Research Fellow - Atomic Catalysts and Machine Learning

About the role

The School of Physical and Mathematical Sciences (SPMS) at Nanyang Technological University, Singapore, is looking for a Research Fellow to join the laboratory of Fan Hongjin. The project focuses on the data-driven discovery of atomic catalysts, combining theory, experimental investigation and project coordination.

Key responsibilities

• Make theoretical predictions using density functional theory (DFT) and machine learning, and build a mechanistic understanding of atomic catalysts.
• Investigate mechanisms using in-situ and/or operando techniques together with theoretical calculations.
• Coordinate collaboration with other researchers in the project and support the research group on related experiments.
• Support project management and lab infrastructure, including procurement, setting up a battery fabrication line, setting up equipment for in-situ and/or operando characterisation, and preparing annual and final project reports.
• Write regular progress reports to the principal investigator (PI).
• Write one proposal based on the project's results for an external grant.

Required profile

• PhD in material sciences or applied physics, with a focus on renewable energy.
• Evidenced experience in DFT and machine learning, especially their application to atomic catalysts.
• Strong publication record on renewable energy materials, especially electrocatalysis.
• Entry-level candidates are welcome to apply.
• Strong motivation to tackle grand challenges in multidisciplinary subjects.
• Team player able to support others in a dynamic, interdisciplinary environment.