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Internship Computational Material Science Jobs in Raleigh, 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 ...

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 ...

... 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 ...

... Science, Software Engineering, Biomedical Engineering (with computational focus), or related field * Preference for students who have completed 3+ years of coursework by the internship start date

... Science, Software Engineering, Biomedical Engineering (with computational focus), or related field * Preference for students who have completed 3+ years of coursework by the internship start date

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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Internship Computational Material Science information

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How much do internship computational material science jobs pay per hour?

As of Jul 24, 2026, the average hourly pay for internship computational material science in Raleigh, NC is $18.78, according to ZipRecruiter salary data. Most workers in this role earn between $15.67 and $20.34 per hour, depending on experience, location, and employer.

What is an internship in computational material science?

An internship in computational material science is a temporary position, often for students or recent graduates, where participants work with experts to apply computer modeling and simulations to study materials at the atomic or molecular level. Interns typically use specialized software to predict material properties, analyze data, and support ongoing research projects. These internships provide hands-on experience in both materials science and computational techniques, helping to prepare individuals for careers or further study in the field.

What types of projects and collaborations can I expect during an Internship in Computational Material Science?

As an intern in Computational Material Science, you will typically work on projects involving the simulation and modeling of materials using computational tools and software. These projects often require close collaboration with other interns, research scientists, and sometimes experimentalists to validate your computational results. You may contribute to ongoing research, assist in code development, analyze data, and present findings to the team. This environment encourages skill development in programming, data analysis, and scientific communication, while also providing valuable exposure to multidisciplinary teamwork.

What are the key skills and qualifications needed to thrive as an Internship Computational Material Science, and why are they important?

To thrive as an intern in Computational Material Science, you generally need a strong foundation in materials science, physics, chemistry, and programming, often supported by coursework or experience in these areas. Familiarity with simulation software (such as VASP, LAMMPS, or Quantum ESPRESSO), coding languages like Python or MATLAB, and potentially basic knowledge of high-performance computing systems is typically required. Analytical thinking, attention to detail, and effective communication are valuable soft skills that help in interpreting results and collaborating with research teams. These skills and qualities are essential for conducting accurate simulations, solving complex research problems, and contributing meaningfully to scientific projects.
What are the most commonly searched types of Computational Material Science jobs in Raleigh, NC? The most popular types of Computational Material Science jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Internship Computational Material Science jobs? Cities near Raleigh, NC with the most Internship Computational Material Science job openings:

Modeling and Simulation Manager

Vulcan Elements

Raleigh, NC

Full-time

Posted 21 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.