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Computational Materials Science Jobs in Raleigh, NC

Wolfspeed

Manager of Research Science

Durham, NC · On-site

As a Manager of Research Science in Machine Learning, you will direct a research group to develop ... computational modeling of materials systems such as DFT and finite element model Multiphysics ...

NCSU

Post-Award Specialist

Raleigh, NC · On-site

... Materials Science and Engineering About the Department The Department of Materials Science and ... computational materials. Wolfpack Perks and Benefits As a Pack member, you belong here, and can ...

Wolfspeed, Inc.

Manager of Research Science

Durham, NC · On-site

As a Manger of Research Science in Machine Learning you will direct the activities of a research ... Expertise in computational modeling of materials systems such as DFT and finite element model ...

Cree

Manager of Research Science

Durham, NC

As a Manger of Research Science in Machine Learning you will direct the activities of a research ... Expertise in computational modeling of materials systems such as DFT and finite element model ...

Ramona

Computational Imaging Engineer

Durham, NC · On-site

$107K - $127K/yr

... sample materials and assess their variability, building this understanding into the system ... for scientific computing and image processing. • Familiarity with how mechanical accuracy ...

New

Susteon

Catalysis Scientist

Morrisville, NC · On-site

PhD in Chemistry, Chemical Engineering, or Materials Science with 4+ years of heterogeneous ... Experience working closely with computational or ML teams and structured data systems (SQL, time ...

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All JobsComputational Materials Science JobsComputational Materials Science Jobs in Raleigh, NC

Computational Materials Science information

See Raleigh, NC salary details

$136.6K

$161.8K

$184.5K

How much do computational materials science jobs pay per year?

As of Jul 2, 2026, the average yearly pay for computational materials science in Raleigh, NC is $161,846.00, according to ZipRecruiter salary data. Most workers in this role earn between $149,100.00 and $174,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Computational Materials Scientist, and why are they important?

To thrive as a Computational Materials Scientist, you need a solid background in materials science, physics, or chemistry, often with a graduate degree and experience in scientific computing. Proficiency with simulation software (such as VASP, LAMMPS, or Quantum ESPRESSO), programming languages (like Python, C++, or Fortran), and familiarity with high-performance computing systems is typically required. Critical thinking, problem-solving abilities, and effective collaboration and communication skills set outstanding candidates apart. These competencies are crucial for designing, executing, and interpreting complex simulations and for translating computational insights into real-world materials innovations.

What is the difference between Computational Materials Science vs Materials Engineer?

AspectComputational Materials ScienceMaterials Engineer
Required CredentialsTypically requires a PhD or Master's in materials science, physics, or chemistryBachelor's or Master's in materials engineering or related field
Work EnvironmentResearch labs, universities, or R&D departments focusing on simulations and modelingManufacturing plants, design offices, or product development teams
Industry UsagePrimarily in research, academia, and advanced R&D projectsProduction, quality control, and product development in manufacturing industries
Common Search/ComparisonYesYes

Computational Materials Science focuses on using computer simulations and modeling to understand and predict material behavior, often requiring advanced degrees. Materials Engineers work on designing, testing, and improving materials in practical applications, usually with a bachelor's or master's degree. While both roles are integral to materials development, Computational Materials Science is more research-oriented, whereas Materials Engineering emphasizes application and production.

What are some common challenges faced by professionals in Computational Materials Science, and how can they be addressed?

Professionals in Computational Materials Science often encounter challenges such as dealing with large datasets, managing the complexity of multi-scale simulations, and ensuring the accuracy of computational models. Addressing these challenges typically involves staying updated on the latest simulation software, collaborating closely with experimental teams to validate results, and developing strong programming and data analysis skills. Effective communication and interdisciplinary teamwork are also key, as projects often require input from chemists, physicists, and engineers to achieve successful outcomes.

What Are Computational Materials Science Jobs?

Jobs in computational materials science include academic and research positions in university settings. You can also find positions in the manufacturing industry. As a research scientist in computational materials science, your duties are to develop hypotheses and test them using computational modeling software and a variety of investigatory tools, such as Monte Carlo algorithms, density function theory, phase field models, and finite element methods. Your responsibilities include gathering data, testing modeling software, collaborating with other researchers to develop tools that aid them in their research, and analyzing data to write reports, journal articles, or presentations for conferences.

What is computational materials science?

Computational materials science is a field that uses computer-based simulations and modeling to understand, predict, and design the properties and behaviors of materials. Researchers use mathematical models, algorithms, and high-performance computing to study materials at the atomic, molecular, or macroscopic level. This approach allows scientists to accelerate the discovery of new materials, optimize existing ones, and investigate phenomena that may be difficult or expensive to study experimentally.
More about Computational Materials Science jobs
What are the most commonly searched types of Computational Materials Science jobs in Raleigh, NC? The most popular types of Computational Materials Science jobs in Raleigh, NC are:
What are popular job titles related to Computational Materials Science jobs in Raleigh, NC? For Computational Materials Science jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Computational Materials Science jobs in Raleigh, NC look for? The top searched job categories for Computational Materials Science jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Computational Materials Science jobs? Cities near Raleigh, NC with the most Computational Materials Science job openings:
Computational Materials Science jobs near you
Infographic showing various Computational Materials Science job openings in Raleigh, NC as of June 2026, with employment types broken down into 1% As Needed, 92% Full Time, 6% Part Time, and 1% Contract. Highlights an 69% Physical, 1% Hybrid, and 30% Remote job distribution, with an average salary of $161,846 per year, or $77.8 per hour.

Modeling and Simulation Manager

Vulcan Elements

Raleigh, NC

Full-time

Posted 29 days ago

Be an early applicant

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.