As a postdoc you will:

Design, analyze, and implement operator neural networks (e.g., DeepONets, Fourier/Neural Operators, graph/mesh operators) that respect conservation laws, symmetries, and stability constraints relevant to compressible hydro, radiation-hydrodynamics, and MHD. Develop mathematical foundations for operator learning: approximation/error bounds, well-posedness, stability, and generalization for PDE-to-PDE maps; contribute proofs and rigorous analyses. Integrate physics into learning (e.g., variational/energy principles, constrained training, differentiable solvers, PINO/PINN-style residuals) and build robust surrogates for stiff, multi-scale flows. Run large-scale computational experiments on CPU/GPU clusters; compare against high-fidelity solvers and community benchmarks. Collaborate across math, CS, and plasma physics, publish in leading journals, present at conferences, and engage with external research partners.

What You Need Minimum Job Requirements:

Minimum Job Requirements Education:

Ph.D. (earned within the last 5 years) in Applied Mathematics, Mathematics, or a closely related field (e.g., CS, Statistics, Physics, Engineering).

Mathematical depth:

Demonstrated strength in functional analysis/operator theory, numerical PDEs, approximation theory, and/or stochastic processes; ability to craft rigorous arguments (stability, error estimates, convergence).

Scientific ML:

Research experience in neural operators / scientific machine learning (operator learning, PINNs/PINOs, PDE-constrained learning, model reduction) with a strong publication record.

Programming:

Proficiency in Python and one or more of PyTorch/JAX/TensorFlow; working knowledge of scientific computing (vectorization, profiling, testing).

Communication:

Clear written and oral communication, as shown through publications and the cover letter. Desired Qualifications Experience with hydrodynamics/ICF/HEDP physics (e.g., shocks, turbulence, EOS, radiation transport, MHD) or with high-order/structure-preserving numerical methods. HPC skills (MPI, Open

MP, CUDA, GPU

acceleration), containers, CI, and collaborative software development. Contributions to open-source ML/scientific software; code reviews; reproducible workflows. Background in UQ/data assimilation/Bayesian inference, multi-fidelity or active learning for PDE models. Evidence of competitive excellence (e.g., research awards, notable competitions) and effective teamwork. Education/Experience A Ph.D. in Applied Mathematics, Mathematics, Computer Science, Statistics, Physics, or a closely related field, earned within the last 5 years. Work Location On-site in Los Alamos, NM. Note to Applicants For questions, contact Marc Klasky (mklasky@lanl.gov).

Include in your application:

CV Cover letter describing research interests, relevant math/ML background, and career goals Contact information for two references Please submit materials via the LANL Jobs website.

Work Location:

The work location for this position has the potential for remote work. Remote work is defined as working offsite that is greater than 2 hours of the Laboratory location. Reporting onsite may be periodically necessary. All work locations are at the discretion of management. Note to

Applicants:

Due to federal restrictions contained in the current National Defense Authorization Act, citizens of the People's Republic of China-including the special administrative regions of Hong Kong and Macau-as well as citizens of the Islamic Republic of Iran, the Democratic People's Republic of Korea (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 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 . 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.

No Clearance:

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.

Internal Applicants:

Regular appointment employees who have served the required period of continuous service in their current position are eligible to apply for posted jobs throughout the Laboratory. If an employee has not served the required period of continuous service, they may only apply for Laboratory jobs with the documented approval of their Division Leader. Please refer to Policy Policy P701 for applicant eligibility requirements.

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 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. 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Postdoctoral Researcher - Operator Networks for Hydrodynamics & Inertial Confinement Fusion