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.

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Found 241 matching student topics

Displaying 109–120 of 241 results

Continuous time samplers (MCMC at the limit!)

The goal of this project is to develop new continuous time Monte Carlo methods for efficient sampling from high-dimensional distributions. Continuous-time Monte Carlo methods are a class of algorithms that use continuous-time dynamics to generate samples from target distributions, rather than the discrete-time dynamics used in traditional Markov chain Monte Carlo (MCMC) methods. These methods have been shown to have faster mixing and better exploration of the state space, making them particularly appealing samplers for challenging distributions.The main objectives of …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Unlocking the Potential of Simplex-Truncated Distributions

This PhD project aims to develop new methods for generating random samples from a specific type of probability distributions called simplex-truncated distributions. These distributions are commonly used in various fields such as statistics, machine learning, and biology.The project will involve the development of new techniques to generate random samples from simplex-truncated distributions. These techniques are based on a method called continuous-time Monte Carlo which is a cutting edge method in statistics that can generate random samples from complex distributions.The main …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Low-cost portable Magnetic Resonance Imaging for clinical applications

The aim of this project is to develop accurate low-cost medical imaging methodology for pseudo-3D mapping of Mammographic Density (MD) within the breast. MD is the degree of radio-opacity (“whiteness”) in an X-ray mammogram. It has implications for breast cancer risk, ease of detection of breast cancer, and monitoring of the efficacy of hormonal breast cancer prevention or anti-cancer treatments.Healthcare ChallengeThere is a growing need for affordable and accurate quantitative assessment of MD without ionising radiation. Magnetic resonance imaging (MRI) …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Chemistry and Physics

Genome to phenome: exploiting multi-omics and deep learning strategies to decipher importance of isoforms in health and behaviour

The molecular process that leads to multiple mRNA transcripts being produced from the same segment of DNA (aka gene) is known as alternative splicing (AS). This is a common form of regulation in higher eukaryotes, enabling the production of novel protein isoforms, which in turn are known to have a big impact on phenotype. Understanding the regulatory factors involved in AS, including epigenetic mechanisms such as DNA methylation, will offer key insights into important biological phenomena (health disease, behaviour, production). …

Study level
PhD
Faculty
Faculty of Science
School
School of Biology and Environmental Science

Prescriptive process analytics

With growing significance of data there is a need to harness the potential of that data for improved business operations. Historical data is often to provide a descriptive overview of how business processes have performed in the past. However, there is a need to be proactive and take appropriate actions to ensure that business processes perform in an optimal manner. Prescriptive analytics is a process that analyzes data and provides instant recommendations on how to optimize business practices. Prescriptive analytics …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems

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

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