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Vanadium Extraction and Processing Innovation Project’
This project aims to advance the projects related to vanadium extraction and processing from the Toolebuc Formation in North Queensland and to develop capacity in North Queensland to assist with the emerging vanadium economy .
Curing arthritis using novel compounds from jellyfish venom (Old ID 27568)
This research aims to determine if a specific fraction of the venom from the box jellyfish Chironex fleckeri, relieves the symptoms in induced rheumatoid arthritic mice by either i) decreasing the severity of the damage in joints of mice, i.e. curing the disease or ii) decreases the pain associated with the disease but does not decrease the underlying disease.
Advancing the chemistry of rare earths-an Australian resource (Old ID 27702)
This project aims to advance knowledge of the synthesis, structures and reactivity of highly reactive rare earth metal-organic compounds. The project expects to build the knowledge and skills to underpin many developments of Australia's still under utilized rare earth resources to diversity from Chinese domination. The expected outcomes will be new synthetic and reaction chemistry including a demonstration of how size and electronic factors can be used to modify and advance rare earth chemistry and related heavy group 2 chemistry. This project should provide significant benefit such as are a better knowledge base in rare earth chemistry to underpin future applications in chemical manufacturing, new materials, catalysis and recycling.
Data-Efficient AI for Precision Weed Monitoring in Tropical Forests
Reforestation plays a critical role in enhancing climate resilience, increasing carbon sequestration, and supporting ecosystem restoration in tropical regions. However, early-stage seedlings face a major threat from the rapid spread of aggressive weed species that compete for essential resources such as light, nutrients, and water. Traditional weed control approaches are labour-intensive, costly, and unsuitable for large or remote reforestation sites, making automated solutions highly desirable.
This PhD project aims to develop AI-driven computer vision systems for precise and efficient weed detection in tropical reforestation settings. Using aerial and ground imagery, the project will focus on building robust and accurate algorithms capable of operating under challenging environmental conditions. To reduce reliance on large annotated datasets, the research will explore data-efficient learning strategies, enabling scalable and cost-effective model development.
The system will be designed for deployment on drones and ground-based platforms, supporting real-time monitoring and decision-making in the field. By improving the accuracy and efficiency of weed detection, the project will help land managers target interventions more effectively, enhance seedling survival rates, and increase the overall success of reforestation programs. This work will contribute to advancing the application of AI and computer vision for environmental restoration, with strong pathways for real-world adoption and commercialisation through industry collaboration.
Assessing risk within social-ecological systems. Using capacity building to operationalise a spatial decision support tool, guiding resilient livelihood development in Solomon Islands (Old ID 27802)
Rural coastal communities in the Solomon Islands are experiencing increasing impact from food insecurity, poverty, and global change. To help inform negotiations and decision making in relation to resilient livelihood development a risk-based spatial decision support tool (SDST) has been developed. SDST outputs identify the key environmental, socioeconomic, and institutional factors that contribute to community-level risk. To build the long-term impact of the project, a capacity building model has been developed which focuses on training in-country partners to independently operationalise the SDST within Solomon Islands. This supports the broader application of the SDST within the region, advancing its potential to contribute to resilient livelihood development.
Feral Pig Reduction for Improved Wetland Health in the Southern Gulf Region
The Southern Gulf NRM are conducting wild pig control works to protect wetlands across the Southern Gulf region. JCU will develop and implement a Wetland Health Report Card. This will involve establishing a monitoring program to collect and analyse data on wetland and riverine health across the Southern Gulf of Carpentaria. Monitoring will include assessing water quality, biodiversity via eDNA metabarcoding, and conducting aquatic habitat assessments.
Feral Pig Reduction for Improved Wetland Health in the Southern Gulf Region
The Southern Gulf NRM are conducting wild pig control works to protect wetlands across the Southern Gulf region. JCU will develop and implement a Wetland Health Report Card. This will involve establishing a monitoring program to collect and analyse data on wetland and riverine health across the Southern Gulf of Carpentaria. Monitoring will include assessing water quality, biodiversity via eDNA metabarcoding, and conducting aquatic habitat assessments.