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 87 matching student topics
Displaying 73–84 of 87 results
Enhancing sonographer work-integrated learning: balancing quality training with workforce demands and student well-being
Sonographers, highly skilled healthcare professionals responsible for essential diagnostic ultrasound services, are currently facing a severe nationwide shortage. The Australasian Sonographers Association reported a deficit of at least 3,000 sonographers in 2019. Training new sonographers involves comprehensive work-integrated learning (WIL), which blends academic knowledge with structured real-world experiences to develop vital clinical skills. However, due to escalating workforce demands, concerns have arisen about potential exploitation of students within workplaces. This exploitation could involve assigning tasks exceeding their capabilities or subjecting …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Clinical Sciences
NHMRC Idea Grant: intergenerational living and learning models
This research project acts upon recommendations from the Inquiry into the Quality of Care and Residential Aged Care in Australia IQCRAC (2018) by developing an inter-generational model for senior living within school campuses in consultation with industry partners. The project differs from existing programs by establishing an economic policy-driven 'shared campus facilities and services' approach which is person-centred, health focused and socially inclusive. The model intends to be translatable across diverse Australian contexts, from urban realms where land is limited, …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
-
Design Lab
Human Emotional Learning: Likes, Dislikes and Fear
There is currently broad agreement that likes and dislikes, including strong emotional responses such as fear and anxiety, are learned. However, little is known about the manner in which different forms of emotional learning interact or about how emotional learning once acquired can be modified, reduced or eliminated. In particular in the context of fear learning this is problematic as fear memories once acquired seem difficult to change and likely to return even after successful extinction – a phenomenon known …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Psychology and Counselling
Praeclarus process-data quality framework
Praeclarus is an open-source software framework that aims to facilitate data pre-processing for process mining. Process mining is specialised data mining focusing on process-data. It is of high interest to industry, with the market doubling every two years (e.g., increasing from $550M in 2020 to $1B in 2022). This market increase has meant that big companies like Microsoft, SAP, and IBM are acquiring process mining vendors such is Minit, Signavio, and myInvenio.Recent process mining surveys show that more than 60% …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Efficient predictive models using physics-informed machine learning
This research explores how advanced physics-informed neural network models can guide the development of simplified yet accurate predictive systems across scientific and engineering domains. The work spans machine learning, computational physics, and applied mathematics, addressing the critical challenge of creating efficient models that maintain physical consistency and predictive reliability.Recent advances in neural operator learning and physics-informed architectures have demonstrated potential for dramatically reducing model complexity while preserving domain-specific knowledge. This research investigates generalisable frameworks for developing simplified predictive models that …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Evidence-Based Teaching in Economics and Business
Evidence-based teaching (EBT) refers to “the conscientious, explicit, and judicious integration of best available research on teaching technique and expertise within the context of student, teacher, department, college, university, and community characteristics” (Groccia & Buskist 2011). In practice, EBT involves educational practices derived from empirical data that show a well-established association with improved course grade, student feedback, and course-driven learning goals. Literature on EBT is growing but there is little on the impact of EBTs on students, academics as well …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Business and Law
- School
- School of Economics and Finance
Maxwell's Demon revisited: Molecular simulations as a statistical physics learning tool
In his 1871 'Theory of Heat', James Clerk Maxwell introduced a fictitious being who can violate the second law of thermodynamics by following the trajectory of every molecule within a gas.The being, later dubbed 'Maxwell's Demon' by Lord Kelvin, would operate a small trapdoor in a partitioned container to allow hotter and colder molecules of the gas to pass to opposite sides of the container. The Demon would be able to raise the temperature of the gas in one half …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
Human-in-the-loop techniques to debug machine learning models
Machine learning models are being deployed in critical domains such as healthcare, education and fintech. The current approach to deploying machine learning models is based on considering a data-centric approach where the models are evaluated using performance measures on a test set. However, the high performance of the model on test data is not indicative of its reliability,An important aspect of reliability is in the understanding of what exactly a machine learning model encodes, and to verify if it learns …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Power efficient computing for statistical machine learning
The carbon footprint of computing globally is estimated to be comparable with that of the aviation industry. With the advent of generative artificial intelligence, there is a growing awareness of this environmental impact both in terms of the carbon footprint and other environmental impacts including e-waste and water consumption, predominantly through the use of power-hungry graphics processing units (GPUs).These are particularly relevant issues to many fields that rely on computationally intensive simulations for data analysis or calibration of statistical machine …
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- 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
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
Predicting good sleep using computer science: Can we use machine learning to find out 'what's the best bed?'
In the Westernised world a person typically spends one third of their life in bed, with more time spent sleeping in a bed than in any other single activity. Sleep amount and quality of sleep have a direct impact on mood, behaviour, motor skills and overall quality of life. Yet, despite how important restful sleep is for the body to maintain good health, there is a comparatively small amount of studies evaluating key multi-factorial determinants of restful sleep in non-pathological, …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
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