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 8 matching student topics
Displaying 1–8 of 8 results
Genetics of cardiovascular disease
This research project involves investigating the genetic basis of cardiovascular disease (CVD). The project will focus on the genetically unique population of Norfolk Island. The Norfolk Island Health Study has been running for 20 yrs. Over this time the cardiovascular health of the Islanders has been tracked via the collection of relevant clinical data. In addition whole genome sequence data from the study group has been collected, which will facilitate the discovery of genetic variants that influence CVD phenotypes - …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
- Centre for Genomics and Personalised Health
Computational methods for multi-scale structural optimisation
Structural optimisation is a powerful computational methodology for finding high-performing designs for structural components or material architectures. For example, what periodic scaffold would provide the highest possible stiffness for its weight?Solving such a problem computationally requires an understanding of the relevant equations required to model the physical properties of interest, as well as efficient implementation of a range of numerical methods including finite elements, finite differences and optimisation.With recent developments in 3D printing technologies it is now becoming possible to …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Power efficient computing for statistical machine learning
The carbon footprint of computing globally is estimated to be comparable with that of the aviation industry. With the advent of generative artificial intelligence, there is a growing awareness of this environmental impact both in terms of the carbon footprint and other environmental impacts including e-waste and water consumption, predominantly through the use of power-hungry graphics processing units (GPUs).These are particularly relevant issues to many fields that rely on computationally intensive simulations for data analysis or calibration of statistical machine …
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Strengthening security for cloud computing applications
In today's digital landscape, applications are increasingly being deployed on cloud platforms, offering benefits such as streamlined management and cost-effectiveness. However, even with the efforts of cloud providers to deliver reliable services, the risk of runtime failures and faults still exists. This project aims to address this challenge by exploring innovative approaches to detect and mitigate errors that occur during the operation of cloud-based applications. By proactively identifying and resolving runtime issues, we can enhance the overall performance, reliability, and …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Quantum machine learning
Quantum machine learning is the integration of quantum algorithms within machine learning programs with great potential to solve complex problems. For instance, Google’s Sycamore processor (61) performs in 200 seconds a task that would require 10,000 years using a classical computer.
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Leveraging AI-driven cognitive computing for energy systems innovation
The transition toward a more sustainable energy system is generating vast volumes of data from distributed sources such as smart meters, energy sensors, and user-end devices. Energy informatics highlights the crucial role of information systems in optimising both energy supply and demand (Watson et al., 2010). In this project, we explore how cognitive computing systems (CCS), integrating artificial intelligence (AI), cognitive psychology, and neurobiology, can strategically transform energy informatics by creating adaptive, explainable, and human-aligned energy solutions.Leveraging advances in CCS …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
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Energy Transition Centre
Optimisation of piezoelectric materials for robotics applications
Piezoelectricity, which translates to “pressure electricity”, is the phenomenon in which certain materials convert mechanical energy to electrical energy, and vice versa. Such materials are common-place and are used in a variety of applications including sensor, actuator, and energy harvesting technologies. The capabilities of such piezoelectric materials have not yet been fully realised. We plan to use computational structural optimisation to design new piezoelectric materials and components that may contribute to novel sensing technologies for robotics applications. Essentially, robots need …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Reconciling competing perspectives of mathematics in teacher education
This project explores how pre-service teachers experience and reconcile competing conceptions of mathematics, such as mathematics as a formal discipline versus a pedagogical practice. These tensions can shape teaching approaches and classroom environments.The project will investigate how teacher education programs influence these perspectives and how pre-service teachers develop coherent professional identities.
- Study level
- PhD
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
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