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Modeling Simulation Engineer Jobs in North Carolina

These models are used to predict performance, fuel consumption, heat rejection, and system ... simulation, virtual engineering, or engine performance analysis, with a primary focus on GT‑SUITE ...

Modeling and Simulation Support Lead Location : Fort Bragg (Fort Liberty), NC Clearance required : SECRET Responsibilities include (but are not limited to): * Direct and manage the Simulation Support ...

... models--into a cohesive simulation environment. * Direct the development and deployment of track‑side tools. Foster the critical engineering bridges between HHDM and VAST. * Own the strategic ...

Supervisor, Automation Process

Hickory, NC · On-site

$125 - $171.87/hr

Lead process concept evaluation and down‑selection; identify critical knowledge gaps and drive closure through engineering analysis, modeling, simulation, and targeted experimentation * Mature and ...

Showing results 21-40

Modeling Simulation Engineer information

See North Carolina salary details

$35.4K

$112.1K

$173.1K

How much do modeling simulation engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for modeling simulation engineer in North Carolina is $112,146.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,600.00 and $133,100.00 per year, depending on experience, location, and employer.

What does a modeling simulation engineer do?

A Modeling Simulation Engineer develops virtual models and simulations to analyze complex systems and processes. They use mathematical models, computer simulations, and data analysis to predict system performance and optimize designs before physical implementation. These engineers typically work in industries like aerospace, defense, automotive, and healthcare to improve efficiency, safety, and decision-making. Their role often involves coding, algorithm development, and working with simulation software to test real-world scenarios in a virtual environment.

What are the typical responsibilities and project stages for a modeling simulation engineer?

Modeling Simulation Engineers are responsible for developing mathematical models, running simulations, analyzing results, and providing recommendations to improve system performance or design. Projects often begin with understanding client or stakeholder requirements, followed by designing models based on those needs and iteratively refining them as data is collected. Engineers work closely with design, hardware, and software teams to validate models and ensure alignment with real-world performance. Collaborating with colleagues and presenting findings to both technical and non-technical audiences are routine aspects of the job, making cross-functional communication vital for project success.

What are the key skills and qualifications needed to thrive in the modeling simulation engineer position, and why are they important?

To thrive as a Modeling Simulation Engineer, you need a strong background in mathematics, physics, and computer science, typically supported by a relevant engineering or science degree. Proficiency with simulation software such as MATLAB, Simulink, ANSYS, or similar tools, and sometimes certifications in systems engineering or modeling methodologies, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills set top candidates apart. These qualifications are crucial for accurately representing complex systems, translating requirements into effective models, and collaborating with multidisciplinary teams to achieve project goals.

What are the most commonly searched types of Modeling Simulation Engineer jobs in North Carolina?

The most popular types of Modeling Simulation Engineer jobs in North Carolina are:

Infographic showing various Modeling Simulation Engineer job openings in North Carolina as of August 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Hybrid job distribution, with an average salary of $112,146 per year, or $53.9 per hour.

Modeling and Simulation Manager

Vulcan Elements

Durham, NC

Full-time

Re-posted 20 days ago


Job description

Vulcan Elements is manufacturing American rare-earth permanent magnets for a secure, resilient future. With a focus on national security and economic resiliency, we serve critical industries such as defense, aerospace, and automotive powering a high-technology future. Vulcan Elements is building a team of ambitious professionals committed to Mission Focus, Technical Excellence and Transparency.

As the Modeling and Simulation Manager you will grow and lead a multidisciplinary team of computational scientists and engineers, driving physics-based and data-based modeling efforts that directly improve magnet performance, production yields, and process efficiency.

This is a hands-on technical leadership role. You will both contribute directly to modeling work and grow a team with deep expertise across a variety of modeling and simulation modalities, including but not limited to mechanical, fluid dynamics, electronic structure, and mathematical and image analysis. Your group's output will shape process decisions, reduce experimental iteration cycles, and create quantitative links between structure, processing conditions, and final properties.

This role will initially support pilot-scale and R&D activities (RTP, NC), with the potential to contribute to commercial plant operations (Benson, NC) in the next year.

The ideal candidate has hands-on experience with one or more of COMSOL, Fluent, finite element analysis, thermodynamic modeling (FactSage, ThermoCalc), mathematical and image analyses, and density functional theorgy, as well as experience as a people leader.

Responsibilities

Build and manage a matrixed modeling and simulations team with broad expertise spanning Finite element analysis, Computational fluid dynamics, Stress/Strain analysis, thermodynamic modeling, mathematical/image analysis, and DFT; define hiring roadmap, team structure, and capability milestones.

  • Translate R&D priorities into a modeling agenda with clear deliverables, timelines, and success criteria in partnership with process engineering, materials science, and production teams.
  • Foster a culture of scientific rigor, reproducibility, and rapid iteration; establish standards for model validation, documentation, and peer review.
  • Present results and recommendations to technical and executive stakeholders; communicate uncertainty and model limitations clearly.

Responsibilities and tasks outlined are not exhaustive and may change as determined by the needs of the business.

Qualifications

  • Ph.D. or M.S. in Materials Science, Chemical Engineering, Mechanical Engineering, Applied Physics, or a related quantitative field.
  • 5+ years of hands-on experience with COMSOL, Fluent, or equivalent; demonstrated ability to build and validate coupled multiphysics models and finite element analysis (FEA).
  • Strong mathematical modeling background; experience with image analysis, machine learning, statistical modeling, or signal processing applied to materials characterization data.
  • Familiarity with rare earth magnets, NdFeB alloy systems, or related metallic/magnetic materials.
  • Experience leading or mentoring a small technical team; ability to set priorities, provide technical guidance, and develop junior researchers.
  • Proficiency in Python, MATLAB, Git, or equivalents for scripting, data analysis, and model post-processing.
  • Strong written and verbal communication skills; able to produce clear technical reports and present complex results to non-specialist audiences.

Must be a U.S. Person due to required access to U.S. export-controlled information or facilities

Preferred Qualifications

  • Direct experience with DFT codes (VASP, Quantum ESPRESSO, or similar) or demonstrated ability to direct and interpret DFT studies.
  • Background in rare earth processing, hydrometallurgy, or magnet manufacturing.
  • Experience with grain boundary diffusion processes or sintering simulation.
  • Familiarity with thermodynamic modeling and databases such as FactSage, or ThermoCalc
  • Knowledge of machine learning principles for data analysis
  • Familiarity with electron microscopy image analysis (SEM/EDS/EBSD) and quantitative microstructural characterization.
  • Publication record in computational materials science, process simulation, or permanent magnets.
  • Experience managing budgets, external collaborators, or academic partnerships.