Los Alamos National Laboratory

What You Will Do

Are you ready to begin a career building AI surrogate models of computational physics codes? If so, we encourage you to learn more about our Postdoctoral Research Associate openings in the Computational Physics: Verification & Analysis group (XCP-8) at the Los Alamos National Laboratory (LANL). We are looking for several highly motivated post-doctoral candidates with experience with the computational solid/fluid dynamics, deep learning, and/or analysis of computational predictions. In this role you will apply state of the art generative deep learning methods to build large AI surrogate models of computational physics simulations of materials under extreme conditions. You will be one member of a team that designs, builds, trains, and tests a large AI model. Experience with continuum mechanics (e.g. hydrodynamics, fluid dynamics, shock physics, turbulence, solid mechanics, material strength, material failure) and/or experience with applied mathematics, statistics, and/or deep learning are desired. You will have the opportunity to publish results in peer-reviewed journals and present at top machine learning conferences.

XCP-8 is an interdisciplinary group which specializes in VVUQ and analysis of complex numerical codes applying diverse physics models (fluid dynamics, hydrodynamics, solid mechanics, material strength and damage, equation of state, reactive flow, high-energy-density physics, instabilities and turbulence, and radiation transport). AI/ML methods are applied by XCP-8 in a highly interdisciplinary manner and group members interact closely with code and physics model developers, experimentalists, and simulation end-users across a broad set of physics. XCP-8 offers an exciting, flexible, scientifically challenging work environment with many opportunities to collaborate with the broader LANL scientific community.

Learn more about XCP-8 at https://content.lanl.gov:8058/orgs/xcp/xcp-8/

What You Need

Minimum Job Requirements:

• Numerical Methods
• Familiarity with the fundamentals of deep learning and computational physics simulations.
• Research Expertise
• You will need to have conducted research in one or more of the following areas: deep learning, computational physics simulation (especially fluid, solid, or multiphase mechanics), verification, validation, uncertainty quantification, optimization, or a closely related focus area.
• Programming
• For this role you will need to be familiar with Python, Pytorch or Tensorflow.
• Journals/Conferences
• You will need to show that you have the ability to publish research in peer-reviewed journals or conference proceedings, communicate research to an interdisciplinary audience and work on an interdisciplinary team.

Education/Experience: PhD in applied mathematics, computer science, physics, materials science, chemistry, engineering, statistics, a closely related STEM discipline, or have PhD thesis work involving deep learning and computational physics simulations. The candidate must be within 5 years of completion of PhD at time of being proposed for review by the committee, or will have completed all PhD requirements by commencement of the appointment.

Desired Qualifications:

• Expertise with one or more of the components (numerical methods, verification, validation, uncertainty quantification) of computational physics model.
• Understanding of various continuum mechanical processes such as equation-of-state modeling, shock physics, high explosive modeling, material failure, material strength under high strain rates, turbulence, and/or materials properties in simulations.
• Expertise using High Performance Computing clusters, including GPUs.
• Expertise with generative deep learning models, computer vision, and/or vision transformers.
• Publications in high impact journals in one or more of the following areas: generative deep learning, physics simulations, verification, validation, uncertainty quantification, optimization, or a closely related focus area.
• Experience coding in a team. Proficient with software engineering tools such as: Git; web-based software repository systems; issue trackers; online collaboration platforms; deep learning APIs; and continuous integration systems.

Work Location: The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.

Salary: Competitive salaries are based on the date the PhD degree requirements were completed or the degree was awarded. Starting salary for a new graduate is currently $94,500. For more information go to Postdoc Program website at https://www.lanl.gov/careers/career-options/postdoctoral-research/index.php .

Note to Applicants:

To be considered for the position, applicants should submit a CV/resume and a detailed cover letter addressing how their experience relates to each of the required and desired skills as applicable. Regular post-doctoral appointments are for two years and are renewable for a third year. Outstanding candidates may be eligible for a LANL Director's Fellowship. For specific inquiries regarding the position, please contact Dr. Bryan Kaiser (bkaiser@lanl.gov). We will begin reviewing applications on Monday January 27.

Due to federal restrictions contained in the current National Defense Authorization Act, citizens of the People's Republic of China, the Islamic Republic of Iran, the Democratic People's Republic of North Korea, and the Russian Federation, who are not Lawful Permanent Residents ("green card" holders) are prohibited from accessing facilities that support the mission, functions, and operations of national security laboratories and nuclear weapons production facilities, which includes Los Alamos National Laboratory.

Where You Will Work

Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our generous benefits package includes:

• PPO or High Deductible medical insurance with the same large nationwide network
• Dental and vision insurance
• Free basic life and disability insurance
• Paid maternity and parental leave
• Award-winning 401(k) (6% matching plus 3.5% annually)
• Learning opportunities and tuition assistance
• Flexible schedules and time off (paid sick, vacation, and holidays)
• Onsite gyms and wellness programs
• Extensive relocation packages (outside a 50 mile radius)

Additional Details

Directive 206.2: Employment with Triad requires a favorable decision by NNSA indicating employee is suitable under NNSA Supplemental Directive 206.2. Please note that this requirement applies only to citizens of the United States.

Clearance: Q (Position may be cleared to this level). Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements* for access to classified matter. This position requires a Q clearance which requires US Citizenship except in extremely rare circumstances. Dependent upon position, additional authorization to access nuclear weapons information may be required that may or may not be available to dual citizens depending upon the circumstances.

• Eligibility requirements: To obtain a clearance, an individual must be at least 18 years of age; U.S. citizenship is required except in very limited circumstances. See DOE Order 472.2 for additional information.

New-Employment Drug Test: The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer.

Equal Opportunity: Los Alamos National Laboratory is an equal opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by applicable federal, state and local laws and regulations.The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request a disability accommodation, email applyhelp@lanl.gov or call (505) 664-6947, opt. 3.

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