Research Fellow – Atomic Catalysts & Machine Learning

About the role

Join the School of Physical and Mathematical Sciences at Nanyang Technological University, Singapore, as a Research Fellow in the laboratory of Prof. Fan Hongjin. You will work on a data‑driven project aimed at discovering atomic catalysts for renewable energy applications.

Key responsibilities

• Theoretical predictions using Density Functional Theory (DFT) and machine‑learning models, and mechanistic understanding of atomic catalysts.
• Investigation of mechanisms via in‑situ and operando techniques combined with theoretical calculations.
• Coordinate collaborations, support related experiments, and maintain lab infrastructure including battery‑fabrication and characterization equipment.
• Prepare regular progress reports, annual and final project reports, and draft proposals for external funding.

Required profile

• PhD in material sciences or applied physics with a focus on renewable energy.
• Demonstrated experience in DFT and machine‑learning applications to atomic catalysts.
• Strong publication record in renewable‑energy materials, especially electrocatalysis.
• Motivation to tackle multidisciplinary grand challenges and ability to work in a dynamic team.

Required skills

• Density Functional Theory (DFT)
• Machine Learning