scenario, a human operator converses with an AI agent to explain the steps that are to be performed, using high-level references and abstractions that make sense to the human, as opposed to simple verbal instructions corresponding to rudimentary robot movements. The AI agent must interpret the high-level instructions and translate …
- Study level
- PhD
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
-
Design Lab
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
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Materials Science
Acceptance and adoption of ambient assistive technologies
Vision-based technologies offer new possibilities to assist individuals with cognitive disabilities to live independently. Ambient assistive technologies, such as smart mirrors and social robots, enable new ways to interact at home with AI technologies that can see.How can we ensure the social acceptance and support the adoption of ambient assistive technologies?Technologies that support independent living are about much more than fulfilling a particular task. They alter how people perceive themselves and how they engage with others. Students in this project …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Respectful ambient interactions with vision-based assistive technology
Vision-based technologies offer new possibilities to assist individuals with cognitive disabilities to live independently. Ambient assistive technologies, such as smart mirrors and social robots, enable new ways to interact at home with AI technologies that can see.How can we design respectful ambient interactions that balance assistance and privacy?Students in this project will develop a method and theory of interactive intent for people with cognitive disabilities. The theory will be established through an exploration of the new types of interactions made …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
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