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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

NextGenEnergyJobs

Woburn, MA • On-site

$180 - $200/hr

Other

Medical

Posted 10 days ago

Job description

The SES AI Prometheus team is seeking an exceptional Computational Materials Scientist to combine physics-based simulation (DFT, MD, quantum modeling) with AI-assisted material prediction to generate high-quality training data and accelerate materials discovery.

Key Responsibilities
  • Atomistic Modeling & Simulation
  • Conduct and oversee DFT (Density Functional Theory), MD (Molecular Dynamics), and QM (Quantum Mechanics) simulations of battery components, including electrolytes, coatings, and electrodes.
  • Develop and refine ML-enhanced force fields and surrogate models to accelerate simulation time scales and enable multi-scale simulation efforts.
  • Apply expertise in atomistic simulation and quantum modeling to solve key challenges in electrochemical energy materials (e.g., batteries/fuel cells).
  • AI Data Generation & Prediction
  • Generate high-quality, structured simulation data to serve as training sets for AI property prediction models and material screening modules.
  • Contribute to the development of battery domain LLM features and advanced property-prediction models.
  • Automate complex simulation workflows using strong coding practices to enhance efficiency and scalability.
  • Collaborate with experimental teams, leveraging a hybrid computational + experimental literacy to validate models and drive design iteration.
  • Utilize advanced simulation tools (VASP, Quantum Espresso) and data science libraries (TensorFlow, Pandas) to manage and analyze large datasets.
Requirements
  • LLM Development: Experience in developing battery domain LLM features or property-prediction models.
  • Hybrid Skillset: Demonstrated experience working in a hybrid computational + experimental environment.
  • Tooling Diversity: Familiarity with additional data analysis tools like R, SQL, MATLAB, and time-series forecasting libraries like Prophet.
  • Target Background: Previous experience at national laboratories, XtalPi, Entalpic, or deep battery modeling groups.
  • The salary range for this position as required under applicable pay transparency laws.
  • Salary Range
  • $180,000
  • —
  • $200,000 USD
  • A highly competitive salary and robust benefits package, including comprehensive health coverage and an attractive equity/stock options program within our NYSE-listed company.
  • The opportunity to contribute directly to a meaningful scientific project—accelerating the global energy transition—with a clear and broad public impact.
  • Work in a dynamic, collaborative, and innovative environment at the intersection of AI and material science, driving the next generation of battery technology.
  • Significant opportunities for professional growth and career development as you work alongside leading experts in AI, R&D, and engineering.
  • Access to state-of-the-art facilities and proprietary technologies are used to discover and deploy AI-enhanced battery solutions.
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