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Found 66 matching student topics

Displaying 1–12 of 66 results

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, 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

Participatory Visualisation of Smart City Data

This PhD project will be affiliated with FrontierSI and Value Australia and contribute to its goals and objectives around smart cities, digital twins, and automated land valuations. Although consumers contribute much of the data upon which these smart city technologies operate, its systems often remain opaque black boxes closed off to public understanding, scrutiny and control. There are also serious concerns around privacy and loss of autonomy.This PhD project addresses these issues by exploring new methods for the participatory visualisation …

Study level
PhD
Faculty
Faculty of Creative Industries, Education and Social Justice
School
School of Design
Research centre(s)

Design Lab

Capturing the impact of patient variability in a novel cancer treatment

In 2015, the Food and Drug Association (FDA) approved a lab-engineered virus for the treatment of melanoma (skin cancer). Since then, there has been a significant increase in the number of lab-grown viruses that are being tested in clinical trials as potential treatments of cancer. Unfortunately, it seems that a large number of patients in these clinical trials fail under this treatment and currently there is no way to distinguish between responders and non-responders to treatment.Fortunately, we can use mathematics …

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

Decision modelling for data quality

Data quality informs organisations about (1) how well data is built regarding the number of times that the data fails to meet stated requirements, and (2) how usable the data is in terms of the reliability of the data in a specific context. It has been demonstrated that Decision Model and Notation (DMN), a standard of the Object Management Group (2022), enables the assessment of data quality based on the evaluation of business rules, and supports the automation of the …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)

Centre for Behavioural Economics, Society and Technology

Scalable and privacy-preserving publish-subscribe for data sharing

The publish-subscribe communication protocol is widely used in real-world data-driven applications. Data producers and consumers share their data using the publish-subscribe communication protocol, which relies on a centralized data sharing server. As the data load increases, the publish-subscribe broker fails to meet the real-time demands of the applications.This project will investigate and develop a scalable and privacy-preserving publish-subscribe protocol.

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

Predicting how fast the next Olympic medalists will swim

A 3-year strategic partnership on sports data science between the Centre for Data Science (CDS), the Australian Institute of Sport (AIS) and the Queensland Academy of Sport (QAS) is currently under way. With a drive towards data informed decision making across the high performance sports network nationally, a number of collaborative, interdisciplinary research and scholarship opportunities ranging from VRES, to honours, masters and PhD have developed.

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

Transport big data analytics: Imputing missing data

The missing data problem is often unavoidable for real-world data collection systems because of a variety of factors, such as sensor malfunctioning, maintenance work, transmission errors, and so on. Filling in missing information in a dataset is an important requirement for many machine-learning algorithms that require a complete dataset as input. Data imputation algorithms aim at filling the missing information in a dataset. Many missing data imputation techniques exist in the literature, with applications demonstrated on various types of datasets. …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Engineering
School
School of Civil and Environmental Engineering
Research centre(s)
Centre for Data Science

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

Making the most of many models

In the age of Big Data, machine learning methods, and modern statistics the adage "all models are wrong but some are useful" has never been so true. This project will investigate data science approaches where more than one model makes sense for the data. Is it better to choose a single model or is there something to be gained from multiple models?This project will look at variable selection methods, penalised regression, Bayesian model averaging and conformal prediction. The research has …

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

Advances in hypothesis testing

You would have learnt about several hypothesis tests already in your degree, such as t-tests and F-tests (think ANOVA). These tests are designed for the situation where you have a single hypothesis you want to check and you know how many observations you’re going to collect before you collect your data.Unfortunately, these assumptions can be problematic in real applications. For example, consider the situation where it’s time-consuming and expensive to collect data. Can you stop early if you’re getting very …

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

Data-driven and process-aware workforce analytics

Modern information systems in today’s organisations record massive amount of event log data capturing the execution of day-to-day core processes within and across organisations. Mining these event log data to drive process analytics and knowledge discovery is known as process mining. To date various process mining techniques have been developed to help extract insights about the actual processes with the ultimate goal to organisations' workforce capability and capacity building.As an important sub-field of process mining, organisational mining focuses on discovering …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Data Science

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