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 684 matching student topics

Displaying 505–516 of 684 results

Time-series analysis of 2D diffraction patterns for Synchrotron rock physics

The interaction between deformation, fluid flow, chemical reactions, and heat flow in rocks constitutes a research frontier in the Earth Sciences. In addition to fundamental academic interest in this subject, there are many applied industrial problems, which require a sound understanding of this coupling. Examples include: the long-term sequestration of carbon dioxide in rocks, the energy-efficient processing of future-mineral resources, the design of unconventional geothermal-energy operations, and the prediction of earthquakes and volcanic eruptions.The advisory team pioneered new methods for …

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

Investigating factors impacting urban heat vulnerability in subtropical cities

In recent years, with the rise in climate change impact, urban heat has become a major issue for many cities to tackle consequently. Extreme heat events are becoming more frequent and intense due to climate change, which has directly caused a substantial increase in heat-related morbidity and mortality. This indispensably puts an extra burden on medical systems and national finance. Meanwhile, the urban heat island effect has been exaggerating the consequences caused by the increased extreme heat in metropolitan areas. …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Architecture and Built Environment

Virus Search Algorithms

Meta-heuristics are powerful search algorithms for solving intractable optimization problems. There are many population based approaches, like genetic algorithms, evolutionary algorithms, particle swarm, etc. but most of these have a static population size.Viruses arise and attack populations periodically. They typically appear when populations become abundant. Viruses infect population members, and often reduce the number of individuals. Viruses create spaces for more individuals and balance competition.The concept of viruses may be mimicked and could be a useful optimization paradigm.

Study level
Honours
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering

Network Flow Improvement

Network flow is impeded by the arcs present in the network and their associated length/weighting. Arcs can be added or removed to debottleneck the network. But which ones? At what cost?

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

Place-based giving and philanthropy

Effective models of place-based funding remain conceptually unresolved.  Place-based, collective impact initiatives are increasingly recognised for creating long-term systems change, yet the role of philanthropy in supporting, advocating for and catalysing change is underexplored.I am interested in supervising research into conceptual models of philanthropic funding for place-based initiatives, to explain and clarify the elements and characteristics of successful, long-term relationships between philanthropic funders and place-based, community-led initiatives in regional and urban Australian communities.

Study level
PhD, Master of Philosophy
Faculty
Faculty of Business and Law
School
School of Accountancy
Research centre(s)

Australian Centre for Philanthropy and Nonprofit Studies

Scalable Bayesian Inference using Multilevel Monte Carlo

Bayesian inference is a popular statistical framework for estimating the parameters of statistical models based on data. However, Bayesian methods are well known to be computationally intensive. This fact inhibits the scalability of Bayesian analysis for real-world applications involving complex stochastic models. Such models are common in the fields of biology and ecology.Multilevel Monte Carlo (MLMC) methods are a promising class of techniques for dealing with the scalability challenge. These approaches use hierarchies of approximations to optimise the trade-off between …

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

Climate vulnerability of nut and pulse food systems in Australia

Arable land, water resources and biodiversity are under pressure from increased human populations and resource needs. On top of that, natural and agri-food systems are rapidly changing due to natural disturbances, with climate change likely to increase the impacts of extreme events like drought and wildfire.With climate change, negative impacts on agriculture are predicted with disruptions to food supply; many ecosystems have already been impacted by increased frequency and severity of extreme fire events; coral reefs will be threatened by …

Study level
Honours
Faculty
Faculty of Science
School
School of Biology and Environmental Science
Research centre(s)
Centre for Agriculture and the Bioeconomy
Centre for the Environment

Coarse-grained molecular dynamics modelling in expansive soil

Expansive soil/active soil has wide applications in geotechnical engineering and other engineering disciplines due to its desirable special properties - for example, low permeability and swelling pressure under saturated condition. But these materials are highly susceptible to experiencing huge volume change and even damage due to moisture content reduction. However, the underlying mechanism of this phenomenon is still not clear for geotechnical engineers. Therefore, there is no optimum solution available to solve the problem.In this project, a special modelling approach …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Engineering
School
School of Civil and Environmental Engineering
Research centre(s)
Centre for Materials Science

Smoke and mirrors: intercepting the elusive molecular precursors of soot

Soot formation occurs via a complex network of chemical reactions leading from simple gases to macromolecular aggregates. Despite being central to our understanding of extreme environments ranging from engines, to bushfires and interstellar clouds, the critical steps and intermediates in these reactions are poorly described.This project will deploy advanced mass spectrometry and laser-based methods to generate, isolate and interrogate gas phase free radical intermediates and elucidate their role in molecular weight growth processes.Through these chemical insights, advanced computational models will …

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

Elucidating the gas-phase reactivity and photochemistry of halide anions

Bromine and iodine are suspected to be responsible for most of the halogen-induced ozone loss in the stratosphere but are not currently included in atmospheric models due to a paucity of knowledge of the gas-phase chemistry and photochemistry of their anions and radicals.This project will develop and deploy advanced mass spectrometry and laser spectroscopy techniques to enable precision measurements of the reactions and photo- reactions of gas-phase iodide and bromide anions and their oxides.These state-of-the-art measurements of reaction kinetics and …

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

Surrogate models for accurate prediction and inference in mathematical biology

High fidelity mathematical models of biological phenomena are often complex and can require long computational runtimes which can make computational inference for parameter estimation intractable.  In this project we will overcome this challenge by working with computationally simple low fidelity models and build a simple statistical model of the discrepancy between the high and low fidelity models.  This approach provides the best of both worlds: we obtain high accuracy predictions using a computationally cheap model surrogate.

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

Investigating the rise of super apps: platforms, services, adoption

Imagine you want to go to a rugby game in Brisbane in a few weeks with some friends. You will probably jump across at least a few apps – coordinating plans on WhatsApp, buying tickets from Ticketmaster, booking a ride through Uber, and paying each other back for drinks over Venmo. But what if all that activity happened in one app on your phone? Meet the so-called 'super apps'.Super apps refer to marketplaces that offer a wide range of products …

Study level
Master of Philosophy
Faculty
Faculty of Business and Law
School
School of Advertising, Marketing and Public Relations
Research centre(s)

Centre for Behavioural Economics, Society and Technology

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