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 684 matching student topics
Displaying 385–396 of 684 results
Understanding and designing for digital self-care
The aim of this project is to better understand self-care practices with digital technologies amongst young adults and to explore opportunities for digital technology design.Self-care is a process of purposeful engagement in practices that promote holistic health and well-being of the self. Holistic health implies overall health and this encompasses more than just physical health but also includes mental, emotional and even spiritual health of a person. For some people, cooking can be a form of self-care to eat healthily …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Sustainable energy transition with system dynamics
The challenge to keep global warming to 1.5°C above pre-industrial levels has become even greater due to a continued increase in greenhouse gas emissions (IPCC, 2023). One major challenge is the shift from fossil fuels to renewable energy to reduce emissions (Gholami et al., 2016). The share of renewable energy in electricity generation has increased to 28.3%, however, an acceleration of the pace of the transition is required to limit global temperature rise (REN21, 2022).New energy policies are needed to …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Southern ocean aerosols: Sources, sinks and impact on cloud formation and climate
Robust prediction of human-induced global warming and future climate requires more accurate climate models. Currently, aerosol-clouds interactions represent the largest source of uncertainty in our global climate models. To reduce this uncertainty, we need a better understanding of aerosol sources, chemical and physical properties, and processes impacting their growth to sizes where they can act as Cloud Condensation Nuclei (CCN) and interact with incoming solar radiation.The Southern Ocean is a region of the world where climate and weather models, including …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
- Research centre(s)
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Centre for the Environment
Uncovering the dark transcriptome and proteome with long-read sequencing
Parts of the transcriptome and proteome are invisible to current technologies. We refer to them as the dark transcriptome and proteome and they encompass uncharacterised mRNA and protein isoforms. Importantly, this hidden molecular phenotype is believed to play a critical role in animal health and behavior.Recent developments in mRNA analytical methods such as long-read sequencing (PacBio, ONT) have enabled better characterization of isoforms and are redefining the transcriptome landscape in many species. We and others have found that data generated …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Biology and Environmental Science
Develop microfluidic technologies for cardiovascular and cerebrovascular diseases
The sudden rupture of vulnerable atherosclerotic plaques and subsequent thrombosis formations are responsible for most acute vascular syndromes, such as myocardial infarction and stroke. Many victims who are apparently healthy die suddenly with no prior symptoms. Such deaths could be prevented through surgery or alternative medical therapy, if vulnerable plaques were identified earlier in their natural progression.To address this pressing need, we're developing simple-to-use, high-throughput and highly-informative microfluidic biochips to understand the sequences of molecular events underlying biomechanical thrombosis (mechanobiology). …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Development of a Microfluidic Gut-Brain Axis Chip
The gut microbiome refers to the collection of micro-organisms that are living symbiotically in the human or animal gastrointestinal tract (defined as the “microbiota”), their genetic material as well as the surrounding environmental habitat. It is now appreciated that the microbiome plays an important role in human health and diseases. Many neurodegenerative diseases, such as Parkinson's Disease have been linked to dysregulation of the gut microbiota. However, it is difficult to study gut-brain axis using animal models due to inter-species …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Centre for Microbiome Research
How do healthy people sleep? Biomechanics, physiology, and environment - what matters most?
In the Westernized world a person typically spends one third of their life in bed, with more time spent sleeping in a bed than in any other single activity. Sleep amount and quality of sleep have a direct impact on mood, behaviour, motor skills and overall quality of life. Yet, despite how important restful sleep is for the body to maintain good health, there is a comparatively small amount of studies evaluating key multi-factorial and biomechanical determinants of restful sleep …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Predicting good sleep using computer science: Can we use machine learning to find out 'what's the best bed?'
In the Westernised world a person typically spends one third of their life in bed, with more time spent sleeping in a bed than in any other single activity. Sleep amount and quality of sleep have a direct impact on mood, behaviour, motor skills and overall quality of life. Yet, despite how important restful sleep is for the body to maintain good health, there is a comparatively small amount of studies evaluating key multi-factorial determinants of restful sleep in non-pathological, …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Big Data ideas for GLMs
The goal of this project is to develop new Bayesian methods for large-scale data analysis using subsampling techniques. The focus of the project will be on generalised linear models (GLMs), which are commonly used models in statistics and machine learning.One of the main challenges in using Bayesian statistics with big data is the high computational cost associated with processing big datasets. The proposed project aims to address this challenge by developing new subsampling techniques for Piecewise Deterministic Markov Process (PDMP) …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Continuous time samplers (MCMC at the limit!)
The goal of this project is to develop new continuous time Monte Carlo methods for efficient sampling from high-dimensional distributions. Continuous-time Monte Carlo methods are a class of algorithms that use continuous-time dynamics to generate samples from target distributions, rather than the discrete-time dynamics used in traditional Markov chain Monte Carlo (MCMC) methods. These methods have been shown to have faster mixing and better exploration of the state space, making them particularly appealing samplers for challenging distributions.The main objectives of …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Unlocking the Potential of Simplex-Truncated Distributions
This PhD project aims to develop new methods for generating random samples from a specific type of probability distributions called simplex-truncated distributions. These distributions are commonly used in various fields such as statistics, machine learning, and biology.The project will involve the development of new techniques to generate random samples from simplex-truncated distributions. These techniques are based on a method called continuous-time Monte Carlo which is a cutting edge method in statistics that can generate random samples from complex distributions.The main …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Mapping the world: understanding the environment through spatio-temporal implicit representations
Accurately mapping large-scale infrastructure assets (power poles, bridges, buildings, whole suburbs and cities) is still exceptionally challenging for robots.The problem becomes even harder when we ask robots to map structures with intricate geometry or when the appearance or the structure of the environment changes over time, for example due to corrosion or construction activity.The problem difficulty is increased even more when sensor data from a range of different sensors (e.g. lidars and cameras, but also more specialised hardware such as …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
- Centre for Robotics
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