Advanced Computational Methods and Machine Learning - Postdoctoral Researcher
Organisation Name: LLNL
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Company Description
Join us and make YOUR mark on the World!
Are you interested in joining some of the brightest talent in the world to strengthen the United States security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.
We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people talents ideas experiences and perspectives. This is important for continued success of the Laboratorys mission.
Pay Range
$108840 Annually
Job Description
We have multiple openings for Postdoctoral Researchers with outstanding research track-records in physical sciences with interest in career growth in optimization machine learning automatic differentiation and computational inverse problems. Knowledge in any of the following areas would also be valuable: high-pressure and high strain rate physics the physics of energetic materials atomistic materials modeling transport properties of materials multi-scale modeling or hydrodynamic simulations.
The positions are envisioned to combine physics and optimization experience to promote scientific and programmatic growth within the strengths of the group. Specific investigations include combining complex hydrodynamics models with computational approaches to facilitate large-scale investigations and machine learning-based design optimization. Specifically the candidates will actively participate in exciting research within the group that includes Richtmyer-Meshkov and other instabilities; model development describing fundamental dynamic processes; and multi-scale and continuum computational investigations of the effect of such processes on bulk material behavior. Uniquely the group also has strongly coupled experimental and theoretical efforts in these mentioned areas. These positions are in the Material Dynamics and Kinetics group in the Materials Science Division.
You will
Develop world-leading ML and optimization techniques to study problems in physics.
Conduct research to understand the fundamental phenomena that affect or control dynamic materials properties including material instabilities plasticity/strength porosity and phase transformations kinetics.
Contribute to the conception design and execution of research to address defined problems.
Engage in scientific and programmatic connections with Laboratory-wide efforts and customers through the promotion of research advancements that tackle Laboratory missions.
Develop understanding of customer needs in order to contribute to development and sustenance of funding support for new and existing research both within and outside of LLNL.
Maintain and establish laboratory protocols.
Document research; publish papers in peer-reviewed journals and present results within the DOE community and at conferences.
Perform other duties as assigned.
Qualifications
This position requires either no security clearance or a Department of Energy (DOE) L-level or Q-level clearance depending on the particular assignment.
PhD in Chemistry Materials Science Engineering Mathematics Physics or a related field.
Experience in one or more of the following areas areas: Computational multiscale modeling energetic materials molecular dynamics multi-physics hydrodynamics non-equilibrium statistical physics highly dynamic high-pressure physics optimization machine learning or computational inverse problems.
Proven track record as an innovative computational scientist with experience in dynamic materials phenomena or optimization techniques.
Ability to represent and document research through programmatic and scientific presentations and publications or technical reports of results.
Proficient verbal and written communication skills as reflected in effectivepresentations at seminars meetings and/or teaching lectures.
Initiative and interpersonal skills with desire and ability to work in a collaborative
Qualifications We Desire
Experience working with or implementing world-class computational physics and hydrodynamic codes.
Knowledge in fluid dynamics and condensed matter physics.
An established record of conceiving and executing pioneering multidisciplinary projects.
Additional Information
All your information will be kept confidential according to EEO guidelines.
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.
None required.However if your assignment is longer than 179 days cumulatively within a calendar year you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check. (This process does not apply to foreign nationals.)
Pre-Employment Drug Test
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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