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.

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Found 22 matching student topics

Displaying 1–12 of 22 results

Advanced artificial intelligence based ultrasound imaging applications

Our research in the space of advanced quantitative medical imaging is investigating how to use ultrasound as a real time volumetric mapping tool of human tissues, to guide in a reliable and accurate way complex medical procedures1. We have developed several novel methods which make use of the most cutting-edge artificial intelligence technology2. For example, to show where the treatment target and the organs at risk are at all times during treatments in radiation therapy3, 4; or to inform robots …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Clinical Sciences
Research centre(s)
Centre for Biomedical Technologies

Technology, Innovation and Health

Professor Belinda Bennett is interested in talking to students who wish to undertake research on legal issues related to technology, innovation and health, regulation of innovative health technologies, legal issues related to genomics, the use of artificial intelligence in health care, and the use of robotics in health care.

Study level
PhD, Master of Philosophy
Faculty
Faculty of Business and Law
School
School of Law
Research centre(s)

Australian Centre for Health Law Research

New technology and the law

Computer vision has developed to a point where machines using artificial intelligence are better and faster than humans at performing many vision-related tasks. For example, we are now often processed through customs based solely on face recognition software. Add to this the fact that the average Australian is photographed on CCTV cameras around 75 times per day. Commercial applications of face recognition technology include Microsoft's Face Application Programming Interface that can be used to classify face images based on gender, …

Study level
PhD, Master of Philosophy
School
null
Research centre(s)
null
null

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

Scene Understanding for Underwater Imagery

Underwater ecosystems, including coral reefs and seagrass meadows, play a critical role in maintaining marine biodiversity, providing coastal protection, and supporting fisheries and tourism economies that millions depend upon globally. These habitats are increasingly vulnerable to climate change, pollution, and other anthropogenic impacts, demanding urgent efforts to monitor and restore them. Accurate scene understanding of underwater imagery enables fine-scale ecosystem monitoring across spatial and temporal scales, supporting essential activities such as habitat and biodiversity assessment, validation of aerial and remotely …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics
Research centre(s)
Centre for Robotics

Bridging the gap: leveraging AI to improve healthcare access

Access to quality healthcare remains a significant challenge in many parts of the world, often due to geographic and financial barriers. This research explores how artificial intelligence (AI) can address the challenges of geographic and financial barriers in accessing healthcare. The project will focus on developing AI-powered solutions that enhance healthcare delivery, increase patient engagement, and reduce costs

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Public Health and Social Work

Enhancing clinical decision-making through AI-assisted agents

Artificial Intelligence (AI) has shown tremendous potential in revolutionizing healthcare delivery. This research focuses on developing AI agents that can augment clinical decision-making processes, ultimately improving patient outcomes. The project aims to explore and design novel AI architectures that integrate disparate medical data sources, providing context-aware recommendations for diagnosis, treatment planning, and care coordination. Despite the promising applications of AI in healthcare, significant challenges remain in integrating these technologies into clinical practice effectively and safely.

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Public Health and Social Work

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

Smart campus is an emerging concept following the smart city research movement and is predominantly argued to be a miniature replica of the smart city providing an ideal prototype for university campus development. The smart campus concept has attracted much attention, predominantly due to the rise in artificial intelligence, internet-of-things, cloud computing and big data applications in advancing university campus operation efficiency. In recent years, Australian universities started to invest in smart campus technologies and development opportunities.ReferenceA brief background on …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Architecture and Built Environment

Exploring the effects of interactions with intelligent agents in immersive systems

This research project aims to investigate the effects of interactions with intelligent agents on player experiences in various contexts, including videogames, learning-teaching, and complex data analysis. The intelligent agents will be developed using ChatGPT as a backend, and the studies will be conducted in both single-player and multiplayer settings, utilizing virtual and augmented reality technologies.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science

Improved data analytics for lithium ion batteries

Join the team to be part of an exciting QUT-lead project into materials for Lithium-ion batteries. The project is part of the Federally supported Future Battery Industries - Cooperative Research Centre, which hosts projects all-over the country that are aiming to boost the industry, create clean energy jobs, and enable a sustainable future.In this role you gain access to QUT's one-of-a-kind in Australia, Advanced Battery Facility. At the facility we build lithium batteries in a range of shapes and sizes. …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Chemistry and Physics
Research centre(s)
Centre for Materials Science
Centre for Clean Energy Technologies and Practices

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

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