Atomistic Materials Modeling Expert

Overview

Mercor partners with leading AI labs to train frontier AI models using human expertise. This role involves evaluating and validating AI-generated answers in atomistic simulations and computational materials science, reviewing DFT calculations, molecular dynamics simulations, and materials property predictions.

What You’ll Do

• Evaluate advanced scientific problems involving atomistic simulations and computational materials science
• Review and validate AI-generated answers involving DFT calculations, molecular dynamics, and materials property predictions
• Assess the appropriateness of computational methods, simulation parameters, convergence criteria, and physical assumptions
• Analyse atomic structures, electronic properties, reaction energetics, diffusion mechanisms, and materials stability
• Evaluate surface and interface phenomena, adsorption energies, defect formation, and chemical reaction pathways
• Develop high-quality reference solutions, evaluation rubrics, and technically rigorous scientific explanations
• Identify computational inaccuracies, methodological limitations, and errors in scientific reasoning
• Apply computational expertise to improve AI performance on complex materials science problems

Requirements

• PhD in Computational Materials Science, Materials Science and Engineering, Computational Chemistry, Condensed Matter Physics, Chemical Engineering, or related field
• Demonstrated hands-on experience with at least one of: Density Functional Theory (DFT), Ab initio Molecular Dynamics (AIMD), Classical Molecular Dynamics (MD), Monte Carlo simulations, or atomistic/first-principles materials modelling
• Proficiency with computational tools such as VASP, Quantum ESPRESSO, CP2K, GPAW, LAMMPS, or similar software
• Strong understanding of electronic structure, interatomic interactions, thermodynamics, statistical mechanics, and materials properties
• Experience interpreting simulation results and validating computational predictions
• Strong Python skills for scientific computing, data analysis, or workflow automation