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
Access to screen culture in an algorithmic age
During the course of their PhD, the candidate will drive a research project that investigates how the use of algorithms in search and recommendation systems affect the discoverability of content, including:long tail and back catalogue contenton subscription video-on-demand (SVOD) servicesinternet platforms.The project will explore how digital tools can be developed and used to study the impacts of search and recommendation systems, and examine the regulatory options that might be used to address potential problems in the discoverability of culturally or …
- Study level
- PhD
- Faculty
- Faculty of Business and Law
- School
- School of Law
- Research centre(s)
- Digital Media Research Centre
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
- School
- School of Biomedical Sciences
- Research centre(s)
-
Centre for Microbiome Research
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
- School
- School of Computer Science
- Research centre(s)
- Centre for Biomedical Technologies
Centre for Biomedical Technologies
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
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
- School
- School of Communication
- Research centre(s)
- Digital Media Research Centre
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