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Berkeley Education Alliance for Research in Singapore Limited seeks a Senior Postdoctoral Scholar to build a computational pipeline for CO2 electrocatalytic reduction catalysts. The role spans DFT analyses, ML potentials, and AI-driven materials discovery, integrated with experimental workflows.
You will collaborate with international partners across universities, national labs, and industry to advance next-generation catalysts and sustainable energy systems, contributing to cross-disciplinary
As a Senior Postdoctoral Scholar, you are expected to establish a computational pipeline to achieve catalyst prediction for CO2electrocatalytic reduction reactions.
This is a multi-step approach, where first DFT will be used to understand reactions, then explore the use of machine learning potentials towards kinetic and large length scale/timescale simulations and AI to explore Materials Discovery of new catalysis. These computational efforts will eventually be integrate into the experimental workflow.
This position requires close collaboration with experimental and computational researchers across an international network of partner universities, national laboratories, and industry collaborators. The Computational Scientist will contribute the development of next-generation catalysts and processes for carbon utilization, and conversion providing computational support for international partners.
You will work in a highly collaborative environment as part of the AxCIS team in Singapore, addressing challenges at the interface of materials chemistry, high-throughput synthesis, artificial intelligence, and robotic automation.