Machine Learning for Shock Hydrodynamics - Postdoctoral Researcher

Key Skills

Design, Effective communication skills, Machine learning techniques, Presentation skills

Job Description

We have an opening for a Postdoctoral Researcher with a research track-record in physical sciences with interest in career growth in optimization, machine learning, automatic differentiation, and computational inverse problems. The position combines 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. You will actively participate in research 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. This position is in the Material Dynamics and Kinetics group within the Energetic Materials & Design (EMD) section of the Materials Science Division, supporting the Energetic Materials Center (EMC).

This position requires full-time on-site presence due to the nature of the work.

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, turbulence, 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

• PhD in Chemistry, Materials Science, Engineering, Mathematics, Physics or a related field.
• Experience in one or more of the following 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.
• Experience as an innovative computational scientist with experience in dynamic materials phenomena or optimization techniques, and documented track record of success.
• 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 effective presentations at seminars, meetings and/or teaching lectures.
• Initiative and interpersonal skills with desire and ability to work in a collaborative environment.

Qualifications We Desire

• Experience working with or implementing world-class computational physics and hydrodynamic codes.
• Knowledge in fluid dynamics and condensed matter physics.
• Established record of conceiving and executing pioneering multidisciplinary projects.

Additional Information

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.

Why Lawrence Livermore National Laboratory?

• Included in 2024 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Inclusion, Diversity, Equity and Accountability (IDEA) - visit https://www.llnl.gov/diversity
• Our core beliefs - visit https://www.llnl.gov/diversity/our-values
• Employee engagement - visit https://www.llnl.gov/diversity/employee-engagement

Security Clearance

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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