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 241 matching student topics
Displaying 25–36 of 241 results
Surface engineering for nanoelectronic devices
Ga2O3 is an emerging wide-bandgap semiconducting material that has received enormous attention in recent years. This is due to its potential application in power devices, UV detectors and military applications that are unattainable by conventional semiconductors such as silicon.The operation and performance of these type of electronic devices rely critically on the surface quality and properties of the semiconducting materials. However, the surface atomic structures and electronic structures of Ga2O3 single crystals are not yet fully understood.The principal aim of …
- Study level
- PhD, 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
Glassy 2D molecular materials
Modern semiconductor technologies are based on crystalline materials with well-defined physical and electronic structures.However, molecular materials, such as organic semiconductors, may present interesting opportunities through disordered structures.The focus of this project will be on conjugated 2D materials without long-range order: molecular glasses. Through control of the chemical composition, atomic bonding motifs, and lateral size, we will be able to modify the properties of these materials.Our focus will be on synthesising and studying these new materials to better understand the relationship …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
- Research centre(s)
- Centre for Materials Science
Avatar customisation for diversity training in virtual reality
Avatar representation is found to be crucial for user engagement in various types of applications and user identifications with avatars. This project aims to design and develop an environment where users can customize their avatars by looking at a virtual mirror. In this project, where users will be trained in diversity awareness, it is crucial for them to feel like the character who is in the scenario. The outcome of the project will be used in experiments to test the …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Critical evaluation of Star Formation Rate estimators in galaxies
This project aims to assess the reliability, accuracy, and limitations of various Star Formation Rate (SFR) estimators used in extragalactic astronomy. By leveraging multi-wavelength data from the ZFOURGE survey, the project will explore how well SFR indicators derived from UV, optical (Hα), infrared (IR), and radio observations compare to SED-fitted SFRs from CIGALE. The project will focus on understanding discrepancies, particularly in dusty star-forming galaxies and AGN hosts, and provide recommendations for improving SFR estimates in future research.
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Chemistry and Physics
Power efficient computing for statistical machine learning
The carbon footprint of computing globally is estimated to be comparable with that of the aviation industry. With the advent of generative artificial intelligence, there is a growing awareness of this environmental impact both in terms of the carbon footprint and other environmental impacts including e-waste and water consumption, predominantly through the use of power-hungry graphics processing units (GPUs).These are particularly relevant issues to many fields that rely on computationally intensive simulations for data analysis or calibration of statistical machine …
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Digital Games to Support FIFO Families
This unique research project explores how asynchronous digital games can strengthen social connections among FIFO (Fly-In, Fly-Out) workers and their families. Prolonged separations and demanding schedules create challenges such as isolation and mental health impacts. This study aims to understand how these families use technology to stay connected and how games can support their wellbeing.This project is associated with a funded scholarship. You'll receive a stipend valued at $33,637 per annum for a maximum duration of 1.75 years while undertaking …
- Study level
- Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Hierarchical forecasting: forecasting a collection of time series
Hierarchical forecasting is a method used to generate forecasts at multiple levels of aggregation within a structured hierarchy. This technique is particularly valuable in situations where data can be organised into a hierarchy based on different dimensions, such as geography, product categories, or time. The approach ensures that forecasts at the top levels (e.g. total sales) align with forecasts at the lower levels (e.g. regional or product-level sales), creating a coherent and consistent forecasting process across the entire hierarchy.In many …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Bayesian focused learning
Forecasting renewable energy production is crucial for ensuring stable and sustainable energy grids. Traditional approaches often involve a two-stage process: first, energy production forecasts are generated, then decisions, such as how much energy to produce from various sources (wind, solar, fossil fuels), are made based on those forecasts. This disjointed process, where forecast accuracy and decision-making optimization are treated separately, can lead to sub-optimal outcomes due to conflicting objective functions.The goal of this project is to bridge these stages by …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Optimising inventory control and demand forecast accuracy though multi-objective optimisation
In today’s competitive business environment, effective inventory management and accurate demand forecasting are critical for minimising costs and maximising profitability. This project aims to address these two challenges simultaneously by applying a multi-objective optimisation approach. The primary objectives are to improve demand forecast accuracy while optimising inventory control decisions, balancing trade-offs between conflicting business goals such as minimising stockouts, reducing excess inventory, and maintaining customer service levels.Traditional approaches to inventory management and demand forecasting often treat these processes separately, which …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Decision optimisation in energy supply chain
this project aims to develop integrated forecasting and decision optimisation models for renewable energies.
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Probabilistic forecasting of energy
This project aims to develop probabilistic forecasting models for renewable energies vi a Bayesian approach. The models will be developed for very short term and short-term (10 minutes to 24 hours ahead).
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Spatio-Temporal Forecasting of renewable energies
This project aims to develop short-term (up to 24 hours ahead) forecasting models that take into account the spatial as well as temporal information in wind farms and solar farms. Such models are useful for operational planning in farms and stabilising the network.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
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