Filter by faculty:

Found 34 matching student topics

Displaying 1–12 of 34 results

Diffusion and first passage times in random media

Diffusion in homogenous environments is relatively well understood, but the problem becomes more complicated in complex environments - such as wood tissue, cells, filters and catalysts. At QUT there is extensive expertise in using advanced numerical methods to model diffusions and first passage times in complex environments.The ability to combine this expertise with realistic models of random media based on level-sets of Gaussian random field.

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences

Biophysical models in humans and nature

Biophysical models are developed to represent key processes in humans and nature, from the electrophysiology of the human heart, to calcium carbonate skeleton production of coral reefs.In this project, we will explore biophysical model development across multiple fields, to identify commonalities, strengths and weaknesses, and identify analysis techniques ubiquitous in one field that can be immediately exploited to improve science in another field.

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Mathematical modelling of ecosystem tipping points in Antarctica

Slight variations in the seasonal timing of Antarctic ice melt can drastically shift the composition of local shallow-water ecosystems from being dominated by invertebrates to algae instead. Such "tipping point" events may become commonplace in the future due to climate change, not just in Antarctica but in many ecosystems worldwide.This project seeks to develop mathematical models of the interactions between Antarctic environmental conditions and the local shallow-water ecosystem states. These models could then be used to make predictions about the …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Using mathematical models to detect alternative stable states in ecology

This project seeks to use mathematical models to detect "alternative stable states" in ecology - a behaviour in which the ecosystem can get "stuck" in one state (e.g. pristine) or another (e.g. irreversibly degraded).

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Mathematical modelling of ecosystem feedbacks and value-of-information theory

Ecosystems respond to gradual change in unexpected ways. Feedback processes between different parts of an environment can perpetuate ecosystem collapse, leading to potentially irreversible biodiversity loss. However, it is unclear if greater knowledge of feedbacks will ultimately change environmental decisions.The project aims to identify when feedbacks matter for environmental decisions, by generating new methods that predict the economic benefit of knowing more about feedbacks. Combining ecological modelling and value-of-information theory, the outcomes of these novel methods will provide significant and …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Optimal ecosystem management in rapidly changing systems

Delays in acting in collapsing ecosystems can be catastrophic. With every passing year, the chances that the ecosystem has progressed past some point of no return increases. Yet the research and development needed to develop a new technology can take a long time. Balance between these two dynamic processes is needed to determine the optimal length and effort for developing new technologies. This project will develop a method for finding the optimal schedule for developing technological readiness, social acceptability, a …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Bayesian inference meets value-of-information: how much more data do we really need for management of ecological networks?

The project involves applying value-of-information analysis across ecosystem models fit to data using Bayesian inference, to yield conclusions that have potentially wide application across the field of community ecology.Ecological networks use generalisations of the Lotka-Volterra model to describe the interactions between species, including predator-prey, mutualism, parasitism and others. Lotka-Volterra models fit to noisy data from synthetic ecological networks using Bayesian inference reveal that the predictions made in these networks carry large uncertainty but they may still be useful for informing …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Uncertainty quantification in mathematical ecology

In this project, we will explore uncertainty quantification in mathematical ecology via a number of different methods. The project will involve application to ecological dynamics in the Great Barrier Reef.

Study level
Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences

Optimising delivery of a novel nose-to-brain treatment for brain cancer

Glioblastoma multiforme (GBM) is an aggressive brain cancer with no curative treatment and poor prognosis. One of the biggest challenges with treating GBM is the inability of treatment to cross the blood-brain barrier resulting in poor drug distribution in the brain. Fortunately, scientists have recently developed a novel nose-to-brain delivery system that uses nanoparticles loaded with a chemotherapy drug called paclitaxel. Initial treatment investigations in vivo are showing significant promise in reducing and controlling the tumour burden. While exciting, before …

Study level
Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences

Predicting alternative states induced by multiple interacting feedbacks: seagrass ecosystems as a case study

This project seeks to explore the complex dynamics that might arise from multiple interacting feedbacks in marine ecosystems, by designing ordinary and/or partial differential equation models of these feedbacks and analysing the steady states and/or temporal dynamics of the proposed model(s).It has been hypothesised that many social and ecological systems exhibit alternative stable states due to feedback processes that keep the ecosystem in one state or the other. The result can be tipping points, which are difficult to predict but …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Using mathematics to understand multiple sclerosis: what causes the immune system to attack the brain?

Every day, we use our bodies to move, think, talk and eat, but for people with multiple sclerosis (MS) these tasks can be virtually impossible. MS is a chronic disease which develops because the immune system has started to attack the nerve cells in the brain. This causes the degradation of parts of the brain and irreversible impairment in physical and mental activity. Unfortunately, this disease has no cure, and while considerable therapeutic advances against this disease have been achieved, …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences

STEM Education

Potential projects available under the topic of STEM Education include:Mathematics educationEngineering educationComputational thinkingMathematical modelling and problem solvingEngaging learners and teachers with novel digital technologies across STEM educationOptimising early mathematics learning through STEM-based modellingIndigenous culture and history: integrating mathematics and virtual reality

Study level
PhD, Master of Philosophy
Faculty
Faculty of Creative Industries, Education and Social Justice
School
School of Teacher Education and Leadership

Page 1 of 3