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Internship Computational Materials Science Jobs (NOW HIRING)

Technical Product Manager

Woburn, MA · On-site +1

$200K - $225K/yr

This role requires deep literacy in computational materials science and AI4Science to coordinate strategy across our research, engineering, and materials teams. As the Technical Product Manager, you ...

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 ...

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Internship Computational Materials Science information

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

As of Jun 14, 2026, the average hourly pay for internship computational materials 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 materials science?

An internship in computational materials science is a temporary position, usually for students or recent graduates, where you gain hands-on experience using computer simulations and modeling to study and design materials. Interns typically work on research projects involving software tools to predict material properties, analyze data, or develop new materials. This experience provides valuable skills in programming, data analysis, and scientific research, which are essential for a career in materials science or related fields.

What is the difference between Internship Computational Materials Science vs Computational Materials Scientist?

AspectInternship Computational Materials ScienceComputational Materials Scientist
CredentialsEnrolled in or recent graduate of relevant degree programsAdvanced degree (Master's or Ph.D.) in materials science, physics, or related fields
Work EnvironmentAcademic or research labs, internships at industry companiesResearch and development teams in industry or academia
ResponsibilitiesAssisting with computational modeling, data analysis, learning industry toolsLeading projects, developing models, publishing research

Internship Computational Materials Science positions are entry-level, focused on learning and supporting ongoing projects, while Computational Materials Scientists are experienced professionals responsible for independent research and development in the field.

What types of projects can an intern expect to work on in a Computational Materials Science internship?

As a Computational Materials Science intern, you can expect to be involved in projects such as simulating material properties, analyzing large datasets from experiments, or developing and testing computational models. Interns often assist with software coding, data visualization, and running simulations using tools like Density Functional Theory (DFT) or molecular dynamics packages. Collaboration with other scientists and engineers is common, and you may contribute to research publications or presentations, providing valuable hands-on experience in both individual and team-based research settings.

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

To thrive as an intern in Computational Materials Science, you typically need a solid background in materials science, physics, or related fields, along with programming skills in languages such as Python or C++. Familiarity with computational tools like Density Functional Theory (DFT) software (e.g., VASP, Quantum ESPRESSO) and data analysis platforms is highly beneficial. Strong analytical thinking, attention to detail, and effective communication set candidates apart in collaborative research environments. These competencies enable interns to contribute meaningfully to simulations, data interpretation, and innovative materials research.
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What cities are hiring for Internship Computational Materials Science jobs? Cities with the most Internship Computational Materials Science job openings:
What are the most commonly searched types of Computational Materials Science jobs? The most popular types of Computational Materials Science jobs are:
What states have the most Internship Computational Materials Science jobs? States with the most job openings for Internship Computational Materials Science jobs include:
What job categories do people searching Internship Computational Materials Science jobs look for? The top searched job categories for Internship Computational Materials Science jobs are:
Infographic showing various Internship Computational Materials Science job openings in the United States as of June 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $40,174 per year, or $19.3 per hour.
Dislocation Analysis Computational Materials Science - Postdoctoral Researcher

Dislocation Analysis Computational Materials Science - Postdoctoral Researcher

LLNL

Livermore, CA

$123K/yr

Full-time

Retirement

Posted 28 days ago


Job description

Company Description

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability. 

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

Job Description


We have an opening for a Postdoctoral Researcher in the field of modeling of X-ray scattering for dislocation analysis in metals. You will be an integral member of an interdisciplinary team responsible for conducting and supporting research to model and simulate interactions between high-energy X-rays and crystalline defects in advanced metallic alloy materials. This role includes performing simulations of dislocation networks under various conditions, developing models of X-ray scattering associated with these microstructures, and developing new methods to quantitatively interpret experimental data. This position is in the Metallurgy and Advanced Microscopy group within the Materials Science Division.

You will 

  • Develop and validate a multiscale simulation framework for virtual X-ray diffraction in plastically deformed alloys.
  • Implement the framework in parallel simulation codes intended to run on LLNL supercomputers.
  • Design and conduct complex molecular and dislocation dynamic simulations to investigate deformation mechanisms in FCC and BCC alloys.
  • Develop a machine-learning based methodology to perform dislocation analysis from high energy X-ray diffraction patterns.
  • Develop and present written analyses and verbal briefings that capture and communicate research results as well as periodic progress reports.
  • Publish research results in peer-reviewed scientific or technical journals and present results at external conferences, seminars and/or technical meetings.
  • Perform other duties as assigned.
Qualifications
  • PhD in Materials Science, Condensed Matter Physics, Nuclear Engineering, Computational Science, Applied Math, or a closely related field.
  • Demonstrated experience in atomistic and/or dislocation simulation methods (e.g., Molecular Dynamics, Dislocation Dynamics, Crystal Plasticity)
  • Ability to independently develop massively parallelized codes using C/C++/Python and proficiency in high-performance computing environments.
  • Strong analytical and problem-solving skills.
  • Proficient verbal and written communication skills as reflected in effective presentations at meetings and a demonstrated strong publication record.
  • Initiative and interpersonal skills with desire and ability to work in a collaborative, multidisciplinary team environment.

Qualifications we desire 

  • Experience with multiscale modeling frameworks and integration of multiple simulation methods.
  • Familiarity with synchrotron high energy X-ray diffraction experiments and/or theory.
  • Experience in the design of algorithms, development of simulation codes, and their implementation and validation.
  • Familiarity with data-driven and machine-learning methods.

Pay Range

$123,048 Annually

Please note that the pay range information is a general guideline only. Many factors are taken into consideration when setting starting pay including education, experience, the external labor market, and internal equity.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.

Why Lawrence Livermore National Laboratory?

  • Included in 2026 Best Places to Work by Glassdoor!
  • Flexible Benefits Package
  • 401(k)
  • Relocation Assistance
  • Education Reimbursement Program
  • Flexible schedules (*depending on project needs)
  • Our values - visit https://www.llnl.gov/inclusion/our-values

Security Clearance

None required.  However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process.  This process includes completing an online background investigation form and receiving approval of the background check.  

National Defense Authorization Act (NDAA)

The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities.  The restrictions of NDAA Section 3112 apply to this position.  To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112.

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.  

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under "Find Your Job" of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. 

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.