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 37 matching student topics
Displaying 25–36 of 37 results
AI-Based Data Analysis on Multiple Imaging Modalities
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. According to the World Health Organization (WHO), it is estimated CVD takes 17.9 million lives every year. In Australian, the statistical data from the Australia Heart Foundation shows CVD is a major cause of death in Australia. It occupies 26% of all deaths, responsible for an average 118 deaths every day. Four of the main types of CVD are coronary heart disease, strokes and transient ischaemic attack, peripheral …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Investigation of genetic factors that contribute to concussion and its outcomes
The health outcomes from traumatic brain injuries (TBIs) and concussion depend on the nature of the injury, but response also varies greatly between individuals, suggesting that genetic factors may play a role. In particular, due to effects of head trauma on balances of ions, neurotransmitters and energy use in the brain, there is suggestion that variation in the genes that encode proteins involved in these pathways, e.g. ion channels, may affect the risk of, as well as response to a …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
Understanding public perceptions of the sustainable energy transition: a social network analysis
The challenge to keep global warming to 1.5°C above pre-industrial levels has become even greater due to a continued increase in greenhouse gas emissions (IPCC, 2023). One major challenge is the shift from fossil fuels to renewable energy to reduce emissions (Gholami et al., 2016). The share of renewable energy in electricity generation has increased to 28.3%, however, an acceleration of the pace of the transition is required to limit global temperature rise (REN21, 2022).In this project we investigate public …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Alignments In Process Mining and Social Sequence Analysis
In process mining, we perform computational analyses of sequential data in order to help organisations improve, in settings from ride-sharing platforms to government departments. In social sequence analysis, we perform computational analysis on sequential data to understand small or large structures in society, such as the progress of careers of 18th century German musicians, or the progress of nations through different stages of economic development.In both process mining and social sequence analysis, calculation of "alignments" for is a key technique …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Prostate cancer transcriptomics (Honours and Master of Philosophy)
At the Australian Prostate Cancer Research Centre QLD, we are interested in the cellular adaptive response processes leading to therapy resistance in advanced prostate cancer.A focus area of our research is studying the transcriptome changes in prostate cancer cell lines, xenograft models and patient samples using RNA sequencing technologies.By integrating our large in-house repository of RNAseq data sets with publicly available studies, this project will further explore the cellular heterogeneity of prostate tumours and the plasticity of cancer cells in …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
Towards Synthetic protein-structures based on precision macromolecules: can we beat nature in designing catalysts?
Up for a challenge? In this project you can explore if you can beat nature in making catalytic systems! Over billions of years, nature has perfected the design and synthesis of high molecular weight precision macromolecules, which are able to execute a specific function in a complex biological environment such as proteins.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
Advanced electron microscopy for sustainable nanocatalysis
The systematic and detailed characterisation of heterogeneous catalysts is critical for design of effective and stable catalytic materials, since it allows one to understand the correlation between their structure and physicochemical properties.Especially, it is important to monitor the structural evolution of catalytic materials and their active sites in a controllable environment and under realistic reaction conditions.Thus, we propose to use a powerful combination of aberration-corrected high-resolution TEM and in situ TEM experiments which allow us to gain extensive knowledge about …
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
Analysing the oceanographic variables that generate and mobilise coral rubble on the GBR
There is increasing concern on the effects of global warming and how it is increasing the frequency and severity of disturbance events on the Great Barrier Reef (GBR), an enduring living structure on our planet. For example, the intensity and frequency of tropical cyclones is likely to increase and this will also reduce the time available for coral reefs to recover.Moreover, there are other factors that contribute to the vulnerability of coral to mechanical breakage, such as crown of thorns …
- Study level
- Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
Multi-modal sentiment analysis
In deep learning models, language models and word embedding methods have become popular to understand the context of text data. Popular language models such as BERT have limitations in terms of the token length. There exist some corpora that have longer text with an average of 1000 tokens. Additionally, these corpora are text-heavy and only include some images.In our prior works, we have developed several multi-modality models on social media datasets.
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- 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
Measuring higher education performance: a global comparisons using network data envelopment analysis
The research objective focuses on comparing the top 100 universities (according to the Times Higher Education) from 2010 to 2020. The objective of the project is fourfold. First, to derive appropriate research outputs per university. Second, employ a Network DEA approach to identify (in)efficiencies within the network. Third, to measure productivity change of universities using the Fare-Primont index. Fourth, to determine sources of (in)efficiencies and productivity.This project is both theoretical and applied. The applicant should possess strong mathematical and computational …
- Study level
- PhD
- Faculty
- Faculty of Business and Law
- School
- School of Economics and Finance
Assessing the quality of cluster analysis
Machine learning cluster methods are common classification methods, but methods for assessing performance are limited as are methods for explaining how they work. Exploring methods for both assessing and explaining performance are the subject of this research with application to real-world contexts with the Australian Bureau of Statistics.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
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