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 178 matching student topics

Displaying 145–156 of 178 results

Bridging the gap: leveraging AI to improve healthcare access

Access to quality healthcare remains a significant challenge in many parts of the world, often due to geographic and financial barriers. This research explores how artificial intelligence (AI) can address the challenges of geographic and financial barriers in accessing healthcare. The project will focus on developing AI-powered solutions that enhance healthcare delivery, increase patient engagement, and reduce costs

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Public Health and Social Work

Big data analysis to aid ecological research

We're looking for multiple students to help us answer the question: 'How can we utilise information technology to aid ecological research?'Sensor networks bring ecologists and pattern recognition researchers together to make some applications possible. These applications include assessing risks from potential bird collisions, unobtrusive observations (where the presence of humans changes some animal behaviours) and studying spatial and temporal variation in biological processes.With a significant amount of data being collected from these applications, processing and mining this data is challenging. …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science

Enhancing clinical decision-making through AI-assisted agents

Artificial Intelligence (AI) has shown tremendous potential in revolutionizing healthcare delivery. This research focuses on developing AI agents that can augment clinical decision-making processes, ultimately improving patient outcomes. The project aims to explore and design novel AI architectures that integrate disparate medical data sources, providing context-aware recommendations for diagnosis, treatment planning, and care coordination. Despite the promising applications of AI in healthcare, significant challenges remain in integrating these technologies into clinical practice effectively and safely.

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Public Health and Social Work

Semantic SLAM for robotic scene understanding, geometric-semantic representations for infrastructure monitoring and maintenance

Making a robot understand what it sees is one of the most fascinating goals in our current research. To this end, we develop novel methods for Semantic Mapping and Semantic SLAM by combining object detection with simultaneous localisation and mapping (SLAM) techniques.We work on novel approaches to SLAM that create semantically meaningful maps by combining geometric and semantic information. Such semantically enriched maps will help robots understand our complex world and will ultimately increase the range and sophistication of interactions …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Keeping carbon – ensuring soil carbon gains through improved grazing management persist through drought in Australia's tropical and semi-arid grasslands

Drought is the biggest barrier to sequestering soil organic carbon (SOC) in soils over the long-term. While options are limited during dry periods, how we manage our pastures prior to drought can influence the resilience of SOC to losses and enhance recovery.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Biology and Environmental Science
Research centre(s)
Centre for Agriculture and the Bioeconomy

Combining solar and vibration energy harvesting for rainfall prediction

Rainfall prediction plays a crucial role in various sectors such as agriculture, water resource management, and disaster preparedness. Traditional prediction methods often rely on complex meteorological models and expensive equipment. However, advancements in energy harvesting technology offer the opportunity to develop low-cost and sustainable solutions for rainfall prediction.This project proposes to leverage solar and vibration energy harvesting for rainfall prediction. Combined measurements from both solar and vibration energy harvesting can provide comprehensive data for real-time monitoring of cloud coverage and …

Study level
Honours
Faculty
Faculty of Science
School
School of Information Systems

The efficacy of Mental Health First Aid (MHFA) training in community sport

Organised sport is primarily community based in Australia; and the benefits of sport participation to individuals and communities are well documented. However, there is also evidence that participating in organised high-performance sporting programs is associated with psychological distress, elevated relative to community norms, which would usually warrant a need for care by a health professional. As such a case for improvement in mental health education and practice in sporting communities exists.Mental Health First Aid (MHFA) is a standardised, psychoeducational programme …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Exercise and Nutrition Sciences

Therapeutic opportunities targeting epigenetic-metabolism crosswalks in cancer

Epigenetic and metabolic pathways in cancer cells are highly interconnected. Epigenetic landscape in cancer cells is modified by oncogene-driven metabolic changes. Metabolites modulate the activities of epigenetic modifying enzymes to regulate the expression of specific genes. Conversely, epigenetic deregulation that occurs in cancer affect the expression of metabolic genes, thereby altering the metabolome. These changes all coordinately enhance cancer cell proliferation, metastasis and therapy resistance.The overall aim of the project is to understand the link between the activity of epigenetic …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Health
School
School of Biomedical Sciences

Characterisation of melanoma cell membranes to identify novel drug targets

Cell membrane structure and function are altered during tumour development, but to date comprehensive studies on the characterisation of cell membranes of a given cancer are scarce, or are only focused on a particular property (e.g. overall charge, global lipid composition, or specific lipid). In preliminary work we compared the lipidome (i.e. the lipid profile) of a panel of cells, and found the lipid composition of model melanoma cells to be distinct from that of other cancerous and non-cancerous cells. …

Study level
PhD
Faculty
Faculty of Health
School
School of Biomedical Sciences

Development of peptides as therapeutics to treat drug-resistant metastatic melanoma

Melanoma is a very aggressive cancer due to its metastatic potential, and the third most common in Australia. Many patients with metastatic melanoma have strong side effects, do not respond, or develop resistance to current therapies, which results in low survival rate (26% in 5-years). This project aims at developing a new class of therapeutic leads to tackle drug-resistance in metastatic melanoma.Currently, the preferred first-line regimen given to patients with metastatic melanoma is immunotherapy with antibodies (i.e. ipilimumab and nivolumab), …

Study level
PhD
Faculty
Faculty of Health
School
School of Biomedical Sciences

Spatial localisation of immunoglobulin A in the gastrointestinal tract.

Blood cancers, which include leukaemia, lymphoma and myeloma account for 10% of all cancers and 9.4% of cancer deaths. Stem cell transplantation (SCT) is the predominant curative therapy for these diseases. However, a major complication is graft-versus-host disease (GVHD) in which the gastrointestinal (GI) tract, skin, lung and liver are preferentially damaged by the transplanted donor immune system, limiting the therapeutic potential of this treatment. Thus, there is a pressing need for new treatment approaches to improve transplant outcome for …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Health
School
School of Biomedical Sciences

Systematic evaluation towards the analysis of open-source supply chain on ML4SE tasks

Applying machine learning algorithms to source code related SE task is rapidly developing and attracts the attention from both researchers and industry engineers. While there are many program languages available, applying such techniques, i.e., the representation learning models, for different languages may achieve different performance. Particularly, they all have their own strict syntax, which determines the abstract syntax tree. Thus, a lot of different open-source supply chain are available, for example the parsing tools are used to build AST from …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Computer Science

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