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You Will Do: Design & advance digital twins: Integrate electronic structure (e.g., DFT, ab initio MD, tight‑binding) with multiscale simulations to predict experimental observables at interfaces. Bridge
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& advance digital twins: Integrate electronic structure (e.g., DFT, ab initio MD, tight-binding) with multiscale simulations to predict experimental observables at interfaces. Bridge theory & experiment: Co
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will work at the interface of first-principles theory (e.g., DFT) and reactive force field modeling (e.g., ReaxFF), developing multiscale, high-throughput workflows that simulate and optimize growth
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, Physics, Computer Science, or a related field. Hands-on experience with computational materials methods (e.g., DFT, molecular dynamics, machine learning force field simulations). Proficiency in Python
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experience in theoretical and/or computational research in condensed matter physics, nanoscience, optics, statistical physics or thermodynamics, chemical physics, as well as in molecular dynamics simulations
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in the Department of Materials Science and Engineering at the National University of Singapore under the direction of Dr. Peichen Zhong. This role involves using DFT, molecular dynamics, and machine
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the Department of Materials Science and Engineering at National University of Singapore under the direction of Dr. Jing Yan and Dr. Peichen Zhong. This role involves using computational methods, including DFT