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 4 matching student topics
Displaying 1–4 of 4 results
Mathematical and statistical methods for change point detection in precision fermentation
Precision fermentation uses microorganisms such as yeast to produce valuable biological products for food, biotechnology and synthetic biology. A major challenge is that microbial growth and production can change when cells switch between different metabolic regimes. These changes may occur because of nutrient depletion, stress responses, dilution conditions, or shifts in how cells allocate resources between growth and product formation.This PhD project will develop new mathematical and statistical methods for detecting these metabolic change points from experimental data. The project …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Detecting metabolic regime switching using dilution-resolved growth data: mathematical modelling, statistical inference and uncertainty quantification
Microbial populations rarely grow according to a single fixed physiological program. As nutrients are consumed, waste products accumulate and environmental stress changes, cells can transition between distinct metabolic regimes associated with growth, maintenance, fermentation, respiration and survival. These transitions are biologically important and industrially relevant, but they are often difficult to detect directly from standard growth curve summaries such as maximum growth rate, lag time, carrying capacity or area under the curve.This project will develop new mathematical and statistical methods …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
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
Moving boundary problems in mathematical biology
Invasion of biological cells or ecological populations involves moving fronts that invade into previously unoccupied regions of space. Such moving fronts are driven by a combination of motility, such as random diffusion, and proliferation, such as logistic growth. Understanding how best to model such invasive fronts is important as moving fronts of cells are associated with wound healing and cancer progression and moving fronts in ecology are associated with the spreading of weeds and invasive species.Previously both continuum and discrete …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
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