Postdoctoral Research Associate in AI-Accelerated Molecular and Materials Modeling

About the role

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.

Responsibilities

• Develop and apply advanced electronic structure methods, including DFT and/or TD-DFT.
• Perform atomistic simulations of molecular and/or condensed-phase systems.
• Work at the intersection of quantum chemistry, machine learning, and reactive molecular simulations to investigate REE coordination, separation, and interfacial processes.
• Develop predictive computational tools that bridge atomistic mechanisms and experimentally observable properties.
• Collaborate with experts from various disciplines to advance the field of REE chemistry.
• Organize scientific workshops and attend conferences to disseminate findings and foster interdisciplinary collaboration.

Requirements

• 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.

Qualifications

• In addition to the minimum requirements, the following qualifications are desired:
• 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 CASSCF, GW/BSE, relativistic methods, or spin-orbit coupling treatments.
• Knowledge of spectroscopy simulations, including X-ray, UV-Vis, Raman, or IR spectroscopy.
• Experience developing or applying machine-learning interatomic potentials, reactive neural network potentials, or active-learning workflows.
• Experience using high-performance computing platforms and large-scale scientific modeling.
• Experience with model verification, validation, and uncertainty quantification, integration of simulation and experimental observations, and management of scientific datasets.
• Experience in computer programming using modern computing languages. Programming skills in Python and/or scientific computing environments.
• Demonstrated ability to work independently and with minimum supervision.
• Willingness to work productively on multiple projects.

Benefits

• PPO or High Deductible medical insurance with the same large nationwide network.
• Dental and vision insurance.
• Free basic life and disability insurance.
• Paid childbirth and parental leave.
• Award-winning 401(k) (6% matching plus 3.5% annually).
• Learning opportunities and tuition assistance.
• Flexible schedules and time off (PTO and holidays).
• Onsite gyms and wellness programs.
• Extensive relocation packages (outside a 50 mile radius).

Pay

Details on pay are not specified in the job posting.

Schedule

Details on schedule are not specified in the job posting.