AI-Driven Atomistic Materials Scientist

Mercor; San Francisco (CA); Remote; USD 120,000 - 180,000; Part time

Job summary

Mercor is recruiting Atomistic Materials Modelling Experts with strong backgrounds in computational materials science, quantum mechanical simulations, and molecular modelling to support advanced AI research. Experts will evaluate technically demanding problems involving atomistic simulations, materials properties, computational methodologies, and scientific reasoning.

The ideal candidate has extensive hands-on experience with density functional theory (DFT), molecular dynamics (MD), and other

Qualifications

• PhD in Computational Materials Science, MSE, Computational Chemistry, Condensed Matter Physics, Chemical Engineering, or closely related field.
• Hands-on experience with DFT, AIMD, MD, Monte Carlo, or atomistic/first-principles modelling.
• Proficiency with 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.

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

Python

Data analysis

Workflow automation

Scientific computing

Education

PhD in Computational Materials Science

MSc with substantial relevant experience

Tools

VASP

Quantum ESPRESSO

CP2K

GPAW

LAMMPS

Job description

Mercor is recruiting Atomistic Materials Modelling Experts with strong backgrounds in computational materials science, quantum mechanical simulations, and molecular modelling to support advanced AI research. Experts will evaluate technically demanding problems involving atomistic simulations, materials properties, computational methodologies, and scientific reasoning.

The ideal candidate has extensive hands-on experience with density functional theory (DFT), molecular dynamics (MD), and other