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Internship Computational Material Science Jobs (NOW HIRING)

Fuse

Computational Physicist

San Leandro, CA · On-site

Your work will contribute to advancements in areas such as materials science, energy, aerospace, or ... Develop custom computational tools and optimize existing codes for high-performance computing (HPC)

Foundation Alloy

Senior Material Scientist

Cambridge, MA · On-site

$50K - $180K/yr

Expertise in one or more of these technical areas: powder metallurgy, sintering, alloy design, computational materials science, and/or relevant metallurgical characterization methods. Culture We do ...

Novelis Global R&T

Modeling Scientist

Kennesaw, GA · On-site

... and computational material scientists. * Establish and lead supporting partnerships with ... PhD in metallurgy, metallurgical engineering, materials science/engineering or mechanical ...

Novelis

Modeling Scientist

Kennesaw, GA

... and computational material scientists. * Establish and lead supporting partnerships with ... PhD in metallurgy, metallurgical engineering, materials science/engineering or mechanical ...

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

As of Jun 30, 2026, the average hourly pay for internship computational material science in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 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.
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Automation Engineer, Materials Research Science

Automation Engineer, Materials Research Science

Meta

Redmond, WA

$184K/yr

Full-time

Posted 13 days ago

Meta rating

7.5

Company rating: 7.5 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

130th of 202 rated software companies

Job description

Meta Reality Labs is seeking an engineer to advance materials research capabilities for next-generation wearables hardware. In this role, you will design, build, and operate the automation backbone of an autonomous materials discovery lab — connecting AI agents, robotic work-cells, and scientific instruments into a seamless, closed-loop pipeline. Working at the intersection of lab automation, agentive AI, and computational materials science, this role translates scientific workflows into production-grade software that compresses a discovery cycle from years into weeks, accelerating the development of novel materials for next-generation wearable devices and robotics.
Automation Engineer, Materials Research Science Responsibilities:
  • Define the long-term technical roadmap for laboratory automation systems, integrating robotic sample handling, automated metrology instruments, and data acquisition pipelines
  • Architect and own the end-to-end automation infrastructure for high-throughput materials characterization workflows, including optical, mechanical, and electrical property testing of wearable device materials
  • Collaborate with scientists, hardware engineers, and product teams to translate experiments and lab workflows into clear integration specifications, data models, and scalable automation solutions
  • Work with integrators and vendors to design, build, and commission automated workcells for materials R&D (process development, characterization, property testing, etc.)
  • Build and maintain middleware services that connect instruments, robots, and sensors to laboratory information management systems
  • Develop instrument drivers and automation scripts that generate command sequences and invoke vendor APIs/SDKs to orchestrate lab workflows end-to-end
  • Collaborate with AI and data scientists to tightly integrate the autonomous lab with LLM-based multi-agent systems for experiment planning, analysis, and decision-making
  • Design and implement data pipelines that capture, validate, and store experimental metadata to ensure data integrity and reproducibility across the discovery pipeline
  • Evaluate and benchmark automation performance — measuring throughput, reliability, error rates, and turnaround time of automated experimental workflows
  • Contribute to internal tooling, documentation, and best practices that enable the broader team to leverage automation capabilities
  • Drive the adoption of design-of-experiments methodologies and statistical process control within automated materials screening workflows
  • Define standards and best practices for automation system reliability, calibration, and data integrity across the materials research organization
  • Provide technical guidance to other engineers on automation architecture decisions, instrumentation integration patterns, and software design for laboratory systems
  • Evaluate and integrate emerging laboratory automation technologies, robotics platforms, and scientific instrumentation relevant to materials research

Minimum Qualifications:
  • Ph.D. degree in Electrical Engineering, Computer Science, Mechanical Engineering, Control Engineering, Materials Science, or relevant field, and/or equivalent practical experience
  • 6+ years of experience in lab automation, systems integration, or industrial automation software and/or relevant technical experience
  • Proficiency in Python, with experience writing production-quality automation and integration code
  • Hands-on experience with lab automation platforms (e.g., liquid handlers, robotic arms, automated characterization tools)
  • Experience with laboratory information management systems, electronic lab notebooks, or manufacturing execution systems
  • Demonstrated ability to translate scientific or manufacturing workflows into reliable, automated processes
  • Experience architecting scalable automation platforms for materials characterization or physical science research environments
  • Experience with statistical analysis and data pipeline design for high-throughput experimental datasets

Preferred Qualifications:
  • A track record of commissioning or bringing up complex lab, pilot, or manufacturing equipment
  • Familiarity with APIs, databases, and enterprise software integration patterns
  • Experience defining automation strategy and technical standards at an organizational level within a research or advanced hardware development environment
  • Familiarity with computational chemistry or materials science tools (DFT, MD, LAMMPS, ASE) and high-performance computing (HPC) environments
  • Experience with retrieval-augmented generation (RAG), knowledge graphs, or scientific literature mining in the context of lab systems
  • Publications or demonstrated accomplishments recognized in the field of laboratory automation or materials informatics
  • Experience with materials relevant to wearables hardware, such as optical coatings, waveguide materials, display substrates, or flexible electronics
  • Experience integrating robotic platforms with laboratory information management systems (LIMS) or material databases
  • Experience integrating AI/ML models or LLM-based agent frameworks into physical lab workflows
  • Experience with data historians, or real-time supervisory dashboards
  • Knowledge of industrial communication protocols
  • Familiarity with design-of-experiments frameworks and machine learning approaches applied to accelerated materials discovery

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$184,000/year to $257,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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