What You Will Do

　　We are looking for candidates to join our team in Los Alamos National Laboratory's Theoretical Division (T-Division). T-Division provides a unique and engaging environment that fosters multi-disciplinary collaborations to support the laboratory's strategic basic research and national security missions. The Applied Mathematics and Plasma Physics (T-5) group within T-Division conducts research across a wide variety of topics including fusion science, space plasma, numerical analysis, computational imaging, optimization, and the modeling of critical infrastructure (gas pipelines and electrical grids). These application areas are tied together by research in novel algorithms, numerical methods, artificial intelligence, and machine learning.

　　T-5 is seeking one or more postdoctoral researchers to participate in the development of algorithms to solve hydrodynamic inversion problems using sparse tomographic measurements and other physics constraints. These inversion problems lie at the intersection of computational physics, applied math, and machine learning. Candidates with experience with PDE-based machine learning algorithms and generative neural networks are particularly encouraged to apply. Applications include both hydrodynamics as well as inertial confinement fusion.

　　Successful applicants are expected to work in an interdisciplinary, collaborative research environment. This includes publishing in peer reviewed journals and presenting research at conferences and workshops. This is a 2-year postdoctoral position with the potential for a third-year renewal.

　　What You Need

　　Minimum Job Requirements:

　　Demonstrated expertise in computational and/or mathematical physics with a focus on at least one of the following areas:

　　Data driven algorithms in one or more of the following: inertial confinement fusion, plasma kinetics, continuum mechanics, constitutive modeling, and/or materials science

　　Reduced order modeling

　　Multi-fidelity surrogate modeling

　　PDE-constrained optimization and parameter estimation

　　Demonstrated ability to work effectively in a collaborative and multi-disciplinary scientific environment

　　A record of publications and presentations in one or more of the following areas: applied mathematics, computational physics, theoretical mechanics, computational fluid dynamics, plasma physics, or fusion science

　　Education : A Ph.D. in physics, applied mathematics, engineering, or related field

　　Desired Qualifications:

　　Experience in utilizing the underlying physical phenomena in the development and application machine learning algorithms

　　Experience in the development and/or application of optimization and parameter estimation techniques

　　Facility with high performance computing and/or GPU hardware

　　Ability to obtain a DOE Q Clearance

　　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 $92,000. For more information go to Postdoc Program website at https://www.lanl.gov/careers/career-options/postdoctoral-research/index.php .

　　Note to Applicants:

　　Please include in the application a CV, contact information for 3 references, and a detailed cover letter describing your interest in the position and how you meet minimum requirements and desired qualifications

　　Contact Marc Klasky ([email protected]) or Melanie Vigil ([email protected]) for more details about this position

　　For full consideration please apply by March 1, 2024

　　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 childbirth and parental leave

　　§ Award-winning 401(k) (6% matching plus 3.5% annually)

　　§ Learning opportunities and tuition assistance

　　§ Flexible schedules and time off (PTO 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 (https://directives.nnsa.doe.gov/supplemental-directive/sd-0206-0002) . Please note that this requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A.

　　Position does not require a security clearance. Selected candidates will be subject to drug testing and other pre-employment background checks.

　　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 and supports a diverse and inclusive workforce. All employment practices are based on qualification and merit, without regard to 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 federal 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 such an accommodation, please send an email to [email protected] or call 1-505-665-4444 option 1.