JOB DESCRIPTION

As part of Tata Steel’s decarbonisation strategy, the blast furnace burden is undergoing a transformation. Traditional materials like pellets are being replaced or supplemented with low-carbon alternatives such as HBI, DRI, and scrap. These changes introduce new challenges in maintaining furnace stability, gas flow, and productivity.
This PhD project focuses on developing and applying advanced Discrete Element Method (DEM) models to simulate the charging and formation of multi-component, poly-disperse burden mixtures in the blast furnace. The goal is to optimize burden structure and permeability, enabling reduced coke rates and improved operational efficiency.

In your role you will:

• Combine and extend existing burden charging models developed in previous projects.
• Apply DEM simulations to study segregation, packing structure, and gas-solid contact in diverse burden mixtures.
• Investigate the impact of new materials on burden formation and blast furnace performance.
• Collaborate closely with Tata Steel engineers and researchers.
• Publish findings in peer-reviewed journals and present at international conferences.

JOB REQUIREMENTS

The ideal candidate:

• Holds a PhD degree in Mechanical Engineering, Chemical Engineering, Materials Science, Physics, or a related field.
• Has experience with Discrete Element Method in combination with AI tools relevant to the field
• Has developed advanced models for segregation in blast furnace context
• Excellent communication skills and a collaborative mindset.

• Combine and extend existing burden charging models developed in previous projects.
• Apply DEM simulations to study segregation, packing structure, and gas-solid contact in diverse burden mixtures.
• Investigate the impact of new materials on burden formation and blast furnace performance.
• Collaborate closely with Tata Steel engineers and researchers.
• Publish findings in peer-reviewed journals and present at international conferences