Opportunities

Postdoctoral Researchers

We are seeking postdoctoral associate to work in AI-assisted materials design and discovery for clean energy applications. Areas of interest include 1) development of foundational machine learning models for atomistic simulation, 2) AI-enhanced x-ray absorption spectroscopy, and 3) uncertainty methods for AI, to support materials development in fusion, advanced fission, and water treatment.

Roles and Responsibilities

• Perform density functional theory and ab initio molecular dynamics simulations to study chemical properties, structure-property relationships, defect properties, and reactive interfaces
• Develop machine learning interatomic models for atomistic simulation and enhanced spectroscopic (X-ray Absorption Spectroscopy) analysis
• Manage collaborations with U.S. universities and national laboratories
• Speaking at national and international conferences
• Mentoring MS and PhD students

Preferred Qualifications

• A PhD in related area (e.g., Materials Science, Physics, Chemical Engineering, Mechanical Engineering, Nuclear Engineering, Electrical Engineering, etc.)
• Experience and background in one or more of the following: machine learning, ab initio density functional theory simulation, molecular dynamics, x-ray absorption spectroscopy, molten salt chemistry, semiconductor physics, electrochemical destruction of PFAS.

PhD Students

We are seeking motivated students that are interested in doing research in advanced energy/nuclear materials. Candidates should have a background in chemical engineering, chemistry, physics, materials science, computational science and engineering, or another related engineering field. Experience in molecular dynamics, density functional theory, and/or machine learning is a plus, but not a requirement. We look for individuals that are highly motivated, creative and have potential to do high impact research given the training and opportunity.

To Apply:

Contact Dr. Stephen Lam at stephen_lam@uml.edu with resume/CV, latest academic transcript and a brief statement of interest, and contact information for three references (you will be notified before references are contacted).

The Lam Research Group is an interdisciplinary and highly collaborative research group with active projects that combine predictive simulation, data analytics and informed experiments to accelerate the development of materials in nuclear and other energy applications. Candidates will have opportunities to work with collaborators from other departments, universities and national laboratories across the U.S. For more information on the group, please visit our research page.