Lawrence Livermore National Laboratory

Machine Learning for Reservoir Characterization and Modeling - Postdoctoral Researcher

Location:  Livermore, CA
Category:  Post Docs
Organization:  Physical and Life Sciences
Posting Requirement:  External Posting
Job ID: 106397
Job Code: Post-Dr Research Staff 1 (PDS.1)
Date Posted: November 19 2019

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Join us and make YOUR mark on the World!

Come join Lawrence Livermore National Laboratory (LLNL) where we apply science and technology to make the world a safer place; now one of 2019 Best Places to Work by Glassdoor!

We have openings for multiple postdoctoral researchers to perform original and independent research on machine learning (ML) methods for geologic carbon storage applications. Depending on the candidates’ domain expertise, these positions will be in the Computational Geosciences Group or the Subsurface Transport Group in the Atmospheric, Earth and Energy Division.

Essential Duties
- Conduct research that applies machine learning and data analytics to reservoir characterization and reservoir process forecasting for geologic carbon storage systems.
- Conduct original and independent research on geomechanics, multiphase flow in porous and fractured media, and geophysics using high performance computing codes.
- Analyze and interpret data from geophysical monitoring, laboratory/field experiments, and physics-based simulations.
- Design, implement, and analyze machine learning techniques.
- Publish technical reports and peer-reviewed publications summarizing research findings.
- Present results at review meetings and scientific conferences.
- Perform other duties as assigned.

- Recent PhD in Civil and Environmental Engineering, Energy Systems Engineering, Petroleum Engineering, Geophysics, Earth Sciences, or related fields.
- Research creativity, exceptional ability, and expert knowledge in the applicant’s area of specialization.
- Knowledge of multiphase flow, geomechanics and/or geophysics.
- Knowledge of numerical methods, including discretization and solution techniques.
- Experience producing reports and publications.
- Proficient written and verbal communication skills necessary to collaborate effectively in a multidisciplinary team environment.
Desired Qualifications
- Expertise in artificial intelligence, machine learning, data analytics, and/or uncertainty quantification.
- Experience with geologic carbon storage.
- Experience with code development for high-performance computing platforms.

Pre-Employment Drug Test:  External applicant(s) selected for this position will be required to 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.

Security Clearance:  None required.


Note:   This is a 2 year Postdoctoral appointment with the possibility of extension to a maximum of 3 years.  Eligible candidates are recent PhDs within five years of the month of the degree award at time of hire date.

About Us

Lawrence Livermore National Laboratory (LLNL), located in the San Francisco Bay Area (East Bay), is a premier applied science laboratory that is part of the National Nuclear Security Administration (NNSA) within the Department of Energy (DOE).  LLNL's mission is strengthening national security by developing and applying cutting-edge science, technology, and engineering that respond with vision, quality, integrity, and technical excellence to scientific issues of national importance.  The Laboratory has a current annual budget of about $2.3 billion, employing approximately 6,900 employees.


LLNL is an affirmative action/ equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, protected veteran status, age, citizenship, or any other characteristic protected by law.