Mercor
Atomistic & Surface Modeling Experts (Computational Materials & Catalysis)
$84 / hourRemote · US
Mercor is seeking computational scientists specializing in atomistic and surface modeling to support a frontier AI research lab building models for materials science and the physical sciences. This is hands-on, expert-level work: you'll apply deep, specialized knowledge to generate, structure, and evaluate the scientific data these models learn from — and your input will directly shape how advanced models reason about materials, surfaces, and chemical processes.
Key Responsibilities:
- Contribute domain expertise across first-principles and molecular simulation — electronic structure, surface and interface modeling, adsorption, and reaction energetics — to build high-quality training and evaluation data.
- Review and evaluate AI-generated scientific reasoning, catching errors and improving technical accuracy.
- Design and solve challenging, expert-level problems in atomistic and surface modeling.
- Rate and rank model outputs against defined scientific criteria, with clear written reasoning.
- Structure technical knowledge — simulation setups, methods, and results — into well-organized, model-ready data.
- Deliver reliable, high-quality work within defined timelines.
You're a strong fit if you have:
- Hands-on experience with atomistic modeling using first-principles or molecular methods (DFT, ab initio molecular dynamics, classical MD, or Monte Carlo).
- Experience modeling surfaces, interfaces, and adsorption or reaction phenomena (slab models, surface reconstructions, transition states, NEB, microkinetics).
- Experience modeling semiconductor-relevant materials, or a background in computational (heterogeneous) catalysis.
- Proficiency with standard tooling (e.g., VASP, Quantum ESPRESSO, CP2K, GPAW, LAMMPS, ASE, pymatgen).
- A PhD in materials science, chemistry, physics, chemical engineering, or a related field, ideally with several years of research experience beyond the PhD.
- Clear written English and the ability to explain technical reasoning concisely.