Machine Learning Postdoc Jobs in Sunnyvale, CA (NOW HIRING)

Company Description
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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.
Job Description
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 evaluateshort-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 reducemodel 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,complementaryresearch 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

Qualifications

• 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.

Qualifications we desire

• 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 land-use, water, energy, air-quality, agricultural, or human-system applications of Earth system research.
• Experience engaging with research collaborators, stakeholders, or practitioners to support actionable science.

Pay Range
$123,048 Annually
This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.
Additional Information
#LI-Hybrid
Position Information
This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.
Why Lawrence Livermore National Laboratory?

• Included in 2026 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Our values - visit https://www.llnl.gov/inclusion/our-values

Security Clearance
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External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
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