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 462 matching student topics
Displaying 457–462 of 462 results
Characterizing effects of radiation therapy in 3D bioengineered cancer models
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
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Biomedical Technologies
Designing distanced intergenerational interaction with tangible technology
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
- School
- School of Design
- Research centre(s)
-
Design Lab
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
Leveraging Big Data and AI/ML for Smart Transport Solutions
This PhD position aims to harness the potential of big traffic and mobility data alongside cutting-edge AI/ML algorithms to pioneer innovative solutions for optimizing smart motorways and/or arterial traffic flow. By leveraging these technologies, the project endeavours to develop and test smart algorithms, with the goal of significantly enhancing the efficiency and safety of road networks.Send via email to Prof. Ashish Bhaskar (ashish.bhaskar@qut.edu.au):a brief statement detailing your suitability for the positiona detailed curriculum vitae, including a list of publications, if …
- Study level
- PhD
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Data Science
Evaluating Navicare to improve mental health service access in regional Australia
Improved access to appropriate and timely mental health care for people in outer regional and remote areas is needed in Australia where people are disproportionately affected by severe mental health conditions. Navicare is a model of care co-designed and piloted with communities and service providers and implemented in 2021 to address this issue. In 2022 national funding from National Health and Medical Research Council was obtained to evaluate the implementation of Navicare in three new communities in Central Queensland in …
- Study level
- Honours
- School
- School of Public Health and Social Work
- Research centre(s)
- Centre for Healthcare Transformation
Australian Centre for Health Services Innovation
Infrared signatures and spectral decomposition: Identifying and analysing accreting supermassive black holes
This project aims to explore the identification and properties of accreting supermassive black holes, commonly known as active galactic nuclei (AGN), by cross-matching the FourStar Galaxy Evolution Survey (ZFOURGE) with the Wide-field Infrared Survey Explorer (WISE) data. Using WISE infrared colors to pinpoint AGNs and comparing these findings with results from the spectral energy distribution (SED) decomposition on ZFOURGE data, you will enhance AGN identification techniques and deepen our understanding of their physical characteristics. This comparative approach will improve our …
- Study level
- Vacation research experience scheme
- School
- School of Chemistry and Physics
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