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 1–12 of 17 results
Hierarchical visualisation of large social networks
Networks have been extensively used to capture social interactions, by representing individuals as nodes and their relationships as edges.Such networks have been used to model the spread of epidemics. A few nodes are 'infected', and over time they gradually infect their neighbours on the network, who in turn infect their neighbours, etc. This type of model can then be used to simulate different intervention strategies aimed at containing outbreaks.However, an important limitation is the difficulty to visualise these networks when …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Trust in Internet-of-Things with blockchain
Blockchain is an unchangeable, distributed database that provides trust in data once it is stored on the database. However, in Internet-of-Things (IoT), the data is an observation of physical context and is susceptible to noise, drift, or malicious alterations. Sensors may even be decoupled from their intended context by an attacker, which may compromise the blockchain data and its value for guiding decisions.This project aims to develop an innovative approach for pervasive trust in IoT, underpinned by blockchain. The research …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Representation learning for anti-microbial resistance
This project is about using neural network models help us understand Anti-Microbial Resistance (AMR), a phenomenon in which bacteria adapt to reduce the effectiveness of antibiotics, usually through a process known as Lateral or Horizontal Gene Transfer - where genes are included in the organism from other sources.Our focus will be on learning compact vector representations of biological sequences known to be associated with AMR genes. By encoding DNA sequences in this way we can more rapidly identify AMR genes …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Board interlocks and firm decisions
Board interlocks research is one of the most vibrant areas in corporate governance research. A board interlock is a tie created by two firms sharing a common director. In other words, a director can hold multiple directorships in more than one firm. Board interlocks reflect complex inter-organisational relationships which play an important role in determining a firm’s strategies and structures.Prior research finds that board interlocks have an impact on reducing environmental uncertainty, gaining access to diverse and unique information, diffusing …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Business and Law
- School
- School of Accountancy
Optimising bone shape with memory networks
Bone is a dynamic tissue that optimises its shape to the mechanical loads that it carries. Bone mass is accrued where loads are high, and reduced where loads are low. This adaptation of bone tissue to mechanical loads is well-known and observed in many instances. However, what serves as a reference mechanical state in this shape optimisation remains largely unknown.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
Modelling student engagement and success using Bayesian networks
This PhD project investigates how academic, wellbeing, family, and school-context factors interact to shape student engagement, retention, and academic success in secondary schooling. Using large-scale longitudinal datasets, the project will develop advanced probabilistic models to identify key predictors and pathways that explain diverse learner trajectories.The research will contribute to evidence-based strategies for improving student engagement and reducing attrition, with strong relevance to policy and practice in Australian and international contexts.This project builds on ongoing work applying advanced statistical modelling to …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Education
Road map to local circular communities: strategies, barriers, enablers.
The textile industry is one of the world’s largest, with global sales in 2016 of USD 1.5 trillion. It is also one of the most polluting industries, producing 20% of global wastewater, and contributing to 10% of carbon emissions. Fashion generates large amounts of waste, and has negative social and health impacts for workers.Circular economy would address these issues, keep clothes and textiles at their highest value and keep clothes in continuous circulation. The transformation of the sector requires a …
- Study level
- PhD
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
-
Design Lab
Physics-informed reinforcement learning for complex environments, using graph neural networks
Neglecting to incorporate physics information into world models for reinforcement learning leads to reduced adaptability to dynamic and complex environments and overall learning outcomes.In this project, we endeavour to develop and implement learnable models in reinforcement learning (RL) based on graph neural networks (GNNs). These models will integrate object and relation-centric representations to enable accurate predictions, strong generalization, and system identification in complex, dynamical systems. Additionally, we will focus on leveraging extensive world knowledge or physics information to refine representations …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Network Flow Improvement
Network flow is impeded by the arcs present in the network and their associated length/weighting. Arcs can be added or removed to debottleneck the network. But which ones? At what cost?
- 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
Understanding cellular-spatial interplay between osteocyte networks and their environment using bioengineered 3D bone models
Project Reference: #1MPQC-NATP1Preferred Project Start: ImmediateHow do bone-forming cells communicate to build and maintain a functional bone matrix?Osteoblasts produce new bone extracellular matrix, while osteocytes become embedded within this matrix and form an interconnected network that helps regulate bone formation, adaptation and remodelling. Although these cells work closely together in the body, their interactions are difficult to reproduce and investigate using conventional two-dimensional cell culture.Bone-cell behaviour is strongly influenced by the surrounding microenvironment, including its composition, mechanical properties, mineral content, …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
Machine learning for power quality analysis in low-voltage distribution Networks
Two full PhD scholarships are available at Queensland University of Technology (QUT), Brisbane, Australia, focusing on machine learning for power quality analysis in low-voltage distribution networks.These PhD projects are part of an Industrial Transformation Training Centre (ITTC), providing students with access to a strong interdisciplinary research environment and collaboration opportunities with leading academic researchers and industry partners.The projects will investigate how solar inverters and electric vehicle (EV) chargers affect harmonic distortion, impedance, and resonance behaviour in the 2–9 kHz range. …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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