CASC Hybrid Modeling and Machine Learning Postdoctoral Researcher

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 dedicated to fostering a culture that values individuals, talents, partnerships, ideas, experiences, and different perspectives, recognizing their importance to the continued success of the Laboratory’s mission.

Job Description

We are looking for a postdoctoral researcher to advance fundamental R&D at the intersection of reduced-order modeling, foundation models for the computational sciences, and statistical/machine learning methods. You will help develop scalable models and methods for materials science, fusion, and additive manufacturing, and lead decision-making process, such as design optimization and uncertainty quantification and rigorous validation of deep learning integrated with simulation. Furthermore, you will develop methods to improve interpretability and trustworthiness of these models. This position will be in the Center for Applied Scientific Computing (CASC) Division within the LLNL Computing Directorate.

Essential Duties

• Research & prototype hybrid reduced order model/machine learning methods (DD-FEM, LaSDI, gappy Autoencoder, proper orthogonal decomposition, and neural operators) tightly coupled to governing equations.
• Design discretizations & integrators: derive/implement stable and accurate spatial discretizations (e.g., finite element, finite volume, finite difference methods) and time integrators (e.g., explicit/implicit Runge–Kutta, multistep/BDF).
• Guarantee physics & reliability: enforce conservation/stability, perform error and sensitivity analysis, and lead UQ, and explainability for hybrid models.
• Integrate with HPC codes and experimental/simulation workflows.
• Publish results, contribute proposals, and collaborate across disciplines.
• Perform other duties as assigned.

Qualifications

• Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA). See Additional Information section below for details.
• Ph.D. in Computational Science, Applied Mathematics, Engineering, Statistics, or a related field.
• Demonstrated ability and desire to obtain substantial domain knowledge in fields of application to enable effective communication with subject matter experts, and to identify novel, impactful applications of machine learning.
• Demonstrated expertise in spatial discretization methods (finite element, finite volume, and finite difference methods).
• Strong background in numerical time integration techniques. Demonstrated experience with numerical analysis, including stability and convergence.
• Experience building and evaluating modern ML models using PyTorch, TensorFlow, and/or JAX.
• Significant software development experience with the Python scientific software stack; demonstrated experience following modern software engineering practices (e.g. testing, version control, reproducibility).
• Significant experience building and evaluating reduced order models using Proper Orthogonal Decomposition, Dynamic mode decomposition, and/or hyper-reduction.
• Significant experience using the libROM software library or equivalent.
• Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software, in relevant venues (NeurIPS, ICML, JCP, CMAME, Science, IJNME, SISC, Nature etc.).

Desired Qualifications

• Experience with high-performance computing, GPU programming, parallel programming, and/or related methods including running numerical simulations of complex workflows.
• Demonstrated technical leadership in fields related to computational science and machine learning, such as mentorship or managing teams.
• Experience or interest in scientific applications, such as, material science, climate science, fusion, earthquake, and additive manufacturing.

Additional Information

#LI-Hybrid

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 2025 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Our values - visit https://www.llnl.gov/inclusion/our-values

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.)

National Defense Authorization Act (NDAA)

The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities. The restrictions of NDAA Section 3112 apply to this position. To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112.

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.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.