Materials Science Expert

Skills

About this role

In this role, you'll apply advanced materials science and computational modeling expertise to help train next-generation AI systems through rigorous scientific simulation, analysis, and validation. You'll create and evaluate computational models of material structures, properties, processing, performance, and failure, execute simulations using programmatic workflows, and assess results for computational validity and physical accuracy. This opportunity is suited for materials scientists and engineers with strong structure-property knowledge, practical Python proficiency, and hands-on experience with computational materials or scientific simulation tools.

Materials Science Expert

Responsibilities

• Solve and validate computational materials-science and materials-engineering problems.
• Create material structures, atomic configurations, compositions, and solver-ready inputs.
• Model relationships between material composition, structure, processing, properties, and performance.
• Run atomistic, electronic-structure, molecular-dynamics, continuum, electrochemical, or related simulations.
• Use Python to generate inputs, automate calculations, conduct parameter sweeps, process results, and validate outputs.
• Analyze mechanical, thermal, electrical, chemical, structural, and electrochemical properties.
• Diagnose failed calculations, invalid structures, convergence issues, numerical instability, and incorrect physical assumptions.
• Compare computational results against experimental data, literature values, known properties, and expected physical trends.
• Review AI-generated solutions for scientific correctness and identify invalid assumptions, configurations, or conclusions.
• Develop reproducible reference solutions and objective verification methods.

Qualifications

• MS or PhD in Materials Science and Engineering, Metallurgy, or a closely related discipline; alternatively, MS or PhD in Mechanical or Chemical Engineering with substantial materials specialization.
• Strong understanding of materials behavior and structure-property relationships.
• Experience with computational materials modeling, simulation, characterization, or materials-focused engineering analysis.
• Practical proficiency with Python.
• Experience with at least one CLI-accessible, scriptable, configuration-based, or programmatic engineering or scientific tool.
• Ability to understand and justify modeling assumptions, parameters, approximations, and convergence criteria.
• Ability to distinguish computational failures from genuine physical behavior.
• Ability to clearly explain complex scientific reasoning and technical limitations.