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Intern Computational Materials Science Jobs in Virginia

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Intern Computational Materials Science information

What is the difference between Intern Computational Materials Science vs Intern Materials Engineering?

AspectIntern Computational Materials ScienceIntern Materials Engineering
Required CredentialsUndergraduate or graduate in materials science, physics, or related fields; basic programming skillsUndergraduate or graduate in materials engineering, mechanical engineering, or related fields; foundational technical knowledge
Work EnvironmentResearch labs, computational modeling, data analysisDesign, testing, and development in labs or manufacturing settings
Industry UsageResearch institutions, tech companies, aerospace, academiaManufacturing firms, product development, construction

Intern Computational Materials Science focuses on computational modeling and simulations of materials properties, while Intern Materials Engineering emphasizes practical design, testing, and application of materials. Both roles require a background in materials-related fields but differ in their core activities and work environments.

What does an intern in computational materials science do?

An Intern in Computational Materials Science assists in research and development by applying computational techniques to study and predict the properties and behaviors of materials. Typical tasks include running simulations, analyzing data, and working with software tools to model materials at the atomic or molecular level. Interns may collaborate with researchers to design experiments, interpret results, and contribute to scientific publications or reports. This role provides hands-on experience in both computational methods and materials science, helping to bridge theory and practical application.

What are the key skills and qualifications needed to thrive as an intern in computational materials science, and why are they important?

To thrive as an Intern in Computational Materials Science, you need a solid background in materials science, physics, or engineering, along with coursework in computational modeling and data analysis. Familiarity with programming languages like Python or MATLAB, experience with simulation software (such as VASP or LAMMPS), and knowledge of high-performance computing are typically required. Strong analytical thinking, attention to detail, and effective teamwork are important soft skills for success in collaborative research environments. These skills enable interns to contribute meaningfully to research projects, analyze complex materials data, and communicate findings clearly within multidisciplinary teams.

What types of projects can an intern in computational materials science expect to work on during their internship?

As an Intern in Computational Materials Science, you can expect to engage in projects involving simulations of material properties, data analysis from computational experiments, and the development of models to predict material behavior. You may collaborate with researchers and senior scientists to support ongoing investigations or help optimize simulation workflows. These projects often require proficiency in programming languages such as Python or MATLAB and may involve the use of specialized software like VASP or LAMMPS. The experience provides a hands-on understanding of how computational methods contribute to advancing materials research and often includes opportunities to present your findings to the team.

What are the most commonly searched types of Computational Materials Science jobs in Virginia?

The most popular types of Computational Materials Science jobs in Virginia are:

What are popular job titles related to Intern Computational Materials Science jobs in Virginia?

For Intern Computational Materials Science jobs in Virginia, the most frequently searched job titles are:

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The top searched job categories for Intern Computational Materials Science jobs in Virginia are:

What cities in Virginia are hiring for Intern Computational Materials Science jobs?

Cities in Virginia with the most Intern Computational Materials Science job openings:

Intern Computational Materials Science jobs near you

Computational Physics Specialist - Remote

micro1 AI

Norfolk, VA • Remote

$80 - $140/hr

Part-time

Posted 13 days ago

Job description

Role Title: Physics Expert (PhD / Postdoc)


Role Type: Contractor.


Location: Remote


micro1 is engaging Physics Experts (PhD / Postdoc) to contribute deep scientific knowledge and problem-solving skills to a high-impact customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Solve advanced physics problems from your specialization, delivering rigorous, well-documented derivations and analyses.
  2. Produce technically precise, clearly written solutions, detailing all assumptions, approximations, and final results using LaTeX mathematical notation.
  3. Utilize SymPy, Python, and Jupyter for symbolic or numerical verification and clear computational workflows where relevant.
  4. Identify and articulate subtleties in problem statements, including special cases, boundary conditions, and dimensional consistency.
  5. Flag ambiguities in project materials, proposing well-reasoned interpretations and clarifications as needed.
  6. Iterate on submitted solutions in response to feedback from project reviewers, ensuring corrections are cleanly integrated.
  7. Uphold rigorous standards in documentation and reproducibility consistent with professional research practice.


Preferred Qualifications

  1. PhD in physics or advanced-stage PhD candidacy, with active research experience in a relevant subfield.
  2. Research expertise in one or more of: High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics, Condensed Matter (including moiré systems, magnetism, PXP/Rydberg), AMO/Quantum Optics, Gravitation, Cosmology, Astrophysics, Quantum Information, or Optical Properties of Materials.
  3. 2–5 recent representative publications (past ~5 years) in your field, with accessible arXiv or DOI records.
  4. Proficiency with LaTeX for presenting mathematics, and with SymPy, Python, and Jupyter for computational work; willingness to indicate areas for further support if needed.
  5. Demonstrated excellence in written technical communication, with a track record of producing clear, precise, and well-argued scientific outputs.
  6. Strong analytical skills, able to isolate key physical principles and provide nuanced solutions to complex problems.
  7. Availability to engage with the project consistently over an 8–10 week period (approx. 10 hours/week).

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