Computational Materials Scientist

NextGenEnergyJobs; Woburn, Northern (MA, KY); Hybrid; USD 180,000 - 200,000; Full time

Benefits offered by this job

Health coverage

Equity/stock options program

Job summary

NextGenEnergyJobs is seeking a Computational Materials Scientist to merge physics-based simulation (DFT/MD/QM) with AI-driven material prediction for accelerated discovery in energy tech.

You will generate training data, develop ML-enhanced force fields, and collaborate with experimental teams to validate models while advancing battery materials and related domains.

Qualifications

• Experience in developing battery domain LLM features or property-prediction models.
• Hybrid computational + experimental environment experience.
• Proficiency with atomistic simulations and data analysis tools.

Responsibilities

• Atomistic modeling & simulation of battery components (DFT/MD/QM).
• Develop ML-enhanced force fields and surrogate models to accelerate simulations.
• Generate high-quality, structured simulation data for AI property prediction models.
• Collaborate with experimental teams to validate models and drive design iteration.
• Automate complex simulation workflows with robust coding practices.
• Utilize VASP/Quantum Espresso and data science libraries to manage large datasets.

Skills

LLM Development

Hybrid Experience

Data analysis tools

Battery modeling

Tools

VASP

Quantum Espresso

TensorFlow

Pandas

MATLAB

SQL

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.