Student topics

Quantum machine learning is the integration of quantum algorithms within machine learning programs with great potential to solve complex problems. For instance, Google’s Sycamore processor (61) performs in 200 seconds a task that would require 10,000 years using a classical computer.

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

I am looking for highly motivated and talented PhD students to work with us on robot localisation and navigation. The students would join my DECRA Fellowship project "Adaptive and Efficient Robot Positioning Through Model and Task Fusion" funded by the Australian Research Council, which provides substantial top-up scholarships in addition to QUT's tax-free base stipend.Robot positioningWhere are you? This is a fundamental question to which most of us usually know the answer. And so do the birds singing in our …

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Research centre(s)

Centre for Robotics

As part of an ARC Future Fellowship project awarded to Luis Pedro Coelho, we aim to study small proteins with the aim of better understanding them and laying the groundwork for exploiting them for biotechnological purposes. Small proteins (up to 100 amino acids, but often much shorter) have vital roles in all areas of life, but have been neglected in research due to lack of methods.Particular projects in this topic include developing methods for determining function based on genomic context, …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Health

School

School of Biomedical Sciences

Research centre(s)

Centre for Microbiome Research

Metagenomics data is complex, high-volume data and keeps evolving, requiring novel computational method development as the wetlab approaches changes and databases grow. Thus, novel computational methods are required to take advantage of them.There are several potential projects under this topic, including:using deep learning to improve metagenomics assemblydeveloping better tools to analyse the presence of resistance genes in metagenomics datadeveloping approaches for estimating the quality of genomes from novel generation sequencespredicting the function of small sequences using more than just sequence.Interested …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Health

School

School of Biomedical Sciences

Research centre(s)

Centre for Microbiome Research

Join a world-leading research team examining how recommender systems are shaping personalised and shared experiences of algorithmic culture in Australia. The project is focused on TikTok and engages with both professional TikTok creators and users using innovative computational and traditional research approaches.The empirical work is structured into three streams:In the Platform Stream we observe the type of content TikTok recommends on the least-personalised version of the platform, to create a close-to-generic baseline of the Australian experience of algorithmic culture on …

Study level

PhD

Faculty

Faculty of Creative Industries, Education and Social Justice

School

School of Communication

Research centre(s)

Digital Media Research Centre

In process mining, we perform computational analyses of sequential data in order to help organisations improve, in settings from ride-sharing platforms to government departments. In social sequence analysis, we perform computational analysis on sequential data to understand small or large structures in society, such as the progress of careers of 18th century German musicians, or the progress of nations through different stages of economic development.In both process mining and social sequence analysis, calculation of "alignments" for is a key technique …

Study level

Honours

Faculty

Faculty of Science

School

School of Information Systems

In process mining, sequence analysis algorithms are used to discover computational models of process data, and to analyse them. The insights from these models and analysis then improve the processes in organisations in many real-life domains - from manufacturing, to government, to healthcare. Haskell is a powerful functional programming language well suited to problems involving formal reasoning and pattern matching. This project would advance process mining research by building high-quality, high performance libraries in Haskell for fundamental process mining activities …

Study level

Honours

Faculty

Faculty of Science

School

School of Information Systems

The increase in global energy demand necessitates further advancement in photovoltaic (PV) systems. Advancements in PVs could potentially play a role to help meet the Paris Agreement of limiting global temperature increase to below 2 degrees Celsius. In conjunction with the rising demand for clean energy production, the global agricultural industry needs to keep pace with rising food demand which is expected to increase by 50% by 2050 to feed over a projected 10 billion people. The scarcity of fertile …

Study level

PhD, Honours

Faculty

Faculty of Engineering

School

School of Mechanical, Medical and Process Engineering

Epilepsy is a serious and debilitating condition which is grossly under-researched despite the devastating impact it can have. Damage to the vast language processing network of the brain during surgical resection can cause aphasia, a devastating communication disability. This project aims to determine reliable pre-surgical mapping and outcome predictors in epilepsy resection: To 1) develop a reliable and comprehensive battery to map the language network in pre-surgical epilepsy patients with different foci, and 2) assess how the reorganisation of the …

Study level

PhD, Master of Philosophy

Faculty

Faculty of Health

School

School of Clinical Sciences

Research centre(s)

Centre for Biomedical Technologies

Radiation therapy (RT) is one of the most commonly used modalities in cancer treatment, usually delivered in combination with surgical intervention, chemotherapy, and immunotherapy.However, clinical outcomes show that almost 20% of patients fail to achieve targeted outcomes because of inherent resistance to radiation. This necessitates in-depth understanding of radiation resistance mechanisms using relevant preclinical models of RT. Previous in vitro studies have predominantly used two-dimensional (2D) cell culture models that do not recapitulate the three-dimensional (3D) complexity of native tissues.

Study level

Honours

Faculty

Faculty of Engineering

School

School of Mechanical, Medical and Process Engineering

Research centre(s)

Centre for Biomedical Technologies

This project aims to address the urgent problem of isolation, dislocation of families by distance and lack of 'intergenerational closeness' by developing ways to build stronger bonds between geographically distributed families using tangible, embodied and embedded interfaces (TEIs). TEIs combine physical artefacts and digital information, allowing interactions across a variety of spaces, and in combination with other activities and experiences.

Study level

PhD

Faculty

Faculty of Creative Industries, Education and Social Justice

School

School of Design

Research centre(s)

Design Lab

High-throughput screening assays are essential for accelerating drug discovery, but current assays often rely on endpoint measurements that do not capture the dynamic response of cells to drug treatment. Machine learning algorithms (MLAs) have the potential to enable real-time, high-throughput monitoring of cell response to drug treatment by analyzing complex datasets generated by multiplexed live-cell assays. This research project aims to develop an MLA for enabling high throughput cell response data in drug treatment. The project will involve three main …

Study level

Honours

Faculty

Faculty of Engineering

School

School of Computer Science

Research centre(s)

Centre for Biomedical Technologies
Centre for Biomedical Technologies