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 650 matching student topics

Displaying 85–96 of 650 results

Big Data ideas for GLMs

The goal of this project is to develop new Bayesian methods for large-scale data analysis using subsampling techniques. The focus of the project will be on generalised linear models (GLMs), which are commonly used models in statistics and machine learning.One of the main challenges in using Bayesian statistics with big data is the high computational cost associated with processing big datasets. The proposed project aims to address this challenge by developing new subsampling techniques for Piecewise Deterministic Markov Process (PDMP) …

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

Continuous time samplers (MCMC at the limit!)

The goal of this project is to develop new continuous time Monte Carlo methods for efficient sampling from high-dimensional distributions. Continuous-time Monte Carlo methods are a class of algorithms that use continuous-time dynamics to generate samples from target distributions, rather than the discrete-time dynamics used in traditional Markov chain Monte Carlo (MCMC) methods. These methods have been shown to have faster mixing and better exploration of the state space, making them particularly appealing samplers for challenging distributions.The main objectives of …

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

Unlocking the Potential of Simplex-Truncated Distributions

This PhD project aims to develop new methods for generating random samples from a specific type of probability distributions called simplex-truncated distributions. These distributions are commonly used in various fields such as statistics, machine learning, and biology.The project will involve the development of new techniques to generate random samples from simplex-truncated distributions. These techniques are based on a method called continuous-time Monte Carlo which is a cutting edge method in statistics that can generate random samples from complex distributions.The main …

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

Mapping the world: understanding the environment through spatio-temporal implicit representations

Accurately mapping large-scale infrastructure assets (power poles, bridges, buildings, whole suburbs and cities) is still exceptionally challenging for robots.The problem becomes even harder when we ask robots to map structures with intricate geometry or when the appearance or the structure of the environment changes over time, for example due to corrosion or construction activity.The problem difficulty is increased even more when sensor data from a range of different sensors (e.g. lidars and cameras, but also more specialised hardware such as …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics
Research centre(s)
Centre for Robotics

Low-cost portable Magnetic Resonance Imaging for clinical applications

The aim of this project is to develop accurate low-cost medical imaging methodology for pseudo-3D mapping of Mammographic Density (MD) within the breast. MD is the degree of radio-opacity (“whiteness”) in an X-ray mammogram. It has implications for breast cancer risk, ease of detection of breast cancer, and monitoring of the efficacy of hormonal breast cancer prevention or anti-cancer treatments.Healthcare ChallengeThere is a growing need for affordable and accurate quantitative assessment of MD without ionising radiation. Magnetic resonance imaging (MRI) …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Chemistry and Physics

Genome to phenome: exploiting multi-omics and deep learning strategies to decipher importance of isoforms in health and behaviour

The molecular process that leads to multiple mRNA transcripts being produced from the same segment of DNA (aka gene) is known as alternative splicing (AS). This is a common form of regulation in higher eukaryotes, enabling the production of novel protein isoforms, which in turn are known to have a big impact on phenotype. Understanding the regulatory factors involved in AS, including epigenetic mechanisms such as DNA methylation, will offer key insights into important biological phenomena (health disease, behaviour, production). …

Study level
PhD
Faculty
Faculty of Science
School
School of Biology and Environmental Science

Prescriptive process analytics

With growing significance of data there is a need to harness the potential of that data for improved business operations. Historical data is often to provide a descriptive overview of how business processes have performed in the past. However, there is a need to be proactive and take appropriate actions to ensure that business processes perform in an optimal manner. Prescriptive analytics is a process that analyzes data and provides instant recommendations on how to optimize business practices. Prescriptive analytics …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems

Development of a Microfluidic Gut-Brain Axis Chip

The gut microbiome refers to the collection of micro-organisms that are living symbiotically in the human or animal gastrointestinal tract (defined as the “microbiota”), their genetic material as well as the surrounding environmental habitat. It is now appreciated that the microbiome plays an important role in human health and diseases. Many neurodegenerative diseases, such as Parkinson's Disease have been linked to dysregulation of the gut microbiota. However, it is difficult to study gut-brain axis using animal models due to inter-species …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering
Research centre(s)
Centre for Biomedical Technologies
Centre for Microbiome Research

Human biomarkers of stress, trauma, and memories of fear

Understanding how disorders such as posttraumatic stress disorder develop following trauma is a contemporary challenge for researchers in psychology. The best explanations involve a combination of psychological and biological factors that interact during and following trauma to create a range of troubling symptoms. This project will use cutting edge technology at QUT to provide insights into how a mix of biology and behaviour can result in exacerbated stress responses and threat memories in experimental and real-world settings.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Health
School
School of Psychology and Counselling

Genetics of cardiovascular disease

This research project involves investigating the genetic basis of cardiovascular disease (CVD). The project will focus on the genetically unique population of Norfolk Island. The Norfolk Island Health Study has been running for 20 yrs. Over this time the cardiovascular health of the Islanders has been tracked via the collection of relevant clinical data. In addition whole genome sequence data from the study group has been collected, which will facilitate the discovery of genetic variants that influence CVD phenotypes - …

Study level
PhD
Faculty
Faculty of Health
School
School of Biomedical Sciences
Research centre(s)
Centre for Genomics and Personalised Health

Microfluidic chip-based tumor-immune cancer models for biomarker discovery

In-vitro profiling of tumour-immune cell interactions in proximity can provide valuable insight into patient response to new combinatorial immunotherapies that are in the pipeline and currently being tested in clinical trials. These in-vitro models allow for a more controlled and isolated environment and provide a methodical approach for generating quantifiable data characterizing the interactions between target and effector cells. Traditionally executed in well-plates, tumour-immune models have been slowly moving towards a microfluidic chip-based approach for several reasons: better control over …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering
Research centre(s)
Centre for Biomedical Technologies

Development of a microfluidic sample processing integrated robot (micro SPIN-R)

Microfluidic devices are increasingly relied upon to address the complexity of in-vitro disease models that are intended to mimic and provide insight into in-vivo processes and reactions to novel therapies and in turn, can become powerful companion diagnostic devices essential for predicting and individual patient’s reaction to a particular treatment. However, as these microfluidic devices become more and more prominent and necessary for addressing the drug screening and disease modeling needs of the industry, we have observed a lack in …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering
Research centre(s)
Centre for Biomedical Technologies

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