Argonne National Laboratory-posted about 1 month ago
$70,758 - $117,925/Yr
Full-time • Entry Level
Lemont, IL
1,001-5,000 employees
Professional, Scientific, and Technical Services

The Theory and Modeling Group at the Center for Nanoscale Materials (CNM), Argonne National Laboratory (near Chicago, Illinois), invites applications for a postdoctoral appointment focused on theory and simulation of the electronic structure of polycrystalline and defective two-dimensional materials. Interviews will begin immediately and continue until the position is filled. This position centers on developing machine-learning surrogates for electronic structure and electrostatic potential and using these models to predict structural and electronic evolution under applied bias. Methods may include density functional theory (DFT)-based approaches, coupled with effective continuum and/or tight-binding models derived from first-principles calculations. The project is part of a large, multi-institution collaboration (~30 researchers) spanning Argonne National Laboratory, Oak Ridge National Laboratory, Northwestern University, and Lawrence Berkeley National Laboratory.

  • Develop and validate ML surrogate models for electronic structure and electrostatic potential in 2D materials
  • Perform large-scale materials simulations (e.g., DFT, tight-binding, continuum models) to generate training and validation datasets
  • Integrate surrogate models into workflows to predict bias-driven structural and electronic evolution
  • Design and execute high-throughput calculations; build and manage curated materials databases
  • Collaborate closely with experimental teams to inform model development and interpret results
  • Contribute to software development, documentation, and reproducible workflows
  • Disseminate findings through publications, presentations, and collaborative reports
  • Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of physics, chemistry, materials science, electrical engineering, or a related field
  • Demonstrated expertise in electronic structure theory
  • Experience with large-scale materials simulations
  • Experience developing and applying machine-learning surrogates for atomistic simulations
  • Excellent verbal and written communication skills
  • Strong collaborative skills and the ability to work effectively across divisions, laboratories, universities, and industry
  • Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork
  • Hands-on experience with two-dimensional materials modeling
  • Proficiency in database development and management for computational materials data
  • Strong programming skills and experience with software development best practices
  • Experience with high-throughput calculations and workflow automation
  • Familiarity with inverse design approaches
  • comprehensive benefits are part of the total rewards package
  • Click here to view Argonne employee benefits!
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