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Freelance Computational Materials Science Jobs (NOW HIRING)

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 ...

Mat3ra

Computational Materials Scientist

Walnut Creek, CA · On-site +1

$90K - $140K/yr

Overview We look for computational materials scientists excited about bridging the gap between ... science to help us develop a software framework for designing and discovering new advanced ...

Mercor

Materials Scientist - AI Trainer

Los Angeles, CA · On-site +1

$1.1K - $1.4K/wk

Computational materials science expertise in DFT or MD . * Process development and scale-up experience. * Reliability and failure analysis in advanced materials. * Day-to-day use of VASP , Materials ...

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Freelance Computational Materials Science information

What is the difference between Freelance Computational Materials Science vs Freelance Materials Engineer?

AspectFreelance Computational Materials ScienceFreelance Materials Engineer
CredentialsBackground in materials science, physics, or chemistry; proficiency in computational toolsBackground in materials engineering, metallurgy, or related fields; practical experience in material testing
Work EnvironmentPrimarily remote, focused on simulations and modelingOften remote or on-site, involving testing, analysis, and design
Industry UsageUsed in research, development, and academia for modeling materials behaviorApplied in manufacturing, product development, and quality control

Freelance Computational Materials Science focuses on simulation and modeling of materials properties, while Freelance Materials Engineer emphasizes practical testing and application. Both roles require a strong background in materials science but differ in their approach and work environment.

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Infographic showing various Freelance Computational Materials Science job openings in the United States as of June 2026, with employment types broken down into 60% Full Time, and 40% Part Time. Highlights an 100% In-person job distribution.
Computational Materials Scientist

Computational Materials Scientist

SES

Woburn, MA • On-site, Remote

$180K - $200K/yr

Full-time

Medical

Posted 13 days ago

Job description

SES AI Corp. (NYSE: SES) is dedicated to accelerating the world's energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting-edge machine learning into our research and development. Our AI-enhanced, high-energy-density and high-power-density Li-Metal and Li-ion batteries are unique; they are the first in the world to utilize electrolyte materials discovered by AI. This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage, robotics, and drones.
To learn more about us, please visit: www.ses.ai
What We Offer:
  • 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.

What we Need:
The SES AI Prometheus team isseeking 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. This role is crucial for advancing our understanding of electrochemical energy materials at the atomic level. As a Computational Materials Scientist, you will be a core data-driven modeler responsible for executing and automating complex simulations.
Essential Duties and 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.
  • Collaboration & Tooling
  • 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.

Education and/or Experience:
  • Education: Ph.D. in Mechanical Engineering, Materials Science, Chemical Engineering, or a closely related computational/physics field.
  • Core Simulation Expertise: Deep and extensive experience in atomistic simulation and quantum modeling, including proficiency with key QM/DFT tools (VASP, Quantum Espresso) and MD simulations.
  • Domain Focus: Strong background in electrochemical energy materials and extensive computational work focused on batteries/fuel cells.
  • Coding Proficiency: Strong coding skills in Python (along with related libraries like Pandas and TensorFlow) for simulation workflow automation and data analysis.
  • ML Application: Experience in developing or utilizing ML-enhanced force fields and surrogate models for materials prediction., or equivalent practical experience.

Preferred Qualifications:
  • 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

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