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 8 matching student topics
Displaying 1–8 of 8 results
2032 Brisbane Olympic Games: how can we achieve climate-positive urban objectives?
Brisbane is the first host city to be contractually bound to deliver a climate-positive Olympic Games in 2032 (Queensland Government, 2023). Most of the 8,000-megawatt coal plants are expected to close by 2032, which requires a viable and sustainable transition to renewable energies (Simshauser, 2024).In this project, we investigate how digital energy services and analytics (DESA) can help a sustainable energy transition for a climate-positive 2032 Brisbane Olympic Games.ReferencesQueensland Government. (2023). All Queensland. All in. 2032 procurement strategy. https://www.forgov.qld.gov.au/__data/assets/pdf_file/0011/404030/Q2032-procurement-strategy.pdfSimshauser, P. …
- Study level
- PhD, Master of Philosophy, Honours
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Is battery storage overrated? Achieving grid equilibrium through digital energy services and analytics
The share of renewable energy in electricity generation has globally increased to 28.3%, however, an acceleration of the sustainable energy transition is required to limit worldwide temperature rise (REN21, 2022).Energy storage offers various benefits, such as balancing the mismatch between electricity supply and demand; however, due to its charge/discharge inefficiencies (energy storage results in a loss of at least 10% of electricity in the charge/discharge process), digital solutions are needed to manage grid equilibrium effectively (Watson et al., 2022).In this …
- Study level
- PhD, Master of Philosophy, Honours
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
Improved data analytics for lithium ion batteries
Join the team to be part of an exciting QUT-lead project into materials for Lithium-ion batteries. The project is part of the Federally supported Future Battery Industries - Cooperative Research Centre, which hosts projects all-over the country that are aiming to boost the industry, create clean energy jobs, and enable a sustainable future.In this role you gain access to QUT's one-of-a-kind in Australia, Advanced Battery Facility. At the facility we build lithium batteries in a range of shapes and sizes. …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
Centre for Clean Energy Technologies and Practices
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
Developing predictive models, methods and analytics for complex sports data
A 3-year strategic partnership on sports data science between the Centre for Data Science (CDS), the Australian Institute of Sport (AIS) and the Queensland Academy of Sport (QAS) was launched in the past few months. With a drive towards data informed decision making across the high performance sports network nationally, a number of collaborative, interdisciplinary research and scholarship opportunities ranging from VRES, to honours, masters and PhD have developed.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Human data interaction with big data visual analytics
Our research is seeking to answer the question: 'How can we support human interaction with big data?'We want to integrate the outstanding capabilities of humans in terms of visual information exploration with the enormous processing power of computers. These elements have the capacity to form a powerful knowledge discovery environment. This research will use datasets from the Queensland Government and the QUT Ecoacoustic research group over multiple years. Other big datasets, such as Amazon’s product review dataset, could also be …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
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
Data-driven and process-aware workforce analytics
Modern information systems in today’s organisations record massive amount of event log data capturing the execution of day-to-day core processes within and across organisations. Mining these event log data to drive process analytics and knowledge discovery is known as process mining. To date various process mining techniques have been developed to help extract insights about the actual processes with the ultimate goal to organisations' workforce capability and capacity building.As an important sub-field of process mining, organisational mining focuses on discovering …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Data Science
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