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 293 matching student topics

Displaying 1–12 of 293 results

Evidence-Based Teaching in Economics and Business

Evidence-based teaching (EBT) refers to “the conscientious, explicit, and judicious integration of best available research on teaching technique and expertise within the context of student, teacher, department, college, university, and community characteristics” (Groccia & Buskist 2011). In practice, EBT involves educational practices derived from empirical data that show a well-established association with improved course grade, student feedback, and course-driven learning goals. Literature on EBT is growing but there is little on the impact of EBTs on students, academics as well …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Business and Law
School
School of Economics and Finance

Digital publics

Digital and social media platforms provide new opportunities for public communication, and the formation of distinct publics and communities around shared interests and identities. Such publics may engage in political debate, popular media fandom, science communication, vernacular creativity, and other activities; but they may also be affected by, or actively engage in promoting, mis- and disinformation and other problematic content. Their activities are also shaped by the features and affordances of the platforms they use, from Facebook and Twitter to …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Creative Industries, Education and Social Justice
School
School of Communication
Research centre(s)
Digital Media Research Centre

Evaluation of language models and word embedding methods for natural language processing applications

In deep learning models, language models and word embedding methods have become popular to understand the context of text data. There exist many variants of these methods and have different limitations. This project will introduce you to the hot topic of language models and the fields of Natural Language Processing and Text Mining. 

Study level
Honours
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

Curvature dependence of reaction-diffusion wave front speed with nonlinear diffusion.

Reaction-diffusion waves describe the progression in space of wildfires, species invasions, epidemic spread, and biological tissue growth. When diffusion is linear, these waves are known to advance at a rate that strongly depends on the curvature of the wave fronts. How nonlinear diffusion affects the curvature dependence of the progression rate of these wavefronts remains unknown.

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

Optimising bone shape with memory networks

Bone is a dynamic tissue that optimises its shape to the mechanical loads that it carries. Bone mass is accrued where loads are high, and reduced where loads are low. This adaptation of bone tissue to mechanical loads is well-known and observed in many instances. However, what serves as a reference mechanical state in this shape optimisation remains largely unknown.

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

Building explainable and trustworthy intelligent systems

Existing machine learning-based intelligent systems are autonomous and opaque (often considered “black-box” systems), which has led to the lack of trust in AI adoption and, consequently, the gap between machine and human being.In 2018, the European Parliament adopted the General Data Protection Regulation (GDPR), which introduces a right of explanation for all human individuals to obtain “meaningful explanations of the logic involved” when a decision is made by automated systems. To this end, it is a compliance that an intelligent …

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

Surprising genomes

Genomic sequencing has changed radically since the first public sequencing projects more than 25 years ago. The original human genome project cost more than two billion dollars; sequencing a human genome now costs as little as a thousand, and we may sequence whole viruses and bacteria as a matter of routine.The challenge now lies in rapidly analysing these genomes as they appear, and understanding quickly whether there is anything interesting in the new sequence to warrant further inquiry. This project …

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

Explainable AI-enabled predictive analytics

Modern predictive analytics underpinned by AI-enabled learning (such as machine learning, deep learning) techniques has become a key enabler to the automation of data-driven decision making. In the context of process monitoring and forecast, predictive analytics has been applied to making predictions about the future state of a running process instance - for example, which task will be carried out next, when and who will perform the task, when will an ongoing process instance complete, what will be the outcome …

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

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
Faculty
Faculty of Science
School
School of Mathematical Sciences

Representation learning for anti-microbial resistance

This project is about using neural network models help us understand Anti-Microbial Resistance (AMR), a phenomenon in which bacteria adapt to reduce the effectiveness of antibiotics, usually through a process known as Lateral or Horizontal Gene Transfer - where genes are included in the organism from other sources.Our focus will be on learning compact vector representations of biological sequences known to be associated with AMR genes. By encoding DNA sequences in this way we can more rapidly identify AMR genes …

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

Scalable software solutions for improving the CRISPR gene editing system

The CRISPR-Cas9 technology allows the modification of virtually any gene in any organism of interest. It has generated a lot of interest, both in the research community and the general population.One of the crucial components of CRISPR experiments is the design of the 'guide RNAs' that will control where modifications occur. We have developed a software pipeline, named Crackling, to identify safe and effective guide RNAs across entire genomes.We are seeking to expand and improve various aspects of our current …

Study level
Honours
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

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