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 178 matching student topics
Displaying 1–12 of 178 results
Facilitating gaining trust in AI
Artificial intelligence (AI) technologies are automating service delivery in many sectors. Businesses have shown interest in using these technologies for delivering complex services in a way that meet the unique needs of customers. The technology gained more popularity particularly during Covid-19 outbreak, as it helped organisations to become more efficient in service delivery and increased service availability for customers / service applicants. However, gaining managers’ and users’ trust in these systems has always been a significant challenge. Particularly, managers and …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
The Impact of AI on Leadership Roles and Structures
Examine how the introduction of AI technologies reshapes traditional leadership roles and organisational structures. Investigate the evolving nature of leadership in decentralised, AI-driven decision-making processes and explore how leaders can effectively adapt to new leadership paradigms.
- 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
Cybersecurity for open-source software using machine learning and AI
People are increasingly using open-source software in businesses and industries. These software programs are made by a community of developers and are managed by platforms like PyPI and npm. However, there is a worry about the safety of these programs because hackers add harmful code to compromise security and steal important data. This project explores approaches to detect harmful open-source projects using machine learning and AI.
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Driver engagement and risk in automated driving: Advanced data analytics leveraging driver monitoring systems
The project aims to the explore concept of empathic machines in the context of driver monitoring systems (DMS) and automated driving. The successful candidate will contribute to advancing the understanding of driver engagement, situation awareness, and risk through leveraging advancements in data science techniques on vehicle sensor, DMS, and other related datasets.To apply for this position, please submit the following documents:a cover letter outlining your research interests, relevant qualifications, and motivation to join the Empathic Machines projecta detailed curriculum vitae …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Data Science
Centre for Future Mobility
Development of a machine learning algorithm for high throughput cell response data in drug therapy
High-throughput screening assays are essential for accelerating drug discovery, but current assays often rely on endpoint measurements that do not capture the dynamic response of cells to drug treatment. Machine learning algorithms (MLAs) have the potential to enable real-time, high-throughput monitoring of cell response to drug treatment by analyzing complex datasets generated by multiplexed live-cell assays. This research project aims to develop an MLA for enabling high throughput cell response data in drug treatment. The project will involve three main …
- Study level
- Honours
- Faculty
- Faculty of Engineering
- School
- School of Computer Science
- Research centre(s)
- Centre for Biomedical Technologies
Centre for Biomedical Technologies
Ethical and Legal Implications of RPA and Enterprise Automation
Examine the ethical and legal implications of RPA/Enterprise Automation adoption in organisations. Research can focus on addressing issues such as data privacy, transparency, accountability, and the impact of RPA/Automation on human employment, culture, and structure.
- 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
Unveiling the explainability imperative in medical AI
As AI systems become increasingly prevalent in medical applications, the need for explainable AI (XAI) has become crucial. This research investigates the critical issue of explainability in medical artificial intelligence (AI) systems. This project investigates methods for improving the interpretability and transparency of AI models used in medical diagnosis, treatment planning, and prognosis prediction. Understanding the reasoning behind AI-driven decisions is essential for building trust among healthcare professionals and ensuring patient safety.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Health
- School
- School of Public Health and Social Work
Leveraging Big Data and AI/ML for Smart Transport Solutions
This PhD position aims to harness the potential of big traffic and mobility data alongside cutting-edge AI/ML algorithms to pioneer innovative solutions for optimizing smart motorways and/or arterial traffic flow. By leveraging these technologies, the project endeavours to develop and test smart algorithms, with the goal of significantly enhancing the efficiency and safety of road networks.Send via email to Prof. Ashish Bhaskar (ashish.bhaskar@qut.edu.au):a brief statement detailing your suitability for the positiona detailed curriculum vitae, including a list of publications, if …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Data Science
Basic aircraft collision risk modelling and visualisation
Aircraft collision risk modelling is complex yet key to ensuring safe air transport (both crewed and uncrewed aircraft). Different collision risk models are better suited to different airspace environments which means model comparison and evaluation is an important research problem. This project takes a deeper look into a specific collision risk modelling approach: gas models.
- Study level
- Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
- Centre for Robotics
AI-Based Data Analysis on Multiple Imaging Modalities
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. According to the World Health Organization (WHO), it is estimated CVD takes 17.9 million lives every year. In Australian, the statistical data from the Australia Heart Foundation shows CVD is a major cause of death in Australia. It occupies 26% of all deaths, responsible for an average 118 deaths every day. Four of the main types of CVD are coronary heart disease, strokes and transient ischaemic attack, peripheral …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Data reasoning to extend domain knowledge in deep learning
A wide variety of companies now use personalized prediction models to improve customer satisfaction, for example, detecting cancer relapses, Detecting Attacks in Networks (e.g., SDN) or understanding Customer Online Shopping Behaviour. However, the dramatic increase in size and complexity of newly generated data from various sources is creating a number of challenges for domain experts to make personalized prediction.For example, early detection of cancer can drastically improve the chance and successful treatment. Recently, supervised deep learning has brought breakthroughs in …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Investigating community advocacy in response to aircraft noise pollution in Brisbane: an ethnographic study
The flight path design and community engagement practices associated with Brisbane Airport have long been criticised for prioritising profit over community wellbeing, leading to excessive aircraft noise pollution. These issues have now amounted to a federal Senate Inquiry and an investigation by the Commonwealth Ombudsman.This PhD research project aims to explore the dynamics between Brisbane Airport and the affected residential communities across more than 220 suburbs, drawing inspiration from a similar study conducted into the social engineering practices of Schiphol …
- 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
Contact us
If you have questions about the best options for you, the application process, your research topic, finding a supervisor or anything else, get in touch with us today.