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 86 matching student topics
Displaying 37–48 of 86 results
Efficient parameter estimation for agent-based models of tumour growth
Cancer is an extremely heterogeneous disease, particularly at the cellular level. Cells within a single cancerous tumour undergo vastly different rates of proliferation based on their location and specific genetic mutations. Capturing this stochasticity in cell behaviour and its effect on tumour growth is challenging with a deterministic system, e.g. ordinary differential equations, however, is possible with an agent-based model (ABM). In an ABM, cells are modelled as individual agents that have a probability of proliferation and movement in each …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Topics in computational Bayesian statistics
Bayesian statistics provide a framework for a statistical inference for quantifying the uncertainty of unknowns based on information pre and post data collection.This information is captured in the posterior distribution, which is a probability distribution over the space of unknowns given the observed data.The ability to make inferences based on the posterior essentially amounts to efficiently simulating from the posterior distribution, which can generally not be done perfectly in practice.This task of sampling may be challenging for various reasons:The posterior …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Engineering bioartificial extracellular tumour microenvironments for Osteosarcoma personalised precision oncology
Osteosarcoma (OS) is the most common malignant bone tumour affecting children and adolescents. Importantly, clinical outcomes have not improved for decades, and bone tumours remain to be a leading cause of cancer-related death in adolescents.By identifying ideal treatment approaches for each individual patient, precision oncology has the potential to significantly improve these outcomes. Yet, its widespread application is hindered by a lack of biomaterials that support the reproducible and robust generation of patient-derived osteosarcoma organoids in vitro.Therefore, this project will …
- Study level
- PhD, Master of Philosophy
- School
- School of Biomedical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
Efficient Parameter Estimation for Stochastic Simulations
Stochastic simulation-based models are routinely used in many areas of science to describe inherent randomness in many real-world systems. Applications include the study of particle physics, imaging if black holes, biochemical processes, the migration of animals, and the spread of infectious diseases. To apply these models to interpret data requires statistical methods to estimate model parameters.Unfortunately, standard statistical techniques are not capable of analysing data using these models. This is largely due to the model likelihood, the probability of the …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data 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
Next-generation traffic signals for Safe, Efficient and Green Intersections
There is a full PhD scholarship available in the School of Civil and Environmental Engineering at Queensland University of Technology (QUT) to support the newly awarded ARC Linkage Project on Next-generation traffic signals using artificial intelligence-based video analytics for safe, efficient and green intersections. The stipend has a cash value of $32,500 per annum for 3 years.To apply for this position, please submit the following documents via email to m1.haque@qut.edu.au:a detailed curriculum vitae (CV) highlighting academic achievements, research experience and …
- Study level
- PhD
- School
- School of Civil and Environmental Engineering
Sustainable energy transition with system dynamics
The challenge to keep global warming to 1.5°C above pre-industrial levels has become even greater due to a continued increase in greenhouse gas emissions (IPCC, 2023). One major challenge is the shift from fossil fuels to renewable energy to reduce emissions (Gholami et al., 2016). The share of renewable energy in electricity generation has increased to 28.3%, however, an acceleration of the pace of the transition is required to limit global temperature rise (REN21, 2022).New energy policies are needed to …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
Targeting leptin's signalling axis to prevent treatment resistance in prostate cancer
Advanced prostate cancer (PCa) is a leading cause of cancer-associated death in Australian men. Anti-androgens, which exploit the tumour’s reliance on androgens for its growth & spread, offer temporary remission in advanced PCa patients, but due to treatment resistance, fail to be curative. A further complication of anti-androgens is that they trigger a deleterious suite of metabolic side-effects resembling obesity/Metabolic syndrome. These symptoms not only impact patient health but promote tumours to be more aggressive & resist treatment. Vital new …
- Study level
- PhD, Master of Philosophy, Honours
- School
- School of Biomedical Sciences
Restoring adiponectin signalling to prevent prostate cancer progression
Advanced prostate cancer (PCa) is a leading cause of cancer-associated death in Australian men. Anti-androgens, which exploit the tumour’s reliance on androgens for its growth and spread, offer temporary remission in advanced PCa patients, but due to treatment resistance, fail to be curative. A further complication of anti-androgens is that they trigger a deleterious suite of metabolic side-effects resembling obesity/Metabolic syndrome. These symptoms not only impact patient health but promote the tumour to be more aggressive and resist treatment. Vital …
- Study level
- PhD, Master of Philosophy, Honours
- School
- School of Biomedical Sciences
Exploring the potential of M-assisted survey estimators
The Australian Bureau of Statistics (ABS) conducts surveys to collect information from individuals, households and businesses in order to produce statistics and data products to help inform decision-making. Unlike a census, in which an entire population of interest is enumerated (e.g., all individuals residing in Australia), a survey collects information from only a sample (subset) of a population of interest. Estimators are then used to estimate quantities related to the population of interest using information from the sample. Currently, the …
- Study level
- PhD
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Probabilistic forecasting of energy
This project aims to develop probabilistic forecasting models for renewable energies vi a Bayesian approach. The models will be developed for very short term and short-term (10 minutes to 24 hours ahead).
- Study level
- PhD
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Mathematical modelling of cell-to-cell communication via extracellular vesicles (EVs)
Extracellular vesicles (EVs) are membrane bound packages of information constantly being released by all living cells, including bacteria. There are many types and sizes of EVs. Each EV type contains its own distinctive cargo consisting of characteristic DNA, RNA, and proteins. We are just beginning to understand the many roles of EVs to maintain the health of the cell producing the EVs, and to communicate with other cell types that take up the EVs produced by neighbouring cells. Since EVs …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
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