Atmospheric Sciences - Postdoctoral Researcher

Atmospheric Sciences - Postdoctoral Researcher

Entry Level | Full-time
Postdoctoral/Fellowship | Livermore, CA | 08/27/2026
Reference #: REF
8752I
Job Code: PDS.
1 Post-Dr Research Staff 1
Organization: Physical and Life Sciences
Position Type: Post Doctoral
Security Clearance: None/Position does not require US citizenship (assignments longer than 179 days require a federal background investigation)
Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana)
Medical Exam: Not applicable

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

We have an opening for an Atmospheric Science-Postdoctoral Researcher to study how land-use decisions influence dust emissions, water vapor fluxes, and surface ozone, with implications for water availability, photovoltaic generation, human health, and agriculture. The research will primarily focus on California's Central Valley.

The study will draw on a hierarchy of modeling approaches, including the ultra-high-resolution Energy Exascale Earth System Model (E3SM), the machine learning emulators ACE-ERA5 and ACE-E3SM, and the regional Energy Research and Forecasting (ERF) model. The work will entail analysis of a variety of regional Earth system data products, including observational and model products.

Under the guidance of senior scientists, you will contribute to research that evaluates how land-use decisions affect regional land-atmosphere interactions and related impacts.

This is a two-year Postdoctoral appointment with the possibility of extension to a maximum of three years.

This position is in the Atmospheric, Earth, and Energy Division which is part of the Physical and Life Sciences Directorate.

In this role, you will

• Conduct research to develop and evaluate short-term and long-term weather scenarios representing potential land-use impacts.
• Perform model simulations and analyze observational data and model output
• Diagnose and help characterize and reduce model biases using ground-based and satellite observations and machine learning
• Contribute to research planning, design, and execution related to land-atmosphere-water-human systems
• Pursue independent,complementary research interests that support the project objectives, and interact with a broad spectrum of scientists internally and externally to the Laboratory
• Collaborate with others in a multidisciplinary team environment to accomplish research goals
• Publish research results in peer-reviewed scientific or technical journals and present results at external conferences seminars and/or technical meetings
• Travel as required to coordinate research with collaborators
• Perform other duties as assigned

• PhD degree in Atmospheric Sciences or a related field.
• Experience and expertise in one or more of the following areas:
  Earth system models (ESMs), atmospheric chemistry and aerosols, machine learning for Earth system modeling, land surface processes
• Experience developing independent research projects, including publication of peer-reviewed literature.
• Proficiency in Python for analysis and visualization of Earth system data
• Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.
• Effective initiative and interpersonal skills and ability to work in a collaborative, multidisciplinary team environment.
• Experience with E3SM, ERF, or comparable global or regional Earth system models.
• Experience with machine-learning methods or emulators applied to weather, climate, or Earth system applications.
• Proficiency in at compiled modeling language such as C++ or Fortran.
• Familiarity with…