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About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .
Contribute domain expertise in first-principles and molecular simulation . Focus on 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 . Catch errors and improve technical accuracy.
Design and solve challenging problems in atomistic and surface modeling .
Rate and rank model outputs against defined scientific criteria. Provide clear written reasoning.
Structure technical knowledge into well-organized, model-ready data. Include simulation setups , methods , and results .
Deliver reliable, high-quality work within defined timelines.
Qualifications Must-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.
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