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 476 matching student topics
Displaying 409–420 of 476 results
Digital Leadership Competencies for AI Adoption
Identify the specific competencies and skills that leaders need to effectively lead AI adoption initiatives in organisations. Research can focus on areas such as data literacy, AI literacy, critical thinking, decision-making, and the ability to manage and interpret AI-driven insights. Develop frameworks for assessing and developing these competencies in leaders.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
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Centre for Behavioural Economics, Society and Technology
The Impact of AI on Leadership Roles and Structures
Examine how the introduction of AI technologies reshapes traditional leadership roles and organisational structures. Investigate the evolving nature of leadership in decentralised, AI-driven decision-making processes and explore how leaders can effectively adapt to new leadership paradigms.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
-
Centre for Behavioural Economics, Society and Technology
Mathematical tools for stochastic and continuum transport models
Mathematical models of particle transport are fundamental to many applied disciplines including physics, biology, ecology and medicine. Particle transport is typically modelled using either a stochastic model, where probability rules govern the motion of individual particles, or a continuum model, where partial differential equations govern the concentration of particles in space and time. This project aims to use analytical and numerical techniques from applied and computational mathematics to address one or both of the following questions:what is the average time …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Anode-free Batteries
The lithium-metal battery (LMB) has been regarded as the most promising and viable future high-energy-density rechargeable battery technology due to the employment of the Li-metal anode. However, it suffers from poor energy density and safety, and improved battery design is sought. The anode-free full-cell architecture is constructed from a fully lithiated cathode with a bare anode Cu current collector. In such an anode-free lithium battery, both the gravimetric and volumetric energy densities can be extended to the maximum limit. Moreover, …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
BIOM01 - Novel therapeutic strategies for targeting dementia
Dementia exhibits the presence of Lewy bodies in the cerebral cortex, which are composed of α-synuclein (αSYN) or Amyloid-β (Aβ) plaques, as well as hyperphosphorylated tau (P-tau) tangles in various forms of dementia. The exact pathological mechanisms underlying this disease are not well understood; however, there is evidence suggesting the involvement of inflammatory activity. Microglia, macrophage cells residing in the brain responsible for clearing external pathogens and dead cells, are of particular interest.Our study aims to investigate whether Lewy bodies …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Biomedical Sciences
- Research centre(s)
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Centre for Microbiome Research
The role of childhood social-emotional learning competencies in adolescent health, education, and justice outcomes
This project aims to determine the relationship of childhood social-emotional competencies (particularly those developed by school-based social-emotional learning programs) with adolescent health, education, and justice outcomes. The project uses data from the NSW Child Development Study, a longitudinal study following the development of 91,597 children in NSW from birth.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Psychology and Counselling
Unravelling the function of PSA variants in prostate cancer
OverviewProstate cancer (PCa) is the second-most common cancer in men. Prostate-specific antigen (PSA) encoded by the KLK3 gene is the only FDA-approved PCa biomarker for PCa. As a serine protease, PSA can also regulate multiple functions involved in PCa progression and metastasis and is summarised in our recent publications. Immunotherapies, including PSA-targeting therapies, have shown modest improvement in survival, for only a subset of metastatic PCa patients. Not much is known on the immunoregulatory role of PSA or its variants, …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
- Centre for Genomics and Personalised Health
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
Explainability of outlier detection methods
Outliers are anomalous observations in a data set that are "outside the norm" of what would be expected. Identifying outliers is an important part of exploratory data analysis and data analysis in general. It is often a challenging problem and calls for advanced methods and approaches, including machine learning-based tools. As methods become more and more complex, their explainability becomes more difficult and more important. This research project will look at all aspects of explainability and explore new approaches and …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
The role of genetics in the development and mechanism of human traits
The Statistical and Genomic Epidemiology Laboratory (SGEL) studies the role of genetics in the development and mechanism of human traits, with particular emphasis on migraine, and the specific goal of identifying genetic risk factors and detecting common genetic links with other disorders, in particular depression, endometriosis, and epilepsy.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
- Centre for Genomics and Personalised Health
Aerosol presursors in Australian marine environments
Aerosols, tiny solid or liquid particles, play an important role in global climate regulation, firstly, by scattering and absorbing incoming solar radiation and, secondly, by their ability to take up water vapor from the atmosphere and serve as nuclei for cloud droplet formation (Cloud Condensation Nuclei (CCN)).With oceans covering 71% of the Earth’s surface, marine aerosols present a significant proportion of the global aerosol budget. Production of particles in the marine environment occurs via 2 pathways: 1) wave breaking and …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
- Research centre(s)
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Centre for the Environment
Machine Learning-based pedictive tool for energy storage
The fundamental idea behind the ML approach is to analyze and map the relationships between the physical,chemical, and energy storage properties of materials with their associated output data. This early understanding of the energy storage capabilities through the ML approach helps the material scientists to clearly understand, discover, and optimize the fabrication process to develop highly efficient energy storage systems. It also provides key steps in the device fabrication process omitting excessive experimental stages.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
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