Location: Los Alamos, NM
Cap-Exempt H-1B Position — No lottery required
**What You Will Do** The Physics and Chemistry of Materials group (T-1) at Los Alamos National Laboratory seeks a highly motivated Postdoctoral Researcher to develop and apply advanced electronic structure, atomistic simulation, and AI/ML methodologies for understanding and controlling rare-earth element (REE) chemistry. The successful candidate will work at the intersection of quantum chemistry, machine learning, and reactive molecular simulations to investigate REE coordination, separation, and interfacial processes, while developing predictive computational tools that bridge atomistic mechanisms and experimentally observable properties. This position offers exceptional opportunities for cross-disciplinary collaboration, scientific workshop organization, and conference attendance. **What You Need** **Minimum Job Requirements:** **Education/Experience:** Ph.D. in Chemistry, Physics, Materials Science, Chemical Engineering, or a related field completed within the last five years. - Experience with first-principles electronic structure methods, including DFT and/or TD-DFT. - Experience performing atomistic simulations of molecular and/or condensed-phase systems. - Experience with machine learning, data science, uncertainty quantification, or surrogate modeling for chemical systems. - Demonstrated ability to work creatively and independently as well as learn and collaborate with experts as a part of a multi-disciplinary team. - Excellent communication and writing skills, as evidenced by publications, cover letter and interview. **Desired Qualifications:** In addition to the minimum requirements, the following qualifications are desired, and preference will be given to candidates satisfying (at least one) of them: - Experience in separations science, coordination chemistry, and materials discovery. - Familiarity with molecular dynamics simulations, reactive chemistry, and automated reaction discovery. - Experience with advanced electronic structure methods such as CASS