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 493 matching student topics
Displaying 169–180 of 493 results
Do AI Language Models Think Differently in Different Languages?
Large Language Models (LLMs) — such as OpenAI's GPT-4 or Meta's LLaMA — are advanced artificial intelligence systems capable of generating fluent, human-like text in many languages. These systems are increasingly embedded in everyday technologies, shaping how people access knowledge, receive guidance, and express themselves online. However, recent research has raised important questions about how these models "think" in different languages. For example, studies suggest that many LLMs default to English-based reasoning, even when processing prompts in other languages (Etxaniz …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Communication
- Research centre(s)
- Digital Media Research Centre
Multimodal AI to simulate medical student competency
The assessment of medical graduate competency is a cornerstone of medical education and a critical safeguard for patient safety. Newly qualified physicians must demonstrate a broad range of skills and knowledge, including diagnostic reasoning, clinical decision-making, communication, procedural skills, and professionalism before independently practicing medicine. Traditional assessment methods often include standardized multiple-choice examinations, objective structured clinical examinations (OSCEs), direct observation of procedural skills (DOPS), and portfolio reviews. While these methods offer valuable insights, they have inherent limitations. Standardized tests may …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Public Health and Social Work
- Research centre(s)
- Centre for Data Science
Exploring characteristics of children with pre-myopia
Pre-myopic children are those who, due to their age and refractive error, are at highest risk of developing myopia, and are therefore a unique group of children to study. However, the ocular, environmental, and lifestyle characteristics of pre-myopic children and their potential influence on eye growth and refractive error development has not been well-established. Therefore, this study aims to explore eye growth, refractive error development and a comprehensive range of ocular, environmental, and lifestyle factors, over a 12-month period, using …
- Study level
- Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Clinical Sciences
- Research centre(s)
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Centre for Vision and Eye Research
Nudging better financial habits in young adults through digital cues
In the context of a growing cost of living crisis, many young adults are experiencing financial stress while navigating key life transitions such as starting university, moving out of home, or entering the workforce. These transitional periods present valuable but often missed opportunities to engage young people with tools and strategies that build long-term financial capability. Behaviourally-informed digital interventions - such as timely nudges and relatable role model messages - may help support better financial habits and confidence during these …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Business and Law
- School
- School of Accountancy
Improving safety behaviours for respirable crystalline silica in construction work
Respirable crystalline silica (RCS) is a major health and safety concern, particularly in construction work processes. This project is aimed at understanding employer compliance implications and employee risk perceptions, attitudes, and safety behaviours towards the control measures used in workplaces to help minimise risk related to RCS. The overall intention of the project is to help ensure effective compliance is maintained when managing RCS in the workplace and to prevent silicosis in workers.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Business and Law
- School
- School of Management
Understanding psychosocial factors for addressing mental health concerns in the construction industry
Construction workers are at an increased risk of suicide and experience higher rates of poor psychological health. This research investigates the many psychosocial factors that can contribute to worker psychological (and general) wellbeing. This includes social support, social capital, personal networks, work-related conditions, and work-life-balance. Managing the psychosocial wellbeing of workers is as critical to addressing physical risks associated with construction work.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Business and Law
- School
- School of Management
Critical evaluation of Star Formation Rate estimators in galaxies
This project aims to assess the reliability, accuracy, and limitations of various Star Formation Rate (SFR) estimators used in extragalactic astronomy. By leveraging multi-wavelength data from the ZFOURGE survey, the project will explore how well SFR indicators derived from UV, optical (Hα), infrared (IR), and radio observations compare to SED-fitted SFRs from CIGALE. The project will focus on understanding discrepancies, particularly in dusty star-forming galaxies and AGN hosts, and provide recommendations for improving SFR estimates in future research.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
Digital Games to Support FIFO Families
This unique research project explores how asynchronous digital games can strengthen social connections among FIFO (Fly-In, Fly-Out) workers and their families. Prolonged separations and demanding schedules create challenges such as isolation and mental health impacts. This study aims to understand how these families use technology to stay connected and how games can support their wellbeing.This project is associated with a funded scholarship. You'll receive a stipend valued at $33,637 per annum for a maximum duration of 1.75 years while undertaking …
- Study level
- Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Hostile Interaction Design
Hostile interaction design has emerged as a critical issue in contemporary digital environments, where design decisions increasingly prioritise institutional and corporate interests over the needs of users and citizens. Drawing parallels to hostile architecture—where physical spaces are designed to control behaviour, such as anti-homeless spikes or uncomfortable public seating—hostile interaction design manifests in digital systems as frustrating, impersonal, or obstructive experiences. These designs often shield corporations and governments from accountability, erecting barriers that prevent users from seeking help, lodging complaints, …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
- Digital Media Research Centre
Design Lab
Designing Robotic Intention Visualisation
This project is part of the Human Robot Interaction program in the Australian Cobotics Centre, an ARC Training Centre for Collaborative Robotics in Advanced Manufacturing.People effectively coordinate (co-located) teamwork through various social approaches that make team members aware of what they are doing or intend to do. Collaborative robots (cobots) are being introduced to the workplace to enable tight integration of human and robotic work activities, such as assisting human workers with repetitive or strenuous physical tasks. But robots may …
- Study level
- Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
Hierarchical forecasting: forecasting a collection of time series
Hierarchical forecasting is a method used to generate forecasts at multiple levels of aggregation within a structured hierarchy. This technique is particularly valuable in situations where data can be organised into a hierarchy based on different dimensions, such as geography, product categories, or time. The approach ensures that forecasts at the top levels (e.g. total sales) align with forecasts at the lower levels (e.g. regional or product-level sales), creating a coherent and consistent forecasting process across the entire hierarchy.In many …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Bayesian focused learning
Forecasting renewable energy production is crucial for ensuring stable and sustainable energy grids. Traditional approaches often involve a two-stage process: first, energy production forecasts are generated, then decisions, such as how much energy to produce from various sources (wind, solar, fossil fuels), are made based on those forecasts. This disjointed process, where forecast accuracy and decision-making optimization are treated separately, can lead to sub-optimal outcomes due to conflicting objective functions.The goal of this project is to bridge these stages by …
- 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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