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 6 matching student topics
Displaying 1–6 of 6 results
Novel algorithms for microbiome data
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)
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Centre for Microbiome Research
Reinforcement learning for fair and ethical AI systems
This project studies how reinforcement learning (RL) can help make automated decisions fairer. Instead of fixing fairness after training, fairness is built into the learning process to create more equal outcomes for different groups. The focus is on important areas like hiring, healthcare, and finance, where biased AI can cause real harm.The aim is to reduce unfair bias while keeping the system accurate, helping create AI that is both effective and socially responsible. You will learn about advanced RL methods, …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Virus Search Algorithms
Meta-heuristics are powerful search algorithms for solving intractable optimization problems. There are many population based approaches, like genetic algorithms, evolutionary algorithms, particle swarm, etc. but most of these have a static population size.Viruses arise and attack populations periodically. They typically appear when populations become abundant. Viruses infect population members, and often reduce the number of individuals. Viruses create spaces for more individuals and balance competition.The concept of viruses may be mimicked and could be a useful optimization paradigm.
- Study level
- Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
Development of a machine learning algorithm for high throughput cell response data in drug therapy
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
Australian experiences of algorithmic culture on TikTok
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
Tree-chain: a fast lightweight consensus algorithm for IoT applications
In recent years, blockchain adaptation in IoT has received tremendous attention due to its salient features including distributed management, security, anonymity, and auditability. However, conventional blockchains are significantly resource demanding and suffer from lack of throughput, delay in committing transactions, and low efficiency. We recently introduced a novel blockchain consensus algorithm known as Tree-chain, that bases the validator selection on an existing feature in all blockchains: hash function. Tree-chain achieves a fast throughput while ensuring the randomness and unpredictability of …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Computer Science
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