Lawrence Livermore National Laboratory



Postdoctoral Researcher - Geophysical Subsurface Imaging

Location: Livermore, CA
Category: Post Docs
Organization: Physical and Life Sciences
Posting Requirement: External Posting
Job ID: 102419
Job Code: Post-Dr Research Staff 1 (PDS.1)
Date Posted: June 21 2017

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Science and Technology on a Mission!
For more than 60 years, the Lawrence Livermore National Laboratory (LLNL) has applied science and technology to make the world a safer place.

We have an opening for a postdoctoral researcher to perform original and independent research in support of a project to improve subsurface fluid characterization in complex porous media coupling seismic and electromagnetic phenomena. You will perform algorithmic development, programming, computational modeling, and data analysis and have access to LLNL's extensive high-performance computing and laboratory facilities. This position is in the Computational Geosciences Group in the Atmospheric, Earth and Energy Division.
 
Essential Duties
- Conduct simulations of seismic and/or EM wave propagation, and signal processing.
- Conduct research to develop and simulate seismic & EM wave propagation in three-dimensional subsurface models using spectral finite element method.
- Conduct research using forward and inverse calculation in complex earth models for structure investigations.
- Conduct analyses of seismic and EM datasets, and simulation results.
- Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
- Publish both technical reports and peer-reviewed publications summarizing research findings, and present results at technical meetings and national conferences.
- Perform other duties as assigned.
 
Qualifications
- Recent PhD in geophysics, seismology, physics, applied mathematics, or a closely related field.
- Proficient knowledge in quantitative wave propagation phenomena and signal processing.
- Proficient knowledge and experience in geophysical methods for characterizing the subsurface structure.
- Experience developing and implementing computational strategies, with exceptional ability and knowledge in forward and inverse geophysical modeling.
- Experience collecting, processing and analyzing local/regional geophysical datasets.
- Experience in high-performance computing and parallel programming.
- Knowledge of modern computer systems, computational tools, languages (including FORTRAN, C/C++, PYTHON).  
- Proficient verbal and written communication and interpersonal skills to collaborate effectively in a multidisciplinary team environment and present and explain technical information.
 
Desired Qualifications
- Knowledge of (spectral) finite element codes.
- Experience with algorithmic development for geophysical problems.
- Familiarity with Unix-like operating systems, including software development on such platforms.

Pre-Employment Drug Test:  External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test.
 

Anticipated Clearance Level:  None.

Note:   This is a two-year Postdoctoral appointment with the possibility of extension to a maximum of three 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 $1.8 billion, employing approximately 6,500 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.

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