QUT researchers have partnered with mining company Lava Blue and the Innovative Manufacturing Cooperative Research Centres (IMCRC) to set up a pilot plant. This pilot plant will transform kaolin clay into high-purity alumina (HPA) which is used to make LEDs and lithium-ion batteries.
As a part of this project, you will use machine learning techniques to optimise the extraction of alumina and minimise impurities in the process.
You will apply machine learning techniques to a dataset describing elemental composition of different processes. From the developed models output, you will provide guidance for further experiments to refine the models.
A predictive model and techniques for optimising different parts of the alumina extraction process.
Skills and experience
As the ideal student you are both highly motivated and interested in the following:
- data science
- programming (Python desirable)
A background in chemical processing is highly desirable.
Contact the supervisor for more information.