Lawrence Livermore National Laboratory



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Faculty Research Staff Member

Location:  Livermore, CA
Category:  Students & Faculty
Job ID: 104238
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 faculty member with expertise in first-principles and classical atomistic simulation techniques; statistical sampling, data science, and mathematical optimization methods; and phase transitions in complex materials to conduct independent research in the area of crystal structure prediction in high-entropy materials. You will actively participate in the development of computational models and codes for predicting structural properties of dynamically disordered crystals in energetic materials and in complex hydrides for hydrogen storage. This position is in the Quantum Simulations Group within the Materials Science Division.
 
Essential Duties
- Conduct fundamental and applied research in the crystal structure prediction of high-entropy materials.   
- Develop modeling and simulation capabilities that integrate direct simulation and data science techniques to discover key structural motifs in partially disordered systems at elevated temperatures.
- Design and perform systematic computer simulations on LLNL supercomputers for establishing the foundational understanding of formation of crystal structures in these materials.
- Develop techniques for computing thermally renormalized phonon spectra from molecular dynamics simulations.
- Pursue independent but complementary research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
- Collaborate with scientists in multidisciplinary team environment, including multiscale modeling experts.
- Document research; publish papers in peer-reviewed journals, and present results within the DOE community and at conferences.
- Perform other duties as assigned.
 
Qualifications
- PhD and postdoctoral experience in materials science, chemical engineering, mechanical engineering, physics, applied math, or a related field or the equivalent combination of education and related experience.
- Must be a continuing faculty or teacher affiliated at an accredited institution with a research record on topics relevant to this listing.
- Proven solid background in structural predictions in materials based on first-principles and/or classical atomistic simulation methods.
- Advanced experience with mathematical and data-science methods for optimizing complex systems.
- Ability to independently develop research projects, solve problems, and work effectively in a collaborative, multidisciplinary team research environment.
- Demonstrated publication record in conference proceedings and peer-reviewed journals.
- Advanced verbal and written communication skills as reflected in effective presentations at seminars and meetings.
 
Desired Qualifications
- Experience with FORTRAN, C/C++, and/or parallel computing.
 

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

Security Clearance:  None required.

 

Note:   This is a Temporary Faculty Scholar appointment with the possibility of extension.  This assignment is typically a full-time position during the summer academic break.

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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