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 28 matching student topics
Displaying 1–12 of 28 results
Giant viruses in the human gut microbiome
The human body is home to a vast ecosystem of microorganisms including bacteria, archaea, fungi, viruses, and bacteriophages that make up the human microbiota. These microbes and their collective genetic material, known as the microbiome, influence a wide range of physiological functions including nutrient production and absorption, the development and regulation of our immune system, protection against potential pathogens, and even our mood and mental health. While distinct microbial communities exist throughout the body, the gut microbiome has gained particular …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
-
Centre for Microbiome Research
The Law and Policy of Satellite and Large Data in Environmental and Land Use Management
Dr Evan Hamman is looking for PhD/MPhil candidates wanting to explore the relationship between space technologies and large data sets in the mapping, managing and directing of human land use. Candidates interested in exploring the relationships between land use management, data science and environmental law and regulations are particularly encouraged. The focus can be Australia, comparative or public international law. This topic is led by the QUT School of Law within the Datafication and Automation of Human Life research group. …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Business and Law
- School
- School of Law
Digitising Legislation
Dr Anna Huggins is looking for PhD/MPhil candidates interested in the emerging computational law project of translating legislation into digital forms. This could involve top down conceptualisation of the translation of legislative provisions or projects examining in detail the digitisation of specific legislation. Candidates with a background in data science, public administration and/or law are encouraged to apply. This topic is led by the QUT School of Law within the Digital Social Contract and Datafication and Automation of Human Life …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Business and Law
- School
- School of Law
Profiling aerosol liquid water content over Australia
Aerosol liquid water content (ALWC) is a ubiquitous constituent in atmospheric aerosol particles. The degree of ALWC present in aerosol particles is influenced various factors, including relative humidity, temperature, particle mass, size distribution, and aerosol composition. Comprehensive analyses on ALWC have been conducted in the Northern Hemisphere, but similar work has rarely been done in the Southern Hemisphere due to the scarcity of aerosol particle measurements. In the atmosphere, ALWC scatters radiation and reduces visibility, significantly affecting air quality, weather, …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Earth and Atmospheric Sciences
SafeAge product safety
Older persons as a cohort are at high risk of consumer product-related injury and death. The most recent Australian research into product safety issues for older persons was conducted over 25 years ago, yet the marketplace and product technology have changed dramatically and the population at risk has grown.This Australian Research Council funded Discovery Project aims to generate contemporary knowledge of the role of consumer products in injuries and deaths for older persons. It is a 3-year collaborative academic research …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Public Health and Social Work
- Research centre(s)
- Centre for Healthcare Transformation
Australian Centre for Health Services Innovation
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
- Faculty
- Faculty of Science
- 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
Statistics via scalable Monte Carlo
Monte Carlo methods use random sampling to approximate solutions to challenging problems. These methods are helpful for statistical models with many parameters, as discussed in this short video. The methods are particularly useful for Bayesian inference where one wishes to get a rigorous understanding of parameter uncertainty.Despite having many advantages over their competitors, Monte Carlo methods can be very slow in the context of big data. In this project, you'll help develop scalable Monte Carlo methods to enable timely and …
- Study level
- PhD, Master of Philosophy, Honours
- 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
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
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
Visualisation and sonification for genomic data sets
Successive revolutions in sequencing technology over the past two decades have led to an explosion in the availability of genomic data. Analysing biological datasets and identifying relationships within them is challenging - some of the process can be automated but interactive exploration offers a number of advantages, and supports serendipitous discovery.This project looks at visual analytics and sonification - the use of sound and musical encodings - to enhance our understanding of biological networks.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Gamified process-data cleaning
Despite the importance of data quality, it is often compromised. The majority of the time and energy in most data science projects is spent on data cleaning. Process-oriented data mining (process mining) is not an exception. A recent process mining survey shows that more than 60% of the time and effort is spent on data transformation and pre-processing. While, in most cases, the engagement of domain experts is required for accurate data cleaning, it is challenging to engage them in …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
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