The Group of Condensed Matter and Complex Systems in the Theoretical Division of Los Alamos National Laboratory (LANL) has an immediate opening of postdoctoral position in the area of computational materials physics. The postdoc will focus on applying first-principles DFT and high-throughput approaches in combination with machine learning techniques for discovering novel f-electron materials with boosted Kondo temperatures. The work will be a combination of developing computational workflows and applying a newly developed high throughput DFT framework with existing all electron DFT codes. Successful applicants will join a highly collaborative project aimed to establish a new route to enhancing the energy scale of quantum coherence in high-purity f-electron quantum materials and be a part of a dynamic team of condensed matter theory and experiment scientists at Los Alamos National Laboratory.

A successful candidate must demonstrate strong skills in computational materials theory with an excellent scientific record of publications. Expertise in first-principles density functional theory simulations is required while a knowledge of machine learning is highly desired. The ability to work creatively as a part of a diverse team and independently is important. Strong written and oral communication skills are essential.

Review of applications will begin immediately and will continue until the position is filled. Interested candidates are encouraged to apply online through the link https://lanl.jobs using the job identification number IRC125593, where detailed information and requirements on the postdoctoral position are available. Further inquiries can be addressed to Dr. Christopher Lane (email: [email protected]), Dr. Ying-Wai Li (email: [email protected]), or Jian-Xin Zhu (email: [email protected]).