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 238 matching student topics
Displaying 61–72 of 238 results
Assessing reef restoration using MARRS Reef Stars on the Great Barrier Reef
The Bait Reef rehabilitation project commenced in early 2021 (site surveys, risk assessments and approval processes) and installation on-site occurred in October 2021. Since installation there has been monitoring of the Reef Stars in June 2022, February 2023, and January 2024.Thermal bleaching impacts in early 2022 and rapid colonisation of the area by soft corals meant that by February 2022 more than 50% of the original coral fragments had died. Subsequently, in August 2023 all dead fragments (still attached to …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
- Research centre(s)
- Centre for Data Science
X-ray backscatter diffraction and X-ray fluorescence for the rapid structural and chemical characterisation of rock samples
The advisory team devised a synchrotron-based microscopy method for coeval measurements of elemental concentrations and crystal-orientation data combining X-ray fluorescence microscopy (XFM) with X-ray backscatter diffraction mapping (XBDM).We seek students with a background in physics, crystallography, or mineralogy and coding skills to help with the improvement of the methods.XBDM/XFM has the potential to become a game changer in the microphysical and -chemical characterisation of crystalline solids, with future applications in the critical-minerals industry and material science.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
Profiling aerosol liquid water content over Australia
Aerosol liquid water content (ALWC) is a ubiquitous constituent in atmospheric aerosol particles. The degree of ALWC present in aerosol particles is influenced various factors, including relative humidity, temperature, particle mass, size distribution, and aerosol composition. Comprehensive analyses on ALWC have been conducted in the Northern Hemisphere, but similar work has rarely been done in the Southern Hemisphere due to the scarcity of aerosol particle measurements. In the atmosphere, ALWC scatters radiation and reduces visibility, significantly affecting air quality, weather, …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
Atomic-scale identification of catalyst active sites using electrochemical scanning tunneling microscopy
Catalysts have an important role to play in electrochemical reactions. By reducing the energy required for a reaction, they can save electricity and make feasible the reactions that will enable future sustainable technologies, such as the evolution of hydrogen from water. Optimisation of catalysts requires a detailed mechanistic understanding of their function. A key aspect of this is determining, at the atomic scale, the reactive sites on the catalyst surface. This type of insight can be provided by performing atomic-scale …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
Hospital readmission prediction with domain knowledge
The Australian Commission on Safety and Quality in Health Care has highlighted that reducing avoidable hospital readmissions supports better health outcomes, improves patient safety and leads to greater efficiency in the health system. Previous studies have reported that up to 11% of the emergency (ED) population are 'heavy users' with a higher prevalence of psychosocial problems and often co-existing chronic medical conditions. All Australian governments have committed to reforms under the National Health Reform Agreement Addendum,1 and the ability to …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Interpretable software vulnerability detection using deep learning techniques
Software vulnerabilities have been considered as significant reliability threats to the general public, especially critical infrastructures. Many approaches have been proposed to detect vulnerabilities in source code to avoid any damages they pose when exploited. Conventional approaches include static analysis and dynamic analysis. Static analysis uses pre-defined patterns or vulnerability dataset to scan and examine software source code to identify potential vulnerable code snippets. These patterns are manually crafted or identified by software developers or security experts, which are time-consuming. …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- 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
Process Mining Infrastructure In Haskell
In process mining, sequence analysis algorithms are used to discover computational models of process data, and to analyse them. The insights from these models and analysis then improve the processes in organisations in many real-life domains - from manufacturing, to government, to healthcare. Haskell is a powerful functional programming language well suited to problems involving formal reasoning and pattern matching. This project would advance process mining research by building high-quality, high performance libraries in Haskell for fundamental process mining activities …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Tailoring novel electrode/separator for high performance aqueous zinc metal batteries
Developing sustainable and clean energy sources (e.g. solar, wind, and tide energy) is essential to achieve the goal of carbon neutrality. Due to the discontinuous and inconsistent nature of common clean energy sources, high-performance energy storage technologies are a critical part of achieving this target. Aqueous zinc metal batteries with inherent safety, low cost, and competitive performance are regarded as one of the promising candidates for grid-scale energy storage. However, zinc metal anodes with irreversible problems of dendrite growth, hydrogen …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
Combining solar and vibration energy harvesting for rainfall prediction
Rainfall prediction plays a crucial role in various sectors such as agriculture, water resource management, and disaster preparedness. Traditional prediction methods often rely on complex meteorological models and expensive equipment. However, advancements in energy harvesting technology offer the opportunity to develop low-cost and sustainable solutions for rainfall prediction.This project proposes to leverage solar and vibration energy harvesting for rainfall prediction. Combined measurements from both solar and vibration energy harvesting can provide comprehensive data for real-time monitoring of cloud coverage and …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Gamification and serious games to encourage behavioural change in energy consumption
Games have become an integral part of our lives, which is why they are increasingly being used for other purposes than pure entertainment, such as learning, training, informing, or advertising (Degirmenci, 2017). While gamification uses game elements in non-game contexts, serious games are full-fledged games, both aiming to create meaningful engagement and foster desired behaviours (Degirmenci, 2023; Degirmenci and Breitner, 2023).In this project, we investigate how gamification and serious games can help to encourage behavioural change in energy consumption to …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
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Energy Transition Centre
Artificial intelligence (AI) to balance fluctuations of intermittent renewable energy sources
Artificial intelligence (AI) can play a significant role in analyzing and predicting energy consumption and production patterns from renewable sources such as solar and wind (Lyu & Liu 2021). This is particularly important due to the key challenge of intermittency, where major renewable sources for electricity, such as solar and wind, are subject to the inconsistencies of the weather (Watson et al., 2022).In this project, we investigate how AI and machine learning algorithms can optimize smart grids and other components …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Future Enterprise
Energy Transition Centre
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