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 65 matching student topics
Displaying 1–12 of 65 results
Using agricultural waste and organic amendments for sustainable agriculture and soil health
Optimising the application rates of organic amendments in agricultural soils is one of the most promising and practical solutions to reduce nitrogen (N) losses into the environment while maintaining an economically-adequate crop production.Organic amendments alone often don't meet the crop's needs. Consequently, a supplementary application of N synthetic fertiliser is needed in conventional farming systems to meet perceived production needs.Accounting for the amount of plant-available N (PAN) released by organic amendments and combining this with N-fertiliser will:ensure N demands of …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Biology and Environmental Science
- Research centre(s)
- Centre for Agriculture and the Bioeconomy
Atmospheric cooling and shading for the Great Barrier Reef
This research sits within the Cooling and Shading Subprogram of the Reef Restoration and Adaptation Program (RRAP).RRAP is an ambitious and innovative R&D effort that places Australia as the leader of coral reef adaptation and restoration science. It is a consortium of Partners, including QUT, dedicated to creating an innovative toolkit of interventions to help the Reef resist, adapt to, and recover from the impacts of climate change. These partners include the Australian Institute of Marine Science, CSIRO, the Great …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
- Research centre(s)
-
Centre for the Environment
Ecosystem responses to climate change and human impacts on sub-Antarctic islands: a context for conservation
Sub-Antarctic islands have unique ecosystems and landscapes under increasingly pressure from climate change. In many cases this is compounded by the introduction of invasive species since their discovery by humans in the 1800s.Understanding ecosystem and environmental responses to climate change and separating them from human-induced causes of change is essential for their future protection. To do this requires quantifying long-term, natural rates and variability of change, establishing the ‘baseline’ status of ecosystems and the environment prior to human arrival, and …
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Biology and Environmental Science
- Research centre(s)
-
Centre for the Environment
Scheduling of vessel movements in channel constrained ports
International trade is heavily reliant on maritime transportation which constitutes 80% of total volume. Ports have a significant impact on the efficiency of maritime transportation, with significant delays to vessels observed in accessing or departing ports. These delays can be a result of constraints on wharf capacity, channel capacity, access to tugs and pilots, or a combination of these factors. This project will focus on the development of novel operations research techniques to optimise the efficiency of scheduling vessel movements …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Identifying Indigenous contributions to knowledge
The Australian Census collects data every ten years to reflect who we are as a nation. But the data collected by the Census only tells part of our story.Indigenous people lived in Australia for thousands of years before the arrival of European settlers, accumulating a wealth of knowledge about Australia's land, climate, flora and fauna. Researchers have only begun tapping this knowledge as the basis for modern scientific research.This project will combine machine learning and text-analytics tools to develop a …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Process-data governance patterns
Data is recognised a strategic asset for organisations. There is a growing need to manage the voluminous data an organisation is exposed to in order to use it for decision-making.Of particular significance is process data, which consists of information about the execution of processes. Such information is used to uncover behaviour of processes within an organisation. This brings forth the significance of data governance. Data governance is the exercise of control and authority over management of data. Despite its significance, …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Unified def-site and use-site security policies for component-based software systems
Securing the information manipulated by computer systems, such as privacy and integrity in social software, is a challenge. Traditional methods to impose limits on the information disclosure, such as access control lists, firewalls, and cryptography, provide no guarantees about information propagation. For instance, cryptography provides no guarantees about the confidentiality of the data are given once it is decrypted.Information flow control (IFC) is the problem of ensuring secure information flow according to specified policies within computer systems. Modern applications are …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Productive reproducible workflows for deep learning-enabled large-scale industry systems
Deep learning is a mainstream to increase the capability of industry systems, particularly for those with massive data input and output. It is seen that many tools are now claimed to be freely available and could facilitate such process of development and deployment significantly with scalability and quality.However, limited attention has been on developing reproducible and productive workflows to identify the tools and their values towards large-scale industry systems. In this project, we will explore how to design such a …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Systematic evaluation towards the analysis of open-source supply chain on ML4SE tasks
Applying machine learning algorithms to source code related SE task is rapidly developing and attracts the attention from both researchers and industry engineers. While there are many program languages available, applying such techniques, i.e., the representation learning models, for different languages may achieve different performance. Particularly, they all have their own strict syntax, which determines the abstract syntax tree. Thus, a lot of different open-source supply chain are available, for example the parsing tools are used to build AST from …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Fine-grained software vulnerability detection using deep learning techniques
Software vulnerability is a major threat to the security of software systems. Thus, the successful prediction of security vulnerability is one of the most effective attack mitigation solutions. Existing approaches for software vulnerability detection (SVD) can be classified into static and dynamic methods. Powered by AI capabilities, especially with the advancement of machine learning techniques, current software has been produced with more sophisticated methodologies and components. This has made the automatic vulnerability proneness prediction even more challenging. Recent research efforts …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Automatic Generation of Software Vulnerability Datasets for Machine Learning
In recent years, machine learning has enjoyed profound success in a range of interesting applications such as natural language processing, computer vision and speech recognition. It has been possible mainly due to, in addition to better computing resources, the availability of large amounts of training datasets to these applications. However, in software security research, the lack of large datasets is an open problem that makes it challenging for machine learning to reason about security vulnerabilities found in real-world software. The …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Flexible thermoelectrics for wearable electronics
Advancements in miniaturisation and integration of electronics have recently stimulated the explosive progress in wearable electronics. With increasing practical needs, our analysis has indicated that the market values of wearable electronics are predicted to boost up to US$50B in 2022 and US$72B in 2026. Currently, conventional batteries have limited applications in wearable electronics due to their requirements of frequent replacement/recharge and extra-maintenance. This is especially true in temperature or pressure sensors in some circumstances such as remote-control smart home systems …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
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