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 507 matching student topics
Displaying 181–192 of 507 results
From lab to market: enhancing the translation of publicly funded research into commercial impact
Despite substantial advances in science, the translation of research findings into commercial products and services remains limited and uneven. Many promising ideas stall in the “valley of death” between laboratory discovery and market adoption, resulting in under-realised economic and societal impact.This research topic examines how scientific knowledge can be more effectively transformed into entrepreneurial ventures and innovations that deliver tangible outcomes. Positioned at the intersection of entrepreneurship and innovation, the topic explores the organisational, institutional, and individual factors that enable …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Business and Law
- School
- School of Management
- Research centre(s)
- Centre for Future Enterprise
Australian Centre for Entrepreneurship Research
Mathematical modelling of brain cancer informed by patient data
In this research project, you will develop a mathematical model, known as an agent-based model, to capture the development of a brain cancer in a patient. The model will then be matched to clinical samples from patients and used to make predictions around treatment efficacy.
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Forecast stability and volatility control in decision-centric time series forecasting
This project aims to develop forecasting models that balance accuracy with stability, minimising unnecessary changes in predictions that can disrupt operational decisions.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Energy Transition Centre
Multi-objective optimisation models for forecasting and decision-making in supply chains and energy systems
This PhD project will focus on developing and evaluating multi-objective optimisation models that simultaneously optimise forecasting accuracy and operational decisions in complex systems.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
AI-driven process redesign
This research aims to transform how organisations improve business processes by integrating artificial intelligence with real-time data. Existing process redesign approaches are often static, retrospective, and reliant on manual analysis. While process mining is commonly used to extract insights from historical data, these methods rarely incorporate AI models to support continuous, real-time process adaptation. As a result, they fall short of enabling intelligent, self-adaptive process management.This research addresses these limitations by proposing an AI-assisted, self-adaptive framework that combines historical and …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Object-centric process mining
Object-Centric Process Mining (OCPM) is an emerging paradigm in process analytics that addresses the limitations of traditional process mining by enabling the analysis of complex, multi-entity business processes. Unlike conventional approaches that focus on a single case notion (e.g., an order or a patient), OCPM allows for the simultaneous tracking and analysis of multiple interacting objects—such as orders, customers, products, and invoices—within a unified process model.This research project explores the theoretical foundations, algorithmic developments, and practical applications of OCPM. It …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
From digital design to human-robot collaborative masonry construction
This project addresses Queensland's critical housing shortage by exploring the productivity benefits of human-robot collaboration (HRC) in masonry construction. The research is conducted within the Building 4.0 CRC framework and leverages advanced facilities at QUT alongside industry partners such as Brickworks and the ARM Hub.By integrating collaborative robots (cobots), augmented reality (AR), parametric design tools (e.g. Grasshopper 3D), and AI algorithms, we aim to develop innovative workflows that enhance construction efficiency and material performance through the use of novel binders.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
- Research centre(s)
- QUT Resilience Centre
Reinforcement learning for fair and ethical AI systems
This project studies how reinforcement learning (RL) can help make automated decisions fairer. Instead of fixing fairness after training, fairness is built into the learning process to create more equal outcomes for different groups. The focus is on important areas like hiring, healthcare, and finance, where biased AI can cause real harm.The aim is to reduce unfair bias while keeping the system accurate, helping create AI that is both effective and socially responsible. You will learn about advanced RL methods, …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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
Digital twin in medical or sports context
Digital twins are virtual models of physical systems that use real-time data to mirror, simulate, and analyse behaviour. In medical and sports domains, they offer exciting opportunities for innovation.This project focuses on exploring these applications and aims to create digital twins to better understand and improve outcomes in these rapidly evolving fields.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Australia's urban and regional atmosphere: investigating influences on air quality
Global concern about urban air quality has been steadily increasing in recent years. However, most studies on the factors influencing air quality have focused on heavily polluted regions or locations in the Northern Hemisphere, where weather patterns, industrial activity, and vegetation differ significantly from those in Australia.Historically, urban areas in Australia have enjoyed relatively good air quality. Yet, rising population density, deforestation, and land use changes are placing increasing pressure on this status. Furthermore, the natural emissions from Australian vegetation …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
Regenerating bone following osteosarcoma tumour resection in a post-chemotherapy treated bone defect
Osteosarcoma (OS) is the most common primary bone cancer in children and adolescents. Standard treatment involves surgical resection of the tumour combined with systemic chemotherapy. While most patients undergo limb-sparing surgery to avoid amputation, this often results in significant morbidity and lifelong complications. These complications stem from the creation of large bone defects, poor healing outcomes, the need for revision surgeries, and long-term prosthetic failureThere is a critical clinical need for regenerative strategies that restore bone integrity and function following …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
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