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.

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Found 210 matching student topics

Displaying 109–120 of 210 results

BIOM01 - Novel therapeutic strategies for targeting dementia

Dementia exhibits the presence of Lewy bodies in the cerebral cortex, which are composed of α-synuclein (αSYN) or Amyloid-β (Aβ) plaques, as well as hyperphosphorylated tau (P-tau) tangles in various forms of dementia. The exact pathological mechanisms underlying this disease are not well understood; however, there is evidence suggesting the involvement of inflammatory activity. Microglia, macrophage cells residing in the brain responsible for clearing external pathogens and dead cells, are of particular interest.Our study aims to investigate whether Lewy bodies …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Biomedical Sciences
Research centre(s)

Centre for Microbiome Research

Assessing the quality of cluster analysis

Machine learning cluster methods are common classification methods, but methods for assessing performance are limited as are methods for explaining how they work.  Exploring methods for both assessing and explaining performance are the subject of this research with application to real-world contexts with the Australian Bureau of Statistics.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Explainability of outlier detection methods

Outliers are anomalous observations in a data set that are "outside the norm" of what would be expected. Identifying outliers is an important part of exploratory data analysis and data analysis in general. It is often a challenging problem and calls for advanced methods and approaches, including machine learning-based tools. As methods become more and more complex, their explainability becomes more difficult and more important. This research project will look at all aspects of explainability and explore new approaches and …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Aerosol presursors in Australian marine environments

Aerosols, tiny solid or liquid particles, play an important role in global climate regulation, firstly, by scattering and absorbing incoming solar radiation and, secondly, by their ability to take up water vapor from the atmosphere and serve as nuclei for cloud droplet formation (Cloud Condensation Nuclei (CCN)).With oceans covering 71% of the Earth’s surface, marine aerosols present a significant proportion of the global aerosol budget. Production of particles in the marine environment occurs via 2 pathways: 1) wave breaking and …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Earth and Atmospheric Sciences
Research centre(s)

Centre for the Environment

Natural disaster (landslide, earthquake) mitigation using remote sensing, geophysics, and site monitoring

Extreme weather events can exacerbate slope and dam stability issues. Risk mitigation, stabilisation works, and engineered solutions to slope or dam failure require detailed site and subsurface characterisation – generally undertaken after a failure, but often resulting in unacceptable delays to remediation, impacting communities, transport, and water resources.This project will develop pre-emptive risk mitigation measures for at-risk sites, utilising remote sensing, geophysical, and monitoring approaches.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Earth and Atmospheric Sciences

Lunar seismology: Using lunar seismology data for site characterisation at Schrodinger crater

QUT is involved in the science team for a recently Australian Space Agency-funded mission to Schrodinger crater, to deploy a Fleet Space seismometer. QUT is developing workflows to translate the seismic data into detailed subsurface models for site characterisation, off-world construction, and in-situ resource mapping of materials such as ice.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Earth and Atmospheric Sciences
Research centre(s)
Centre for Data Science

Quantifying sedimentation on reefs using Google Earth Engine

Decreasing water quality is negativtly impacting coral reefs globally and is a threat that can be actively managed.

Study level
Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Earth and Atmospheric Sciences
Research centre(s)

Centre for the Environment

Machine Learning-based pedictive tool for energy storage

The fundamental idea behind the ML approach is to analyze and map the relationships between the physical,chemical, and energy storage properties of materials with their associated output data. This early understanding of the energy storage capabilities through the ML approach helps the material scientists to clearly understand, discover, and optimize the fabrication process to develop highly efficient energy storage systems. It also provides key steps in the device fabrication process omitting excessive experimental stages.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Chemistry and Physics
Research centre(s)
Centre for Materials Science

Anode-free Batteries

The lithium-metal battery (LMB) has been regarded as the most promising and viable future high-energy-density rechargeable battery technology due to the employment of the Li-metal anode. However, it suffers from poor energy density and safety, and improved battery design is sought. The anode-free full-cell architecture is constructed from a fully lithiated cathode with a bare anode Cu current collector. In such an anode-free lithium battery, both the gravimetric and volumetric energy densities can be extended to the maximum limit. Moreover, …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Chemistry and Physics
Research centre(s)
Centre for Materials Science

Mathematical tools for stochastic and continuum transport models

Mathematical models of particle transport are fundamental to many applied disciplines including physics, biology, ecology and medicine. Particle transport is typically modelled using either a stochastic model, where probability rules govern the motion of individual particles, or a continuum model, where partial differential equations govern the concentration of particles in space and time. This project aims to use analytical and numerical techniques from applied and computational mathematics to address one or both of the following questions:what is the average time …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences

Medical selfies and patient generated health data

Smartphones and wearable technologies provide exciting opportunities for patients and health professionals to transform healthcare.Patients can benefit from photos (“medical selfies”) taken on their smartphone to record a condition that they want to discuss with a health professional. Wearable devices allow patients to semi-automatically collect data about their physical activity, sleep, mood, diet, etc.This data can help patients to better understand a health concern, its underlying causes and the impact of treatments.Clinicians, on the other hand, can benefit from medical …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science

Statistics via scalable Monte Carlo

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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