Senior Computational Modeling Engineer – Hybrid

Sandia National Laboratories; New Mexico; Hybrid; USD 139,000 - 236,000; Full time

Job summary

Sandia National Laboratories is seeking a Senior/Principal Computer Science Engineer to develop and produce state‑of‑the‑art methods for solving computational mechanics optimization problems. The role requires proximity to Albuquerque, NM or Livermore, CA, with hybrid onsite/offsite reporting as needed for team activities.

You will work on inverse problems, optimal experimental design, and topology/shape optimization, with a focus on C++ in a massively parallel environment.

Qualifications

• Bachelor's degree in a relevant discipline with five years of directly relevant experience or equivalent combination of education and engineering/science experience.
• Experience with optimization.
• Experience with computational mechanics concepts and applications.
• Experience with scientific programming including some exposure to C++ and scripting languages.
• Ability to obtain a DOE Q-level security clearance.

Responsibilities

• Develop fundamental algorithm research on inverse methods, optimal design of experiments, shape and topology optimization with C++ in a massively parallel environment.
• Collaborate with Sandia's Computational and Experimental groups to fuse test data and simulations for parameter estimation and design of experiments.
• Implement research ideas in a massively parallel C++ computing environment.
• Integrate AI/ML strategies with optimization-based solutions for design and inverse problems.
• Publish research in leading journals and present at conferences.

Skills

Optimization

Computational mechanics

C++

Scripting

Security clearance

Education

Bachelor's degree

PhD in Computer Science or related field

Tools

Cubit

Plato

Sierra Inverse Optimization

Sierra Mechanics

Job description

Sandia National Laboratories is seeking a Senior/Principal Computer Science Engineer to develop and produce state‑of‑the‑art methods for solving computational mechanics optimization problems. The role requires proximity to Albuquerque, NM or Livermore, CA, with hybrid onsite/offsite reporting as needed for team activities.

You will work on inverse problems, optimal experimental design, and topology/shape optimization, with a focus on C++ in a massively parallel environment.