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 494 matching student topics
Displaying 205–216 of 494 results
Augmented reality interfaces for autonomous vehicles
We're seeking brilliant and highly motivated students to work on an project seeking to improve the accessibility and usability of automated vehicles for disadvantaged users.Automated Vehicles are often touted as a solution to enable mobility for older users and people with disabilities, but these user groups are rarely included in their design. As a result, current developments are largely focused on the needs and skills of affluent, younger users, and ironically risk to further marginalise, instead of empowering, those who …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Two dimensional heterostructures on SiC for new electronics
The present electronic technology is approaching the limit to the smallest circuit element achievable, and the future electronic devices will depend critically on the development of novel approaches. Two dimensional materials seem to offer an exciting perspective, and the advent of graphene (a single layer of carbon atoms in a honeycomb structure) sparked a huge interest, but its application to electronics are limited by the absence of a band gap.A new perspective has been open by other 2D materials which …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
Visualisation of CRISPR targets
CRISPR-Cas9 technology allows us to modify virtually any gene in any organism of interest. It has generated a lot of interest, both in the research community and the general population.One of the crucial components of CRISPR experiments is the design of the 'guide RNAs' that will control where modifications occur.We have developed a software pipeline, named Crackling, to identify safe and effective guide RNAs across entire genomes. We're now seeking to develop a visualisation to communicate the results produced by …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Understanding and manipulating bacterial motility for infection control (PhD)
The recent COVID 19 pandemic reminds us of how difficult it is to control infectious diseases. Pathogenic microorganisms are known to be extremely 'smart' and are able to quickly develop mechanisms against most of our strategies aimed at eradicating them. Our group is focused on bacterial infections to implants and medical devices. We are in the pursuit to outsmart the bacteria to develop the next generation medical device and implant materials.Bacterial motility/movement and group-coordination on surfaces and in 3-dimensional environment …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Developing predictive models, methods and analytics for complex sports data
A 3-year strategic partnership on sports data science between the Centre for Data Science (CDS), the Australian Institute of Sport (AIS) and the Queensland Academy of Sport (QAS) was launched in the past few months. With a drive towards data informed decision making across the high performance sports network nationally, a number of collaborative, interdisciplinary research and scholarship opportunities ranging from VRES, to honours, masters and PhD have developed.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Mathematical modelling of ecosystem feedbacks and value-of-information theory
Ecosystems respond to gradual change in unexpected ways. Feedback processes between different parts of an environment can perpetuate ecosystem collapse, leading to potentially irreversible biodiversity loss. However, it is unclear if greater knowledge of feedbacks will ultimately change environmental decisions.The project aims to identify when feedbacks matter for environmental decisions, by generating new methods that predict the economic benefit of knowing more about feedbacks. Combining ecological modelling and value-of-information theory, the outcomes of these novel methods will provide significant and …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for the Environment
Addressing security challenges for the industrial internet of things
With the emergence of the Internet of Things (IoT) and Industry 4.0, there is a trend for applying these services and applications to a large-scale industrial area. The IoT paradigm has changed the way of interactions with the things that surround us. In essence, the IoT promises ubiquitous connection to the Internet, turning common objects into connected devices. It is predicted that there will be 50 billion connected devices at the end of the year 2022.Over the last few years, …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Optimal ecosystem management in rapidly changing systems
Delays in acting in collapsing ecosystems can be catastrophic. With every passing year, the chances that the ecosystem has progressed past some point of no return increases. Yet the research and development needed to develop a new technology can take a long time. Balance between these two dynamic processes is needed to determine the optimal length and effort for developing new technologies. This project will develop a method for finding the optimal schedule for developing technological readiness, social acceptability, a …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for the Environment
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
Modelling and managing uncertain Antarctic species networks
Antarctic ecosystems are complex, and data is limited since it is expensive to collect. Species interact in food webs which can be modelled as mathematical networks. The relationships between species are not always known, or we might know they interact but not how strongly. Noisy (or imperfect) data can be used to model these species interactions to give more certainty about how the ecosystem works as a whole – although the worse the data is, the less information it contributes. …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for the Environment
Conservation is a noisy business: modelling the effects of stochasticity on wildlife management decisions
To conserve species in disturbed natural environments, we need to use mathematical models to predict the consequences of different interventions. Unfortunately, these models are based on partial information of complex systems, and the systems themselves are subject to substantial observational and process noise.We often use ordinary differential equations to describe ecosystems, like the classic logistic growth model:dn/dt = r n (1 - n / k)However, these models are deterministic, and they assume we know the values of the key parameters …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for the Environment
Semantic-based source code embeddings for software vulnerability discovery
Operational Technology (OT) is a field of computing which is becoming increasingly prominent in modern society. It is responsible for a variety of critical services, especially in industrial contexts, including power generation, manufacturing, transport, and many others. This important role makes OT an especially tempting target for malicious attackers. In order to counter this, tools must be developed to locate vulnerabilities and flaws in OT software systems before attacks can be launched. Vulnerability discovery in computer software systems including OT …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
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