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Computational Modeling Simulation Multiphysics Jobs in Missouri

Boeing

Senior Low Observables (LO) RCS Analyst

Berkeley, MO · On-site

$82K - $109K/yr

Experience using computational electromagnetic (CEM) tools such as SENTRI, XPATCH, CARLOS, HFSS ... Experience preparing CAD models for electromagnetic simulation and analysis * Strong technical ...

Boeing

Senior Low Observables (LO) RCS Analyst

Berkeley, MO · On-site

$82K - $109K/yr

Experience using computational electromagnetic (CEM) tools such as SENTRI, XPATCH, CARLOS, HFSS ... Experience preparing CAD models for electromagnetic simulation and analysis * Strong technical ...

Leonardo DRS

Controls Systems Engineer II

Bridgeton, MO · On-site

$79.92 - $103.89/hr

... computational delay/latency, quantization, filtering, saturation, and anti-windup * Support real ... Study alternative concepts and use models and simulations to predict closed-loop system performance ...

Leonardo DRS

Controls Systems Engineer II

Bridgeton, MO · On-site

$79K - $103K/yr

... computational delay/latency, quantization, filtering, saturation, and anti-windup * Support real ... Study alternative concepts and use models and simulations to predict closed-loop system performance ...

Leonardo DRS

Controls Systems Engineer II

Bridgeton, MO

$79K - $103K/yr

... computational delay/latency, quantization, filtering, saturation, and anti-windup * Support real ... Study alternative concepts and use models and simulations to predict closed-loop system performance ...

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Computational Modeling Simulation Multiphysics information

What is computational modeling simulation multiphysics?

Computational modeling simulation multiphysics refers to the use of computer-based models to simulate and analyze systems that involve multiple interacting physical phenomena—such as fluid dynamics, heat transfer, electromagnetics, and structural mechanics—all at once. This approach allows researchers and engineers to predict complex real-world behavior, optimize designs, and reduce the need for expensive prototypes. Multiphysics simulations are widely used in industries like aerospace, automotive, energy, and biomedical engineering, where accurate modeling of coupled physical processes is critical.

What are common challenges faced by professionals in computational modeling simulation multiphysics, and how can they be addressed?

One of the main challenges in Computational Modeling Simulation Multiphysics roles is managing the complexity of integrating multiple physical phenomena, such as thermal, structural, and fluid dynamics, into a single simulation. This often requires a deep understanding of both the underlying physics and the numerical methods used by simulation software. Collaborating closely with domain experts and maintaining clear communication within multidisciplinary teams can help address these challenges. Additionally, staying updated with advances in simulation tools and best practices through continuous learning is key to overcoming technical hurdles and ensuring accurate results.

What are the key skills and qualifications needed to thrive as a computational modeling simulation multiphysics engineer, and why are they important?

A strong background in physics, engineering, mathematics, and computational science—typically with an advanced degree—is essential for a Computational Modeling Simulation Multiphysics Engineer. Proficiency in simulation software such as ANSYS, COMSOL Multiphysics, MATLAB, and programming languages like Python or C++ is commonly required, along with familiarity with high-performance computing environments. Analytical thinking, problem-solving skills, and effective communication set standout professionals apart in this field. These capabilities enable accurate modeling of complex physical phenomena, efficient collaboration, and successful project outcomes in research and industry settings.

What is the difference between Computational Modeling Simulation Multiphysics vs Computational Engineer?

AspectComputational Modeling Simulation MultiphysicsComputational Engineer
CredentialsTypically requires degrees in engineering, physics, or related fields; certifications in simulation software are commonSimilar educational background; often holds engineering degrees and software certifications
Work EnvironmentPrimarily in R&D labs, engineering firms, or manufacturing settings focusing on complex simulationsInvolved in product development, software development, or systems design in various industries
Industry UsageUsed in aerospace, automotive, energy, and manufacturing for advanced simulationsApplied across industries for designing, analyzing, and optimizing systems and products

While both roles involve computational skills and engineering principles, Computational Modeling Simulation Multiphysics specializes in complex, multi-physics simulations, whereas Computational Engineer focuses on designing and implementing computational solutions across various engineering projects.

What are popular job titles related to Computational Modeling Simulation Multiphysics jobs in Missouri?

For Computational Modeling Simulation Multiphysics jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Computational Modeling Simulation Multiphysics jobs in Missouri look for?

The top searched job categories for Computational Modeling Simulation Multiphysics jobs in Missouri are:

Computational Modeling Simulation Multiphysics jobs near you
Infographic showing various Computational Modeling Simulation Multiphysics job openings in Missouri as of August 2026, with employment types broken down into 100% Full Time. Highlights an 59% In-person, and 41% Remote job distribution.

Senior Solutions Architect, AI - Accelerated Physics

NVIDIA Gruppe

California, MO • On-site

$184 - $287.50/hr

Other

Posted 4 days ago

Job description

At NVIDIA, we believe that accelerated computing is key to solving the world’s most significant scientific and engineering challenges. We are looking for a Solutions Architect to join our Higher Education and Research Team, where you will serve as a technical partner to the visionaries shaping the future of discovery!

In this role, you will be an integral part of a team supporting higher education universities and research institutes across the nation, with a focus on computational physics, engineering simulation, scientific AI, and high-performance computing. You will help researchers harness NVIDIA platforms to accelerate simulation, build trusted AI surrogates, train scientific foundation models, and unlock new workflows in areas such as fluid dynamics, multiphysics simulation, engineering design exploration, and physics-based modeling at scale.

What you'll be doing:
  • Partner with research universities and institutes to co-create innovative HPC and AI solutions using NVIDIA’s accelerated computing platform
  • Collaborate with engineering, product, and business teams to align NVIDIA’s technical roadmap with the evolving strategies and complex workflows of the scientific and engineering research community
  • Engage with developers and researchers to architect ground‑breaking solutions in areas such as computational physics, multiphysics simulation, engineering design exploration, and the next generation of Scientific Foundation Models
  • Help researchers move from high‑fidelity simulation data to AI‑enabled workflows, including surrogate models, neural operators, physics‑informed models, reduced‑order models, differentiable simulation, and real‑time inference
  • Profile and optimize the performance of scientific applications, AI training, and inference workloads so sophisticated research workflows reach their full potential on accelerated systems
  • Travel requirement up to 20%
What we need to see:
  • BS, MS or PhD in Computational Physics, Engineering, Computer Science, Applied Mathematics, or a related field, or equivalent experience
  • 8+ years of hands‑on experience in accelerated computing and knowledge of parallel computing with GPUs
  • Experience porting and/or optimizing scientific or engineering applications targeting GPUs
  • Strong fundamentals in programming and software design, especially in Python and C++
  • Familiarity with computational physics or engineering simulation workflows, including numerical methods, model validation, uncertainty/error analysis, or simulation‑data pipelines
  • Excellent knowledge of the theory and practice of AI at scale, especially as applied to scientific, simulation, or physics‑based workloads
  • A dedication to clear and inclusive communication with a deep desire to partner with the academic community to help others succeed in their research goals
Ways to stand out from the crowd:
  • Excellent GPU programming skills, including debugging, profiling, code optimization, performance analysis, and test design
  • Experience supporting HPC, AI, computational physics, engineering simulation, or scientific computing workflows
  • Familiarity with NVIDIA scientific computing and AI tools such as PhysicsNeMo, NVIDIA Warp, PyTorch, JAX, or related frameworks
  • Experience building AI‑enabled simulation workflows using neural operators, physics‑informed models, graph neural networks, and/or reduced‑order models
  • A desire to learn and grow within an encouraging, forward‑thinking community dedicated to solving the world’s most significant computational science and engineering challenges

We offer highly competitive salaries and a comprehensive benefits package. The base salary range is 184,000 USD – 287,500 USD, and you will also be eligible for equity and benefits.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal‑opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

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