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 17 matching student topics
Displaying 13–17 of 17 results
A new physics informed machine learning framework for structural optimisation design of the biomedical devices
The machine learning based computer modelling and simulation for engineering and science is a new era. The optimisation analysis is widely used in the design of structures.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Centre for Biomedical Technologies
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
Sensor network optimisation for illicit discharge detection in stormwater systems
Illicit discharges into stormwater networks threaten waterways, but current detection methods are often inefficient. This project develops a smart sensor network to identify and locate pollution sources in real time. The PhD will focus on:optimal sensor placement: algorithms for location, type, and density selectionreal-time alarm systems: fast, reliable detection to trigger inspections or robotic trackingscalability: cost-effective strategies for city-wide deployment.
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
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
My flow: Menstrual cycle Femtech for elite athlete performance optimisation through wearable technology
There is a need for additional studies to monitor on-field performance parameters in female elite athletes (Meignié 2021). We know that wearable sensors can be used to monitor the physiological and biochemical profile of athletes (Seshadri 2019), and a combination of several wearables is going to be more effective for accessing all relevant parameters (Düking 2016). However, there is limited research on the effects of menstrual cycle phases on elite athlete performance (Meignié 2021).This proposed research aims to bridge the …
- Study level
- PhD
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
-
Design Lab
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