At TU Delft, you will contribute to a transformative research initiative focused on sustainable steel production. This project addresses a critical and growing challenge in metallurgy, which is liquid copper infiltration (LCI) in copper-contaminated steels leading to cracking during steel processing. While LCI is a known issue in conventional steel recycling, it becomes especially critical in the context of green steel production, where increased reliance on recycled scrap and electric arc furnace (EAF)-based routes promotes copper accumulation in steel, creating conditions that favor subsequent copper-induced embrittlement.

About the Company

TU Delft is a prestigious university known for its commitment to impactful research and education in engineering and technology. With a focus on sustainability and innovation, TU Delft trains engineers who contribute to solutions for today's challenges.

The Role

As a postdoctoral researcher, you will unravel the atomic-scale mechanisms of LCI and the inhibitory role of silicon in steel. You will perform molecular dynamics (MD) simulations to gain insights into copper segregation, wetting, and embrittlement at grain boundaries in steels. Your work will involve developing a Density Functional Theory (DFT)-accurate machine-learned interatomic potential (MLIP) to facilitate predictive MD simulations.

Responsibilities

• Conduct molecular dynamics (MD) simulations to explore atomic-scale insights into copper segregation and embrittlement at steel grain boundaries.
• Develop a DFT-accurate machine-learned interatomic potential (MLIP) for predictive MD simulations.
• Investigate how silicon suppresses LCI, focusing on grain boundary site competition and copper-silicon intermetallic phase formation.
• Collaborate with researchers and industry partners to connect modeling insights with process development and alloy design.
• Contribute to scientific publications, conference presentations, and new research proposals in sustainable steelmaking.

Requirements

• PhD in Materials Science, Engineering, Physics, Chemistry, or a related field.
• Expertise in atomistic and molecular simulation techniques (density functional theory, molecular dynamics, ab initio molecular dynamics).
• Experience in developing machine learning interatomic potentials.
• Strong research track record with publications in peer-reviewed journals.
• Excellent written and verbal communication skills in English.

What We Offer

• A temporary contract for 3 years.
• A full-time position (36-40 hours per week).
• Salary and benefits according to the Collective Labour Agreement for Dutch Universities.
• Excellent pension scheme and flexible working arrangements.
• Opportunities for professional development and training.
• Support for relocation and a Dual Career Programme for partners.

Join this unique program at TU Delft, where you can apply your technical knowledge to collaborate with leading European research institutes and steel industries. Help enable the safe use of recycled scrap in green steel production and contribute to a more sustainable future.