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 33 matching student topics
Displaying 25–33 of 33 results
Advancing Water Quality Monitoring in Queensland through Data Science
Organisations throughout Queensland are actively involved in the real-time monitoring of water quality parameters in rivers that contribute to the health of the Great Barrier Reef. This crucial assessment is conducted using in-situ sensors and grab samples to measure key parameters such as nitrate and turbidity. However, it is important to note that while sensor data is collected at high frequencies, they are often affected by anomalies leading to potential errors. Consequently, physical visits to monitoring sites are required to …
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Statistics via scalable Monte Carlo
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Web-scraping for business information
National Statistics Offices (NSOs) have used web-scraping to collect information on the prices of goods and services for some time now. However, some work is now being done by European NSOs on using web-scraping for collecting other kinds of statistical information on businesses. The aim of this project is to investigate the feasibility of using this approach in Australia.
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Assessment of non-linear dimension reduction methods for calculating a SEIFA-like index
This project would involve applying one or more non-linear dimension reduction methods to Census 2021 data to calculate an index similar to the Index of Relative Socio-economic Advantage and Disadvantage (IRSAD) from the Socio-Economic Indexes For Areas (SEIFA). Some information and recommendations for the specific non-linear dimension reduction methods will be supplied as the output from an earlier project.
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
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, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Combining solar and vibration energy harvesting for rainfall prediction
Rainfall prediction plays a crucial role in various sectors such as agriculture, water resource management, and disaster preparedness. Traditional prediction methods often rely on complex meteorological models and expensive equipment. However, advancements in energy harvesting technology offer the opportunity to develop low-cost and sustainable solutions for rainfall prediction.This project proposes to leverage solar and vibration energy harvesting for rainfall prediction. Combined measurements from both solar and vibration energy harvesting can provide comprehensive data for real-time monitoring of cloud coverage and …
- Study level
- Honours
- School
- School of Information Systems
Driver engagement and risk in automated driving: Advanced data analytics leveraging driver monitoring systems
The project aims to the explore concept of empathic machines in the context of driver monitoring systems (DMS) and automated driving. The successful candidate will contribute to advancing the understanding of driver engagement, situation awareness, and risk through leveraging advancements in data science techniques on vehicle sensor, DMS, and other related datasets.To apply for this position, please submit the following documents:a cover letter outlining your research interests, relevant qualifications, and motivation to join the Empathic Machines projecta detailed curriculum vitae …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Data Science
Centre for Future Mobility/CARRSQ
Taxonomy of data science methods
To reap the benefits of data science it's necessary to be able to pair real world data problems with data science methods.In this project we'll begin to map out the key methods, their benefits and drawbacks, and suitability of each given some initial problem statements.
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Harnessing the Power of Data Science to Protect Endangered Fish Populations
In this research project, we explore the world of endangered fish species in Alberta, Canada, aiming to gain a deep understanding of aquatic ecosystems. Our focus is to assess the factors impacting the abundance of endangered trout populations, a topic of great interest among scientists. Through the application of advanced statistical machine learning models, we analyze parameters measured by water sensors to uncover the factors affecting fish populations. By developing a predictive framework, we aim to provide valuable insights into …
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
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