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 49 matching student topics

Displaying 25–36 of 49 results

Medical litigation, medical law and compensation for medical negligence

Tina Cockburn is interested in supervising PhD students in the area of patient safety law — focusing on medical litigation and compensation for medical negligence, communication of information to patients (including consent and post treatment open disclosure), regulation of health care professionals and the regulation of innovative medical treatment and new technologies.

Study level
PhD, Master of Philosophy
Faculty
Faculty of Business and Law
School
School of Law
Research centre(s)

Australian Centre for Health Law Research

Advanced artificial intelligence based ultrasound imaging applications

Our research in the space of advanced quantitative medical imaging is investigating how to use ultrasound as a real time volumetric mapping tool of human tissues, to guide in a reliable and accurate way complex medical procedures1. We have developed several novel methods which make use of the most cutting-edge artificial intelligence technology2. For example, to show where the treatment target and the organs at risk are at all times during treatments in radiation therapy3, 4; or to inform robots …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Clinical Sciences
Research centre(s)
Centre for Biomedical Technologies

Comprehensive strain-level characterisation of microbial communities associated with inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic, relapsing inflammatory disorder driven by complex interactions between environmental, microbial and immune-mediated factors 1,2. An unfavourable shift in gut microbiome composition, known as dysbiosis, is now considered a key feature of IBD 2-5, however it is unclear how specific microorganisms and their interactions with host cells contribute to disease onset and progression.Previous IBD studies have been largely limited to older sequencing methods with low phylogenetic and functional resolution. Furthermore, these studies have predominantly …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Health
School
School of Biomedical Sciences
Research centre(s)

Centre for Microbiome Research

Using systems architecture to model neuropathic pain

Neuropathic pain effects '1 in every 10 adults over the age of 30'. The treatments available for neuropathic pain can at best be described as having 'moderate efficacy'. Due to the nature of neuropathic pain, the ability to scientifically study and understand its fundamental causes has been limited to animal models and trials. There are over 27 animal models for neuropathic pain where pain has been induced by macroscopic and microscopic nerve lesions, chemotherapy, viral infections and diabetes mellitus.Looking at …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering

A soft robotic manipulator for spinal surgery

The geriatric population in Australia (4.2 million 2020, ABS), is growing steadily with numbers expected to double in the coming years. Incidences of spinal disorders requiring surgical treatment are therefore predicted to increase, incurring an estimated lifetime cost of AUD 3.7 billion per case (The Treasury). Robotics, an increasingly important component of modern medicine, is well suited to address the minimally invasive surgical needs of treating the spine.This project proposes the use of a soft-robotic manipulator to carry out spinal …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics
Research centre(s)
Centre for Robotics

Unveiling the explainability imperative in medical AI

As AI systems become increasingly prevalent in medical applications, the need for explainable AI (XAI) has become crucial. This research investigates the critical issue of explainability in medical artificial intelligence (AI) systems. This project investigates methods for improving the interpretability and transparency of AI models used in medical diagnosis, treatment planning, and prognosis prediction. Understanding the reasoning behind AI-driven decisions is essential for building trust among healthcare professionals and ensuring patient safety.

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

Achieving a sub-micrometer surgical robot end-effector via hybrid sensing

When operating with a tool within the human body in the context of a medical procedure, it is crucial to be able to keep track of the pose of the tool. This project will develop a hybrid approach to end effector pose estimation by combing optical tracking with other sensor inputs (e.g. force, sound, acoustic emissions) to compliment and improve tracking accuracy with applications towards orthopaedic surgical robots. This project is part of a broader collaboration with industry partner Stryker.

Study level
PhD
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering
Research centre(s)
Centre for Biomedical Technologies

Tracking small bones for robotic surgery

Robotic knee surgery can perform femoral and tibial resection. Currently it is not possible to use robotic technology for patella preparation; to do so will require miniaturisation of tracking, effective clamping of the patella and controlled use of a saw. This project will aim to develop the technology for any small bone resection with a robot, taking the patella as a test case.

Study level
PhD
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering
Research centre(s)
Centre for Biomedical Technologies

Dexterous tools with variable stiffness for minimally invasive surgery

Robotics has a positive impact on surgical procedures. This is particularly the case with minimally invasive surgeries. In these procedures, there is a need for compact tools that can be inserted through a tiny opening but are versatile in function. This project will look at the design of dexterous alternatives to traditional surgical tools within this context. Methods to vary the workspace and stiffness of the tool will be investigated by combining inspiration from the design of miniature biological joints …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics
Research centre(s)
Centre for Robotics

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

Medication and dietary supplement use and symptom severity of chemotherapy-induced peripheral neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is highly prevalent and clinically problematic, occurring in up to 60–80% of people receiving chemotherapy. Despite the high prevalence and significant patient and healthcare burden of CIPN, treatment options are limited.This project will explore the association between medication and dietary supplement use and symptom severity of CIPN to identify factors that might worsen or improve CIPN symptoms.

Study level
Honours
Faculty
Faculty of Health
School
School of Nursing
Research centre(s)
Centre for Healthcare Transformation
Cancer and Palliative Care Outcomes Centre

Drone ship landing under adverse sea condition

Estimating the motion of a landing deck, and controlling the descent of a drone under severe weather events is a challenging task. We have developed a simulation environment to test control and prediction algorithms that could allow a drone to safely land on a ship. This PhD program involves the investigation of innovative predictive control approaches closely linked with predictors that provide T secs ahead the future position of the landing deck.

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

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