Lawrence Livermore National Laboratory

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Postdoctoral Research Staff Member

Location:  Livermore, CA
Category:  Post Docs
Job ID: 102765
Job Code: 
Date Posted: 

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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 research in multilevel approaches and numerical upscaling of broad classes of PDEs, utilizing high-performance computing. The approach is based on finite element algebraic multigrid coarsening with guaranteed approximation properties. You will support ongoing projects by developing algorithms and software, to solve extremely large problems that may not be computationally feasible without dimension reduction.  This position is in the Center for Applied Scientific Computing (CASC) within the Computation Directorate.

Essential Duties
- Research and develop methods for constructing highly accurate coarse (upscaled) finite element discretization schemes based on specialized algebraic multigrid techniques utilizing high-performance computing.
- Develop software utilizing high-performance computing to evaluate novel techniques in the above area.
- Develop prototype software utilizing high-performance computing to evaluate novel uncertainty quantification (UQ).
- Pursue independent (but complementary) research interests and being able to interact with team members internally and externally.
- Publish research results in external peer-reviewed scientific journals and participate in conferences and workshops.
- Present formal and informal overview of research progress at group meetings.
- Participate in existing division collaborations and alliances with academia and industry.
- Perform other duties as assigned.

- Recent PhD in Computer Science, Mathematics, or related field.
- Research experience in numerical PDEs, finite elements and multigrid, and/or distributed and multithreaded computing.
- Ability to conduct high quality research and to develop implementations of sophisticated algorithms to evaluate the results.
- Experience programming in C and/or C++.
- Proficient verbal and written communication skills necessary to interact with members of a research team, author technical and scientific reports and papers, and deliver technical presentations.
- Demonstrated publication record in peer-reviewed journals and/or conferences.
- Strong decision-making skills necessary to independently solve complex research problems.

Desired Qualifications
- Experience in element based or aggregation based algebraic multigrid and/or Monte Carlo and MCMC simulations.
- Experience implementing algorithms for distributed computers or multi-core CPUs or GPUs.
- Experience in parallel mesh and graph partitioners.

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 one 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 $1.5 billion, employing approximately 6,000 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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