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 219 matching student topics
Displaying 121–132 of 219 results
Data-informed decision-making in education systems
This project explores how advanced statistical modelling can support decision-making in complex education systems. It focuses on modelling uncertainty, interdependencies, and policy-relevant insights to guide planning and practice.The project aligns with research applying Bayesian networks to real world decision-making under uncertainty across infrastructure, health, and education contexts
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- 1043176
Automation/RPA in Healthcare
Investigate the potential applications of RPA/ Process Automation in the healthcare sector. Explore how RPA/Process Automation can streamline administrative tasks, improve patient data management, enhance healthcare delivery processes, and support clinical decision-making. Address the challenges and opportunities of implementing RPA in highly regulated environments like healthcare.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Human-Robot Collaboration
Study the dynamics and challenges of human-robot collaboration in the context of RPA and Business Process Automation. Explore ways to design collaborative interfaces, communication protocols, and decision-making frameworks that enable seamless interactions between human workers and automation robots (RPA), leading to efficient and effective task completion.
- 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
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)
-
Centre for Behavioural Economics, Society and Technology
Citizen-developers: challenges and opportunities for low-code/no-code automation
Robotic Process Automation (RPA) is becoming a popular choice for organisations to support their digital transformation and to maintain operational resilience. Many organisations are keen to adopt Robotic Process Automation (RPA) to dramatically improve operational efficiency. Many organisations train and assign their staff as “citizen-developer” to design, test, and maintain the bots using Low-Code/No-Code platforms. However, there are number of issues surfaced when using organisational employees as citizen developer ranging from technical & process capabilities to scalability of RPA.
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
The dark side of robotic process automation
Pandemics such as COVID 19 have forced organisations to pursue hyper-automation to maintain operational sustainability. Many organisations are keen to adopt Robotic Process Automation (RPA) to dramatically improve operational efficiency. However, evidence to date highlighted various associated challenges associated with adoption of RPA in organisations.Furthermore, recent surveys by consultant organisations found a high RPA project fail rate and their inability to meet the expected return on investment.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Future Enterprise
Alleviating corruption: a data driven perspective
Corruption is cited as among the greatest challenges faced by government and citizenry the world over and threatens to undermine the very trust that is essential for a functioning democratic society. In order to earn and maintain public trust, governments at all levels must continuously strive to reduce corruption and uphold the highest levels of integrity.Amidst the countless human interactions and electronic transactions that occur within the public service on a daily basis are a complex and ever-changing variety of …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Leadership and digital transformation
Digital transformation and digitalisation are on top of the CIOs' agenda. However, organisations embarking into these initiatives struggle to understand the nature of leadership capabilities required for effective DT. Furthermore, the complexities associated with pandemics such as Covid19 has forced organisations to change the traditional view of leadership. The uncertainties require well-rounded leaders who can create vision and execute tactically to influence change, develop digital capabilities and foster enterprise agility.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
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
Local drug delivery to prevent osteosarcoma recurrence and metastasis
Osteosarcoma (OS) is the most common primary bone cancer in children and adolescents. Despite aggressive treatment involving multi-agent chemotherapy and wide surgical resection, survival outcomes remain poor, with five year survival as low as 13% for patients with metastatic or recurrent disease. Current treatment relies heavily on systemic chemotherapy, which is associated with significant toxicity and long-term side effects, including cardiotoxicity, nephrotoxicity, and impaired growth and fertility. Local recurrence occurs in up to 30% of patients after surgical resection, often …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
Exploring the accessibility needs of visually impaired peer workers in digital employment support platforms
This project will explore how blind and visually impaired (VI) peer workers use digital platforms in their day to day practice, with the aim of identifying or co-designing a platform that is accessible, JAWS compatible and aligned with the requirements of industry partner Chapter1’s peer-led employment services.
- Study level
- Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Fine-grained software vulnerability detection using deep learning techniques
Software vulnerability is a major threat to the security of software systems. Thus, the successful prediction of security vulnerability is one of the most effective attack mitigation solutions. Existing approaches for software vulnerability detection (SVD) can be classified into static and dynamic methods. Powered by AI capabilities, especially with the advancement of machine learning techniques, current software has been produced with more sophisticated methodologies and components. This has made the automatic vulnerability proneness prediction even more challenging. Recent research efforts …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
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