Design Optimization Engineer - Postdoctoral Researcher

Entry Level | Full-time
Engineering | Livermore, CA | 05/13/2026
Reference #: REF
8361P
Job Code: PDS.
1 Post-Dr Research Staff 1
Organization: Engineering
Position Type: Post Doctoral
Security Clearance: Anticipated DOE Q clearance (requires U.S. citizenship and a federal background investigation)
Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana)
Medical Exam: Not applicable Apply Now

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

We have an opening for a Design Optimization Engineer - Postdoctoral Researcher to conduct basic and applied research in the optimization, simulation, and design of physical and engineered systems. You will work both collaboratively and independently to extend and develop physics-based design optimization tools. Our team is working to advance the state-of-the-art in support of Laboratory missions. This position is in the Computational Engineering Division (CED), within the Engineering Directorate.

Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.

You will

• Develop and implement high-performance computing (HPC) algorithms for the simulation and design optimization of systems governed by nonlinear, transient, multiscale and multiple physical phenomena, including uncertainties in geometry and material properties.
• Contribute to identifying and solving challenging design optimization problems with gradient-based optimization approaches.
• Develop continuum models and implement them in our HPC numerical analysis software to solve the governing partial differential equations of the physical system, to predict design responses of interest.
• Demonstrate our design optimization capabilities and establish credibility with mission customers.
• Document research findings through presentations and peer-reviewed journal articles and contribute to identifying future research directions and proposals that will provide opportunities in the field.
• Collaborate with multidisciplinary teams to integrate design optimization tools with other simulation and analysis frameworks.
• Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
• Stay current with technological advancements by updating and enhancing your knowledge of the latest HPC algorithms, simulation techniques, and design optimization methods.
• Perform other duties as assigned.

• Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
• PhD in Engineering, Mathematics, Computational Science, or a related field.
• Experience developing custom simulation tools using continuum discretization approaches (e.g., finite elements) for physical systems.
• Proficiency in programming languages such as C/C++/FORTRAN and scripting languages including Python.
• Fundamental knowledge of HPC and one or more associated parallel programming interfaces, such as MPI, OpenMP, or CUDA.
• Ability to perform independent research.
• Proficient verbal and written communication skills needed to effectively collaborate in a team environment, to present and explain technical information, to document work, and to prepare and present successful proposals and high-quality research papers.

Qualifications We Desire

• Experience in design sensitivity analysis via direct (forward) and adjoint (backward) methods, shape/topology optimization and other design optimization techniques; familiarity with machine learning and data science techniques.
• Experience simulating and designing systems that involve complex nonlinear, transient, multiphysics models; proficient in nonlinear solvers, and linear algebra concepts for solving challenging linear systems.
• Experience working in a collaborative software development environment, including experience with version control systems, such as Git.
• Adept at tackling complex technical challenges with a logical and analytical approach, working effectively with experts from various fields, and promoting an inclusive and diverse work environment.

Pay Range

$122,028 - $143,328 Annually

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors…