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.

Filter by faculty:

Found 207 matching student topics

Displaying 25–36 of 207 results

Investigating factors impacting urban heat vulnerability in subtropical cities

In recent years, with the rise in climate change impact, urban heat has become a major issue for many cities to tackle consequently. Extreme heat events are becoming more frequent and intense due to climate change, which has directly caused a substantial increase in heat-related morbidity and mortality. This indispensably puts an extra burden on medical systems and national finance. Meanwhile, the urban heat island effect has been exaggerating the consequences caused by the increased extreme heat in metropolitan areas. …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Architecture and Built Environment

Security analysis of open-source software

Several open-source projects drive modern-day IT applications. However, some open-source projects get compromised by malicious attackers, who include malware to the code to compromise the security of the application users.This project will investigate approaches for securing the open-source software.

Study level
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

Co-benefits of trees on farms: soil carbon

Soils are now in the ‘front line’ of global environmental change. Soils are the largest global pool of actively cycling organic C and N. Maintaining and increasing soil organic matter (SOM) is a prominent strategy for mitigating atmospheric CO2 and adapting agriculture to climate change.At the same time the global biodiversity crisis has led to increased scrutiny on supply chains to scrutinise farms ecological footprint. Planting or retaining trees in the landscape has the opportunity to achieve both outcomes, however …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Biology and Environmental Science
Research centre(s)
Centre for Agriculture and the Bioeconomy

Explainable AI-enabled predictive analytics

Modern predictive analytics underpinned by AI-enabled learning (such as machine learning, deep learning) techniques has become a key enabler to the automation of data-driven decision making. In the context of process monitoring and forecast, predictive analytics has been applied to making predictions about the future state of a running process instance - for example, which task will be carried out next, when and who will perform the task, when will an ongoing process instance complete, what will be the outcome …

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

Representation learning for anti-microbial resistance

This project is about using neural network models help us understand Anti-Microbial Resistance (AMR), a phenomenon in which bacteria adapt to reduce the effectiveness of antibiotics, usually through a process known as Lateral or Horizontal Gene Transfer - where genes are included in the organism from other sources.Our focus will be on learning compact vector representations of biological sequences known to be associated with AMR genes. By encoding DNA sequences in this way we can more rapidly identify AMR genes …

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

Scalable software solutions for improving the CRISPR gene editing system

The CRISPR-Cas9 technology allows the modification of 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 are seeking to expand and improve various aspects of our current …

Study level
Honours
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

Simulation of turbulent fluid flow through a microfluidic device using CFD

Microfluidic devices (MFD) are extensively used in microbial studies. Bacterial cell attachment onto surfaces under flow conditions in laminar regime has been previously studied using a custom designed MFD.As an extension of this study, microbial attachment under turbulent flow is to be studied in a future project. The suitability of current MFD for microbial studies under turbulent flow must be evaluated to adopt / redesign the MFD.A computational fluid dynamics (CFD) analysis is proposed to examine the fluid flow inside …

Study level
Honours
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering

Sport AI

Videos of sport activities are widely available at large scales. AI and its sub-fields, especially computer vision and machine learning, have a great potential to analyse, understand and extract useful information from these videos.This project aims at using AI and its subfields in computer vision and machine learning to develop techniques for analysing sport videos to extract intelligence for players and coaches.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Transport big data analytics: Imputing missing data

The missing data problem is often unavoidable for real-world data collection systems because of a variety of factors, such as sensor malfunctioning, maintenance work, transmission errors, and so on. Filling in missing information in a dataset is an important requirement for many machine-learning algorithms that require a complete dataset as input. Data imputation algorithms aim at filling the missing information in a dataset. Many missing data imputation techniques exist in the literature, with applications demonstrated on various types of datasets. …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Civil and Environmental Engineering
Research centre(s)
Centre for Data Science

Efficient parameter estimation for agent-based models of tumour growth

Cancer is an extremely heterogeneous disease, particularly at the cellular level. Cells within a single cancerous tumour undergo vastly different rates of proliferation based on their location and specific genetic mutations. Capturing this stochasticity in cell behaviour and its effect on tumour growth is challenging with a deterministic system, e.g. ordinary differential equations, however, is possible with an agent-based model (ABM). In an ABM, cells are modelled as individual agents that have a probability of proliferation and movement in each …

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

Making the most of many models

In the age of Big Data, machine learning methods, and modern statistics the adage "all models are wrong but some are useful" has never been so true. This project will investigate data science approaches where more than one model makes sense for the data. Is it better to choose a single model or is there something to be gained from multiple models?This project will look at variable selection methods, penalised regression, Bayesian model averaging and conformal prediction. The research has …

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

Page 3 of 18

Contact us

If you have questions about the best options for you, the application process, your research topic, finding a supervisor or anything else, get in touch with us today.