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Internship Computational Material Science Jobs in California

Leidos

Computational Imaging Scientist

San Diego, CA · On-site

You will develop and apply computational imaging models that connect optical design, image ... Basic Qualifications * BS degree in Physics, Materials Science, Optics, or a related field with 8+ ...

Leidos

Computational Imaging Scientist

San Diego, CA · On-site

You will develop and apply computational imaging models that connect optical design, image ... Basic Qualifications * BS degree in Physics, Materials Science, Optics, or a related field with 8+ ...

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Internship Computational Material Science information

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 intern in 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 California?

The most popular types of Computational Material Science jobs in California are:

What cities in California are hiring for Internship Computational Material Science jobs?

Cities in California with the most Internship Computational Material Science job openings:

Internship Computational Material Science jobs near you

Research Scientist/Engineer, Materials

Periodic Labs

Menlo Park, CA • On-site

$250K - $350K/yr

Full-time

Posted 16 days ago

Job description

About Periodic Labs
We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.
About the Role
At Periodic Labs, we are automating scientific research in materials discovery; the data we collect, and how we represent it, is what makes this possible. We are hiring a materials scientist to work across the entire process: to find where our agents and data fail, and to fix those failures at the source. This is a hybrid research and infrastructure role. Roughly half your time will be spent working directly with our experimental and computational scientists, building agents and tools that solve active research problems. The other half will be spent improving the data those agents depend on.
This role requires domain depth, not just data engineering skill. You need to know, for example, what metadata actually matters for a given characterization technique. The research half of the role keeps you grounded in the problems we are actually using LLMs to solve, so the schemas you build serve real research rather than an abstraction of it. The work demands attention to detail and a willingness to get into the weeds: to meticulously read, understand, and improve our data. You'll be as much a materials scientist doing research as the person who makes our agentic harness actually work.
What You'll Do
  • Work directly with lab scientists and the computational team on active research problems, staying close to the actual bottlenecks LLM agents are meant to solve.
  • Investigate agent traces to identify data errors and agentic failure modes, and eliminate them at the source.
  • Restructure and re-architect our materials databases (lab experiments, characterization data, computations) around how LLM agents actually reason and fail, not just around human readability. Draw on domain expertise about how to represent the data and what metadata matters.
  • Work with the hardware and automation teams to make data collection more robust.
  • Build research software for lab environments, translating scientific requirements into working tools.
  • Distill what you learn into evaluations that measure agent performance.

Mechanics
  • Minimum experience: 4+ years of research or industry experience in experimental or computational materials science and working with data at scale.
  • Minimum education: PhD in Materials Science, Chemistry, or a related field, or equivalent industry experience.
  • Location: Menlo Park, CA (Soon: San Francisco, too)
  • Compensation: $250,000-350,000 + equity
  • Visa sponsorship: Yes, we sponsor visas.

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