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 41 matching student topics
Displaying 37–41 of 41 results
Symbiosis in microbial ecosystems
Soil systems are fundamentally important to the health of our planet, but the complexity of soil microbial communities makes them particularly challenging to study. Soil systems are amongst the most diverse microbial ecosystems on Earth in terms of the number of microbial species (and strains) present within individual samples, and in the breadth of functions encoded. Beyond complexity measured by counting distinct community members, interactions between microbial species including symbiosis, parasitism or commensalism are widespread and yet barely studied.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
-
Centre for Microbiome Research
Human-in-the-loop techniques to debug machine learning models
Machine learning models are being deployed in critical domains such as healthcare, education and fintech. The current approach to deploying machine learning models is based on considering a data-centric approach where the models are evaluated using performance measures on a test set. However, the high performance of the model on test data is not indicative of its reliability,An important aspect of reliability is in the understanding of what exactly a machine learning model encodes, and to verify if it learns …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Continual learning system
AI that is pre-programmed is limited in its tasks and human bias. Learning systems offer richer decision-making behaviors where collaborative projects have led to the following three systems that require integration:A symbolic learning system that can continually learn Boolean classification problems as they are presented to it. But this needs to be extended to real-valued, noisy and uncertain classification problems.A lateralized system that can consider an input at the constituent level and the holistic level simultaneously, which enables flexible and …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Resolving uncertainty in decisions to improve agri-food system outcomes for people and nature
Despite efforts to monitor and manage declining species and ecosystems around the world, biodiversity is still not routinely included in mainstream decision-making and continues to decline at the highest rate in human history. Added to this is the problem that both natural and agri-food systems are complex networks that are continually changing due to human and natural disturbances, with climate change likely to increase the impacts of extreme events like drought, fire and economic shocks on these networks.Because of large …
- Study level
- PhD
- Faculty
- Faculty of Science
- School
- School of Biology and Environmental Science
- Research centre(s)
- Centre for Data Science
Centre for the Environment
Identifying emergent ecosystem responses through genes-to-ecosystems integration at Stordalen Mire
Permafrost thaw induced by climate change is predicted to make up to 174 Pg of near-surface carbon (less than 3m below the surface) available for microbial degradation by 2100. Despite having major implications for human health, prediction of the magnitude of carbon loss as carbon dioxide (CO2) or methane (CH4) is hampered by our limited knowledge of microbial metabolism of organic matter in these environments.Genome-centric meta-omic analysis of microbial communities provides the necessary information to examine how specific lineages transform …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
-
Centre for Microbiome Research
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