AI-Driven Atomistic Materials Modeling Expert

Mercor; United States; Remote; USD 96,000 - 179,000; Full time

Job summary

Mercor is seeking Atomistic Materials Modelling Experts to support advanced AI research in computational materials science. You will work with DFT, MD and related atomistic techniques, reviewing AI-generated results and validating simulations while exploring surface phenomena and material properties.

Ideal candidates will have a PhD in a relevant field, hands-on experience with VASP/Quantum ESPRESSO, strong Python skills, and a track record in materials modelling and AI-driven discovery.

Qualifications

• PhD in Computational Materials Science or closely related field; exceptional MSc candidates considered.
• Hands-on experience with at least one of: DFT, AIMD, MD, Monte Carlo, or atomistic/materials modelling.
• Proficiency with one or more tools such as VASP, Quantum ESPRESSO, CP2K, GPAW, LAMMPS or similar.

Responsibilities

• 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.

Skills

DFT

AIMD

MD

Monte Carlo

Atomistic modelling

Python

Education

PhD in Computational Materials Science

Tools

VASP

Quantum ESPRESSO

CP2K

GPAW

LAMMPS

ASE/pymatgen

Job description

Mercor is seeking Atomistic Materials Modelling Experts to support advanced AI research in computational materials science. You will work with DFT, MD and related atomistic techniques, reviewing AI-generated results and validating simulations while exploring surface phenomena and material properties.

Ideal candidates will have a PhD in a relevant field, hands-on experience with VASP/Quantum ESPRESSO, strong Python skills, and a track record in materials modelling and AI-driven discovery.