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 468 matching student topics
Displaying 205–216 of 468 results
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
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
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
Bushfire design of residential buildings
This project aims to investigate the bushfire performance of residential buildings in the bushfire-prone areas of Australia. This includes a detailed review of:bushfire characteristicsradiant and convective heat ratestype of materials used to construct bushfire safe housesstructural and fire performance of external wall and roof panelsstructural and architectural building design requirementsThis comprehensive review will contribute towards developing conceptual models and design methods for external wall and roof systems for residential buildings in bushfire zones.
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Materials Science
Changing the world with augmented creativity
We're seeking brilliant and highly motivated students to work on an Australian Research Council-funded project.Our goal is to transform augmented reality (AR) from a hyper-specialised tool for power users, into an enabler of creativity, socialisation, and new forms of community.We will reimagine augmented reality, from the current hyper-specialised tool for power users, into an enabler of creativity and imagination. We seek to engage with artists, designers, musicians, to explore new forms of creativity, art, and performance.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
AI-Based Data Analysis on Multiple Imaging Modalities
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. According to the World Health Organization (WHO), it is estimated CVD takes 17.9 million lives every year. In Australian, the statistical data from the Australia Heart Foundation shows CVD is a major cause of death in Australia. It occupies 26% of all deaths, responsible for an average 118 deaths every day. Four of the main types of CVD are coronary heart disease, strokes and transient ischaemic attack, peripheral …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Data reasoning to extend domain knowledge in deep learning
A wide variety of companies now use personalized prediction models to improve customer satisfaction, for example, detecting cancer relapses, Detecting Attacks in Networks (e.g., SDN) or understanding Customer Online Shopping Behaviour. However, the dramatic increase in size and complexity of newly generated data from various sources is creating a number of challenges for domain experts to make personalized prediction.For example, early detection of cancer can drastically improve the chance and successful treatment. Recently, supervised deep learning has brought breakthroughs in …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Predicting alternative states induced by multiple interacting feedbacks: seagrass ecosystems as a case study
This project seeks to explore the complex dynamics that might arise from multiple interacting feedbacks in marine ecosystems, by designing ordinary and/or partial differential equation models of these feedbacks and analysing the steady states and/or temporal dynamics of the proposed model(s).It has been hypothesised that many social and ecological systems exhibit alternative stable states due to feedback processes that keep the ecosystem in one state or the other. The result can be tipping points, which are difficult to predict but …
- 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
Virtual leaves: from data to surfaces and the steps in-between
Like all industries, agriculture is benefiting from the data and computing revolution. Using hand-held scanners, CT scanners, or other technologies, we can acquire data sets that represent real leaves of agricultural crops, e.g. wheat. Using this data, and performing many intermediate steps, we can build virtual leaf surfaces that can be used in computer models to perform simulations of droplet impactions, spreading, evaporation, and other phenomena of interest to the industry.This project concerns the 'many intermediate steps', for which there …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Tree-chain: a fast lightweight consensus algorithm for IoT applications
In recent years, blockchain adaptation in IoT has received tremendous attention due to its salient features including distributed management, security, anonymity, and auditability. However, conventional blockchains are significantly resource demanding and suffer from lack of throughput, delay in committing transactions, and low efficiency. We recently introduced a novel blockchain consensus algorithm known as Tree-chain, that bases the validator selection on an existing feature in all blockchains: hash function. Tree-chain achieves a fast throughput while ensuring the randomness and unpredictability of …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Computer Science
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