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 502 matching student topics
Displaying 325–336 of 502 results
Identifying individuals at high risk of Alzheimer’s disease
Dementia is the greatest cause of disability in Australians over the age of 65 years. In the absence of a significant medical breakthrough, more than $6.4 million Australians will be diagnosed with dementia in the next 40 years. The most common form of dementia is Alzheimer’s disease (AD), accounting for 60-80% of cases. The pathogenic process of AD begins decades prior to the clinical onset, so it is likely that treatments need to begin early in the disease process to …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
The Daigou phenomenon: exploring the heterodox behaviours of entrepreneurial Chinese shoppers
As demand for Australian-made products increases, a new type of entrepreneur has emerged. Daigous, or purchasing agents, serve as important ‘middlemen’ – connecting Chinese customers with Western brands. Daigou have become a paradox. They have been associated with ‘unorthodox’ behaviours such as stockpiling highly sought after products, for example, they have previously created market-wide shortages of infant formula. On the other hand, Daigou are increasingly enacting opportunistic behaviours, boosting demand for premium Australian products such as, cosmetics, skincare and vitamins.Recently, …
- Study level
- PhD, Master of Philosophy
- School
- School of Advertising, Marketing and Public Relations
Continual learning system
AI that is pre-programmed is limited in its tasks and human bias. Learning systems offer richer decision-making behaviors where collaborative projects have led to the following three systems that require integration:A symbolic learning system that can continually learn Boolean classification problems as they are presented to it. But this needs to be extended to real-valued, noisy and uncertain classification problems.A lateralized system that can consider an input at the constituent level and the holistic level simultaneously, which enables flexible and …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Designing smart visual technologies with people with intellectual disability
This research is part of a Future Fellowship project funded by the Australian Research Council. You will join a team of researchers and research students in the school of computer science, with expertise in the disciplines of human computer interactions and data science.In broad terms, the project is seeking to understand how the meaning of images can be computed and used in the design of intelligent interfaces which can be used by and support people with intellectual disability.The visual interactions …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Molecular simulation of rotational diffusion in ideal liquids
Rotational tumbling of molecules in a liquid is an important phenomenon in Magnetic Resonance Imaging (MRI) because it determines the spin-relaxation rates of the resident nuclei which can determine MRI contrast.For a relatively simple molecular process, the theoretical description of rotational motion of molecules in liquids remains controversial. The most commonly used model, the Debye model, assumes that:the rotational diffusion propagator of a tumbling molecule is a solution of the diffusion equation on a spherical surfacethis solution is described by …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
Computational drug repurposing for neuropsychiatric disease
While hundreds of robust genetic associations have been found for neuropsychiatric disease (such as schizophrenia, major depression, and anxiety) understanding the exact molecular mechanisms leading to disease onset and progression remains challenging. Inherited (i.e. genetic) risk factors for many neuropsychiatric diseases converge on genes that are co-ordinately expressed (co-expressed) in a disease-relevant tissue (e.g. brain). The study of how genetic risk factors affect co-expressed genes (i.e. gene co-expression analysis) has the potential to uncover new biological processes underlying disease onset. …
- Study level
- Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
Can virus-based defective interfering particles (DIPS) be used to treat dengue infection?
Infection by dengue virus causes incapacitating and potentially dangerous acute disease in humans. Dengue is a mosquito-borne infectious disease with about 100 million serious clinical infections annually. Considerable effort in drug development is underway, but no effective drug therapy is available. A major difficulty for drug development is the rapid evolution of RNA viruses, like dengue virus, which presents a major challenge for controlling virus transmission and infection using conventional pharmaceuticals and vaccines.This project is based on the observation that …
- Study level
- Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
Physics-informed reinforcement learning for complex environments, using graph neural networks
Neglecting to incorporate physics information into world models for reinforcement learning leads to reduced adaptability to dynamic and complex environments and overall learning outcomes.In this project, we endeavour to develop and implement learnable models in reinforcement learning (RL) based on graph neural networks (GNNs). These models will integrate object and relation-centric representations to enable accurate predictions, strong generalization, and system identification in complex, dynamical systems. Additionally, we will focus on leveraging extensive world knowledge or physics information to refine representations …
- Study level
- PhD, Master of Philosophy, Honours
- School
- School of Electrical Engineering and Robotics
Production of hard carbon for sodium-ion batteries
The transition to renewable energy sources such as solar and wind necessitates efficient and large-scale energy storage solutions. Sodium-ion batteries (SIBs) have emerged as a viable alternative to lithium-ion batteries for grid-scale storage due to the abundance and low cost of sodium. Hard carbon anodes, derived from biomass, offer a sustainable and effective solution for SIBs, providing a pathway to enhance energy storage capabilities and support renewable energy integration.
- Study level
- PhD, Master of Philosophy, Honours
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Agriculture and the Bioeconomy
Network Flow Improvement
Network flow is impeded by the arcs present in the network and their associated length/weighting. Arcs can be added or removed to debottleneck the network. But which ones? At what cost?
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Strain-level characterisation and visualisation of microbial communities associated with inflammatory bowel disease
Inflammatory bowel disease (IBD) is a chronic, relapsing inflammatory disorder driven by complex interactions between environmental, microbial and immune-mediated factors. An unfavourable shift in gut microbiome composition, known as dysbiosis, is now considered a key feature of IBD, however it is unclear how specific microorganisms and their interactions with host cells contribute to disease onset and progression. Previous IBD studies have been largely limited to older sequencing methods with low resolution. Furthermore, these studies have predominantly focused on bacterial populations, …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
-
Centre for Microbiome Research
Moving boundary problems in mathematical biology
Invasion of biological cells or ecological populations involves moving fronts that invade into previously unoccupied regions of space. Such moving fronts are driven by a combination of motility, such as random diffusion, and proliferation, such as logistic growth. Understanding how best to model such invasive fronts is important as moving fronts of cells are associated with wound healing and cancer progression and moving fronts in ecology are associated with the spreading of weeds and invasive species.Previously both continuum and discrete …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
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