PhD Opportunities in Smart Process Design, Fluidized Beds, and AI for Low-Carbon Metallurgy Monash University in Australia

The ARC Research Hub for Smart Process Design and Control at Monash University is offering two fully funded PhD opportunities. The Hub focuses on developing and applying advanced computational technologies to optimize complex particulate processes, with a strong emphasis on cutting-edge research, advanced technology, and international collaboration.

Project 1 involves commissioning and operating a purpose-built cold experimental fluidized bed model to characterize fluidization regimes, particle segregation, and attrition using industrially-relevant DRI materials. Applicants for this project should have a background in experimental design, familiarity with data analysis tools such as Python or Matlab, CFD-DEM, and high performance computing.

Project 2 centers on AI development and applications for low-carbon metallurgy. Candidates should have a background in data science or computer science at both undergraduate and master's levels. The research will contribute to the advancement of low-carbon technologies in metallurgy, leveraging artificial intelligence and computational methods.

Both positions are supervised by Associate Professor Shibo Kuang and Professor Sankar Bhattacharya, both based at Monash University, Australia. The standard Monash University living scholarship will be provided for a maximum period of 3.5 years, covering living expenses. The Hub encourages applications from domestic and female students.

To apply, interested candidates should send a CV outlining their academic and industry experience, as well as their publication record, to Professor Sankar Bhattacharya ([email protected]) and copy Associate Professor Shibo Kuang ([email protected]). For more information, visit the ARC Research Hub for Smart Process Design and Control's LinkedIn page.

Key research areas include smart process design, fluidized bed modeling, low-carbon metallurgy, artificial intelligence, computational technologies, data science, CFD-DEM, and high performance computing. This is an excellent opportunity for students interested in interdisciplinary research at the intersection of chemical engineering, mechanical engineering, computer science, and materials science.