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 479 matching student topics

Displaying 109–120 of 479 results

Exploring the potential of M-assisted survey estimators

The Australian Bureau of Statistics (ABS) conducts surveys to collect information from individuals, households and businesses in order to produce statistics and data products to help inform decision-making. Unlike a census, in which an entire population of interest is enumerated (e.g., all individuals residing in Australia), a survey collects information from only a sample (subset) of a population of interest. Estimators are then used to estimate quantities related to the population of interest using information from the sample. Currently, the …

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

Developing and evaluating an evidence-based and practical system approach to reduce surgical site infections

A surgical wound is an incision in the skin that is made during a surgical procedure and generally expected to heal within two to four weeks by primary intention in an orderly manner through the normal wound healing process. However, this process can be disrupted by many factors, leading to complications such as wound dehiscence, non-healing wounds, surgical site infections and sepsis. On average, there are 11 surgical wounds infected for every 100 surgical wounds and these surgical site infections …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Nursing
Research centre(s)
Centre for Healthcare Transformation

Assessing the quality of cluster analysis

Machine learning cluster methods are common classification methods, but methods for assessing performance are limited as are methods for explaining how they work. Exploring methods for both assessing and explaining performance are the subject of this research with application to real-world contexts with the Australian Bureau of Statistics.

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

Explainability of outlier detection methods

Outliers are anomalous observations in a data set that are "outside the norm" of what would be expected. Identifying outliers is an important part of exploratory data analysis and data analysis in general. It is often a challenging problem and calls for advanced methods and approaches, including machine learning-based tools. As methods become more and more complex, their explainability becomes more difficult and more important. This research project will look at all aspects of explainability and explore new approaches and …

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

Facilitating Towards Sustainable Electric Vehicles Trading System

The number of Electric Vehicles (EVs) on the road is expected to reach 145 million by 2030. As the number of EVs on the road increases, the demand for energy to charge these vehicles also grows. Traditional charging infrastructure may not meet the increasing energy demands, which may lead to increased waiting time in those charging stations. The EV-EV trading scheme is a promising solution that allows EV owners to access additional energy from nearby EVs. This scheme has attracted …

Study level
Honours
Faculty
Faculty of Science
School
School of Information Systems

Real-time Business Process Integration in the Industrial Internet of Things (IIoT) for Industry 4.0

The vision of Industry 4.0 is to support business capabilities at the edge. The Industrial Internet of Things (IIoT) enables this vision by integrating IoT with Enterprise Systems (ESs). In an IIoT process, sensor applications at the edge require seamless integration with the software services of ESs. This, in turn, facilitates the real-time correlation of sensor events with BPs. However, existing IIoT architectures lack the necessary architectural capabilities to reflect the true essence of Industry 4.0.This research aims to develop …

Study level
Honours
Faculty
Faculty of Science
School
School of Information Systems

Identifying novel pheno-endotypes in children with chronic cough

Chronic wet cough is among the commonest symptoms of chronic lung disease. In Australia, the most common cause of childhood chronic wet cough is protracted bacterial bronchitis (PBB), a clinical entity we first described. It has now been shown to be a precursor to bronchiectasis, which causes substantial morbidity and mortality, especially from acute respiratory exacerbations. Lung inflammation in children with persistent chronic wet cough is an important driver of ongoing and progressive tissue damage, leading to bronchiectasis, highlighting the …

Study level
PhD
Faculty
Faculty of Health
School
School of Public Health and Social Work
Research centre(s)
Centre for Healthcare Transformation
Australian Centre for Health Services Innovation

Making predictions using simulation-based stochastic mathematical models

Stochastic simulation-based models are very attractive to study population-biology, disease transmission, development and disease. These models naturally incorporate randomness in a way that is consistent with experimental measurements that describe natural phenomena.Standard statistical techniques are not directly compatible with data produced by simulation-based stochastic models since the model likelihood function is unavailable. Progress can be made, however, by introducing an auxiliary likelihood function can be formulated, and this auxiliary likelihood function can be used for identifiability analysis, parameter estimation and …

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

Assessing visual acuity errors in pre-school children (CVER01)

Measuring visual acuity is in preschool children is challenging. In particular, young children will be prone to making mistakes in identifying symbols on eye charts, even when they can see what those symbols are, so called “false negative responses”.This project uses an established vision assessment protocol, EVA testing, and assesses the extent of false negative responses in this task. The protocol assesses the effects of an intervention, pointing to the target on a card, which may decrease false negative responses. …

Study level
PhD
Faculty
Faculty of Health
School
School of Clinical Sciences
Research centre(s)

Centre for Vision and Eye Research

Scalable Bayesian Inference using Multilevel Monte Carlo

Bayesian inference is a popular statistical framework for estimating the parameters of statistical models based on data. However, Bayesian methods are well known to be computationally intensive. This fact inhibits the scalability of Bayesian analysis for real-world applications involving complex stochastic models. Such models are common in the fields of biology and ecology.Multilevel Monte Carlo (MLMC) methods are a promising class of techniques for dealing with the scalability challenge. These approaches use hierarchies of approximations to optimise the trade-off between …

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

Wound care in regional/rural Queensland

Barriers to health care for regional/rural residents often relate to the limited availability of local health services and resources and the distance needed to seek suitable specialised services. Wounds experienced in rural and regional areas are often dependent upon the types of employment available, recreational pursuits and risk-taking behaviours.The prevalence of non-communicable lifestyle related risk factors (such as obesity and poor nutrition) and the propensity for an ageing population in rural and regional areas, positions this population group as one …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Nursing

Building metallo-supramolecular cages for sensing and catalytic applications

The concept of creating molecular electronic devices has resulted in the development and rapid advance of the field of supramolecular chemistry.In this project we are particularly interested in how we can use simple building blocks to self-assemble into complex, functional structures both in solution and at the solution:surface interface.These types of structures have shown great promise in applications such as catalysis, sensing, drug delivery and even in the development of molecular machines.AimsThis project aims to:design, synthesise and characterise complex metallo-supramolecular …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Chemistry and Physics
Research centre(s)
Centre for Materials Science

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