PhD Materials Scientist — AI Benchmarking in Modeling

Mercor; United States; Remote; USD 67,000 - 100,000; Part time

Job summary

Mercor is hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code) for a new benchmark in scientific computing. You will author original, executable research problems that frontier models cannot solve.

Domains—depth in at least two subdomains with a coding focus, including materials science and semiconductor materials; molecular modeling. Start date is immediate for this 6-week, part-time engagement at 20+ hours per week.

Qualifications

• PhD in materials science or closely related field.
• Demonstrated depth in semiconductor materials and molecular modeling.
• Working proficiency in Python, R, or another language for scientific computing.
• Comfortable with GitHub and running code in Docker — PR workflow with automated checks.

Responsibilities

• Source your own material: a published paper, a Kaggle dataset, an open-source repository, or a scenario you design.
• Write scientific prompts based on the input.
• Build the grading criteria that define a correct answer.
• Calibrate against frontier models — a task ships only when strong models fail it more often than they succeed.

Skills

Python

R

Scientific computing

Git/GitHub

Education

PhD in materials science

Master's in a related field

Tools

Docker

Git

Job description

Mercor is hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code) for a new benchmark in scientific computing. You will author original, executable research problems that frontier models cannot solve.

Domains—depth in at least two subdomains with a coding focus, including materials science and semiconductor materials; molecular modeling. Start date is immediate for this 6-week, part-time engagement at 20+ hours per week.