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From Home Computational Materials Science Jobs (NOW HIRING)

Entegris, Inc.

$101 - $126/hr

## Senior Scientist, Computational Materials SolutionsApplylocations: Remote, PAtime type: Full ... This role focuses on accelerating innovation by combining computational science, machine learning ...

Mat3ra

Computational Materials Scientist

Walnut Creek, CA · On-site

$90K - $140K/yr

... science to help us develop a software framework for designing and discovering new advanced ... Work From Home * Free Food & Snacks * Wellness Resources * Stock Option Plan Compensation * $90,000 ...

Mat3ra

Computational Materials Scientist

Walnut Creek, CA · On-site +1

$90K - $140K/yr

... science to help us develop a software framework for designing and discovering new advanced ... Work From Home * Free Food & Snacks * Wellness Resources * Stock Option Plan Compensation * $90,000 ...

Mat3ra

Computational Materials Scientist

Walnut Creek, CA · On-site

$90 - $140/hr

Excellent knowledge of chemistry/materials science (Ph.D. from a tier-1 lab) * Prior work on ... Work From Home * Free Food & Snacks * Wellness Resources * Stock Option Plan Compensation * $90,000 ...

SES

Computational Materials Scientist

Woburn, MA · On-site +1

$180K - $200K/yr

This powerful combination of "AI for science" and material engineering enables batteries that can ... As a Computational Materials Scientist, you will be a core data-driven modeler responsible for ...

NextGenEnergyJobs

$180 - $200/hr

The SES AI Prometheus team is seeking an exceptional Computational Materials Scientist to combine ... Utilize advanced simulation tools (VASP, Quantum Espresso) and data science libraries (TensorFlow ...

Amat

AI Materials Research Engineer

Santa Clara, CA · On-site

$170K - $234K/yr

... work, at home, or wherever you may go. Learn more about our benefits. Role Summary Applied ... MS/PhD in Materials Science, Computational Materials Science, Physics, Chemical Engineering, or ...

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All Jobscomputational materials science Jobsremote JobsFrom Home Computational Materials Science Jobs

From Home Computational Materials Science information

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$142.5K

$168.8K

$192.5K

How much do from home computational materials science jobs pay per year?

As of Sep 4, 2026, the average yearly pay for from home computational materials science in the United States is $168,844.00, according to ZipRecruiter salary data. Most workers in this role earn between $155,500.00 and $182,000.00 per year, depending on experience, location, and employer.

What is a from home computational materials science job?

A 'From Home Computational Materials Science' job involves conducting research, simulations, and data analysis related to materials science using computer-based methods, all while working remotely. Professionals in this field use software to model the properties and behaviors of materials, predict new material structures, and optimize material performance for various applications. These roles often require a strong background in physics, chemistry, programming, and computational modeling, and they allow scientists and engineers to contribute to research projects without needing to be physically present in a laboratory or office setting.

What are the key skills and qualifications needed to thrive as a remote computational materials scientist?

To thrive as a remote Computational Materials Scientist, you need a strong background in materials science, physics, or chemistry, typically supported by an advanced degree (MS or PhD) and expertise in computational modeling. Proficiency in programming languages such as Python or C++, experience with simulation software (e.g., VASP, LAMMPS), and familiarity with high-performance computing environments are essential. Strong problem-solving abilities, self-motivation, and effective communication skills help you collaborate virtually and manage independent research. These skills and qualities are crucial for conducting complex simulations, publishing research, and contributing to interdisciplinary teams in a remote work setting.

How do remote computational materials scientists typically collaborate with experimental teams and other researchers?

Remote computational materials scientists often work closely with experimentalists, data scientists, and other researchers through virtual meetings, shared cloud-based platforms, and collaborative tools like version control systems. Regular video conferences and clear documentation are essential for staying aligned on project goals and integrating computational findings with experimental results. While working from home offers flexibility, it also requires strong communication skills to ensure successful interdisciplinary collaboration and timely project delivery.

What is the difference between From Home Computational Materials Science vs Computational Materials Engineer?

AspectFrom Home Computational Materials ScienceComputational Materials Engineer
CredentialsTypically requires a PhD or Master's in Materials Science, Physics, or related fieldsRequires a degree in Materials Science, Engineering, or related disciplines; often a Master's or PhD
Work EnvironmentPrimarily remote, using computer simulations and modeling softwareUsually in-office or hybrid, combining lab work and computer modeling
Industry UsageUsed in research, academia, and some R&D departmentsCommon in manufacturing, R&D, and product development sectors

From Home Computational Materials Science focuses on remote research and simulation work, while Computational Materials Engineer often involves hands-on engineering and on-site collaboration. Both roles require advanced degrees and involve modeling, but differ in work environment and application.

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From Home Computational Materials Science jobs near you
Infographic showing various From Home Computational Materials Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, and 3% Contract. Highlights an 79% Physical, 1% Hybrid, and 20% Remote job distribution, with an average salary of $168,844 per year, or $81.2 per hour.

Computational Materials Scientist

Discovery 2 Scale

Santa Fe, NM • On-site

$110 - $150/hr

Other

Medical, Retirement

Posted 16 days ago

Job description

Discovery 2 Scale is building the Autonomous Foundry for Advanced Materials—an end-to-end platform connecting materials design, autonomous experimentation, qualification, and scale-up to deliver production-ready materials faster and with less risk.

We are looking for a highly skilled computational materials scientist with strong CALPHAD and Thermo-Calc experience to help build the thermodynamic intelligence behind our platform.

What you’ll do
  • Develop CALPHAD and Thermo-Calc workflows for alloy design and high-throughput screening.
  • Model phase stability, solidification, segregation, and phase transformations.
  • Perform Scheil and kinetic simulations to evaluate manufacturability and processing windows.
  • Develop models for weldability, heat-affected-zone behavior, and thick-section producibility.
  • Build automated Python and Thermo-Calc pipelines for large composition and processing spaces.
  • Integrate thermodynamic predictions with AI/ML models and experimental data to guide alloy design.
Required qualifications
  • M.S. or Ph.D. in Materials Science, Metallurgy, Computational Materials Science, or a related field.
  • Hands-on experience with Thermo-Calc and CALPHAD.
  • Experience modeling multicomponent metallic alloy systems.
  • Experience with equilibrium phase and Scheil solidification calculations.
  • Strong understanding of physical metallurgy, thermodynamics, solidification, and phase transformations.
  • Experience with scientific programming or workflow automation using Python or similar tools.
  • Ability to connect computational predictions with real materials processing and experimental observations, and work independently in a fast-paced startup environment.
Preferred qualifications
  • Experience with TC-Python, DICTRA, TC-PRISMA, or related thermodynamic and kinetic modeling tools.
  • Experience with steels, nickel-based alloys, titanium or refractory alloys, or multi-principal-element alloys.
  • Experience with welding metallurgy, HAZ transformations, solidification, segregation, or casting.
  • Experience integrating CALPHAD predictions with SEM, EDS, EBSD, or other experimental data.
  • Experience combining CALPHAD with machine learning, materials informatics, or high-throughput alloy design.
Why join D2S?
  • Build cutting-edge autonomous materials discovery technology.
  • Work alongside world-class scientists and engineers.
  • High level of ownership and technical freedom.
  • Opportunity to help build a company from the ground up.
  • Competitive salary, comprehensive health benefits, and a 401(k) with company match.
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