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Modeling and Simulation Manager

Vulcan Elements

Raleigh, NC • 10/1/2026

Job Description

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 amultidisciplinary team of computational scientists and engineers, driving physics-based and data-based modeling efforts that directly improve magnetperformance, 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 thenext year.

The ideal candidate has hands-on experiencewithone or more ofCOMSOL, Fluent,finite element analysis,thermodynamic modeling (FactSage,ThermoCalc),mathematical and image analyses, anddensity functionaltheorgy, as well as experience as a people leader.

Responsibilities

Build and manage amatrixedmodeling and simulations teamwith broadexpertisespanningFinite 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;establishstandards 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 asdeterminedby 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;demonstratedability to build andvalidatecoupledmultiphysicsmodelsandfinite 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 relatedmetallic/magneticmaterials.
  • Experience leading or mentoring a small technical team; ability to set priorities,providetechnical guidance, and develop junior researchers.
  • Proficiencyin Python, MATLAB,Git,or equivalentsforscripting,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) ordemonstratedability 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 asFactSage, orThermoCalc
  • Knowledge of machine learningprinciples 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.