ZipRecruiter

Log In

1

Computational Material Science Jobs in Berkeley, CA

Substrate

Research Scientist, AI

San Francisco, CA · On-site

$150K - $275K/yr

... and computational workflows * Develop AI-augmented tools for materials science, device physics, or accelerator physics applications * Build internal AI infrastructure and capabilities to enable ...

Arcadis

Computational Designer

San Francisco, CA · On-site +1

$24.25 - $29.50/hr

... materials to support projects Build quality relationships with team members and across the ... Science, Software Engineering, Hardware Engineering, or related fields (Master's Degree preferred ...

Periodic Labs

Research Scientist, Data

Menlo Park, CA · On-site

$250K - $350K/yr

Research experience in areas such as materials science, solid state chemistry, chemistry, computational physics, semiconductors Mechanics Minimum education: Bachelor's degree or similar experience ...

Periodic Labs

Research Scientist, Data

Menlo Park, CA · On-site

$250 - $350/hr

You will work with computational and experimental scientists to translate complex scientific ... Source, evaluate, and procure external datasets across chemistry, physics, materials science ...

Mat3ra

Community Evangelist

San Francisco, CA · On-site +1

$100K - $140K/yr

... materials science; MS or PhD in Engineering, Computational Chemistry, Computational Biology, Computer Science or Cheminformatics (or equivalent experience) * ability to learn and apply new concepts ...

previous pagenext page

Showing results 21-40

All JobsComputational Material Science JobsComputational Material Science Jobs in Berkeley, CA

Computational Material Science information

See Berkeley, CA salary details

$25.1K

$86.4K

$172.6K

How much do computational material science jobs pay per year?

As of Sep 6, 2026, the average yearly pay for computational material science in Berkeley, CA is $86,440.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,914.00 and $112,817.00 per year, depending on experience, location, and employer.

What is a computational material science?

A Computational Material Science job involves using computer simulations, modeling techniques, and data analysis to study and predict the properties of materials. Professionals in this field leverage methods like density functional theory (DFT), molecular dynamics, and machine learning to design new materials and optimize existing ones for various applications, including electronics, energy, and manufacturing. They often work in academia, research institutions, or industries such as aerospace, semiconductors, and pharmaceuticals. The role requires expertise in materials science, physics, chemistry, and programming, typically using tools like Python, MATLAB, or specialized simulation software.

What are typical daily tasks for a computational material science professional?

Daily tasks for a Computational Material Science professional often include developing and running computer simulations to investigate material properties, analyzing data from these simulations, and collaborating with experimental scientists to compare computational predictions with laboratory results. You may spend significant time programming, writing reports, and presenting your findings to colleagues or industry partners. You'll typically work within a multidisciplinary team, where clear communication and project coordination are crucial. The balance between independent computational work and collaborative meetings helps ensure innovative solutions to complex material challenges.

What are the key skills and qualifications needed to thrive in computational material science?

To thrive in Computational Material Science, you need a strong background in materials science, physics, and computational modeling, usually supported by an advanced degree such as a Master's or Ph.D. Proficiency with simulation software (like VASP, LAMMPS, or Quantum ESPRESSO), high-performance computing environments, and programming languages like Python or C++ is often required. Strong analytical thinking, problem-solving ability, and effective teamwork and communication skills help set professionals apart in this field. These skills are essential for designing, analyzing, and optimizing materials using computational techniques, often as part of collaborative, interdisciplinary research teams.

What jobs can I get with a computational material science degree?

A computational material science degree prepares individuals for roles such as materials scientist, computational researcher, or simulation engineer. These jobs often involve using modeling software, programming skills, and knowledge of materials properties to develop new materials or improve existing ones in industries like aerospace, electronics, and energy. Additional certifications or experience with tools like MATLAB, Python, or molecular dynamics software can enhance job prospects.

What are the most commonly searched types of Computational Material Science jobs in Berkeley, CA?

The most popular types of Computational Material Science jobs in Berkeley, CA are:

What are popular job titles related to Computational Material Science jobs in Berkeley, CA?

For Computational Material Science jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Computational Material Science jobs in Berkeley, CA look for?

The top searched job categories for Computational Material Science jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Computational Material Science jobs?

Cities near Berkeley, CA with the most Computational Material Science job openings:

Computational Material Science jobs near you
Infographic showing various Computational Material Science job openings in Berkeley, CA as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, and 3% Contract. Highlights an 77% Physical, 4% Hybrid, and 19% Remote job distribution, with an average salary of $86,440 per year, or $41.6 per hour.

Research Scientist, AI

Substrate

San Francisco, CA • On-site

$150K - $275K/yr

Full-time

Re-posted 21 days ago

Job description

Research Scientist, AI
Substrate is addressing one of the most important technological problems facing the United States. At the intersection of advanced manufacturing and cutting-edge physics, we are developing technologies that will reshape the semiconductor industry and strengthen America's technological leadership. We are a team of world-class scientists, engineers, and technical experts building technology for the United States.
Summary
As a Research Scientist working with AI, you will accelerate and augment R&D workflows by applying machine learning to scientific simulations and modeling while simultaneously building internal AI capabilities across the organization. This role sits at the intersection of cutting-edge physics and artificial intelligence, and you'll work hands-on to develop AI-augmented tools that enable breakthrough research, and build the infrastructure and expertise that empowers our technical teams to leverage AI in their own work. Whether you are a physicist who has embraced machine learning or an AI expert with deep scientific domain knowledge, you will play a pivotal role in defining how we utilize AI to accelerate our own internal R&D.
Responsibilities
  • Integrate machine learning techniques to accelerate scientific simulations, modeling, and computational workflows
  • Develop AI-augmented tools for materials science, device physics, or accelerator physics applications
  • Build internal AI infrastructure and capabilities to enable research teams across the organization
  • Train and mentor scientists and engineers on integrating AI/ML into their research workflows
  • Implement surrogate models, physics-informed neural networks, or generative approaches for scientific problems
  • Develop data pipelines and frameworks for scientific machine learning across distributed teams
  • Collaborate with computational physicists and experimentalists to identify high-impact AI applications
  • Set AI best practices and establish standards for ML-augmented R&D

Required Qualifications
  • 5+ years professional or academic research experience in physical sciences, engineering, or related field
  • 2-3+ years hands-on experience applying machine learning to scientific or technical problems
  • Strong programming skills in Python and ML frameworks (PyTorch, TensorFlow, JAX, or similar)
  • Deep understanding of scientific computing, numerical methods, and computational modeling
  • Proven ability to translate scientific problems into machine learning approaches
  • Experience building tools, infrastructure, or capabilities used by technical teams

Preferred Qualifications
  • PhD in Physics, Materials Science, Computer Science, Applied Mathematics, or related field
  • Publications applying ML to scientific computing, simulation, or experimental data analysis
  • Experience with physics-informed machine learning or scientific foundation models
  • Background in accelerator physics, semiconductor devices, materials modeling, or related domains
  • Track record of enabling technical teams through tool development or mentorship

Salary Range
$150,000-$275,000 USD
Substrate is an equal opportunity employer. It provides equal employment opportunity to all applicants without regard to race, color, religion, national origin, disability, medical condition, marital status, sex, gender, age, military or veteran status, or any other characteristic protected by applicable federal, state, or local laws.
Substrate will provide reasonable accommodations to applicants with disabilities. If you need an accommodation during the hiring process, please let your recruiter know.
Applicants must be legally authorized to work in the United States. This position is not eligible for visa sponsorship.

Apply