Physics PhD - Quantum Computing Expert - AI Trainer

Mercor; New York (NY); On-site; USD 83,000 - 124,000; 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, collaborating with leading AI labs. You will author original, executable research problems that frontier models cannot solve.

Domains require depth in at least two subdomains with a coding focus. You'll use Python or similar, and work with GitHub and Docker to ensure runs pass automated quality checks.

Qualifications

• PhD in physics, applied physics, or a closely related field.
• Demonstrated depth in at least two subdomains: condensed matter, optics, quantum information/computing, computational physics, astrophysics, particle physics.
• Proficiency in Python, R, or another relevant programming language for scientific computing.
• Familiarity with Git/GitHub and running code in Docker with pull-request workflow and automated quality checks.

Responsibilities

• Source your own material: a published paper, Kaggle dataset, an open-source repository, or a self-designed scenario.
• Write scientific prompts based on the input.
• Build the grading criteria that define a correct answer.
• Calibrate against frontier models so tasks fail more often than they succeed.

Skills

Condensed matter physics

Quantum information/computing

Computational physics

Scientific problem design

Education

PhD in physics or closely related field

Tools

Git/GitHub

Docker

Jupyter

Job description

Mercor is hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code)

Mercor is partnering with leading AI labs on a new benchmark for scientific computing. You will author original, executable research problems that today's frontier models cannot solve.

Domains — depth required in at least two subdomains (with a coding focus)

• Physics — condensed matter, optics, quantum information/computing, computational physics, astrophysics, particle physics

What you'll do

• 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

Required

• PhD in physics, applied physics, or a closely related field
• Demonstrated depth in at least two of the following subdomains: condensed matter, optics, quantum information/computing, computational physics, astrophysics, particle physics
• Working proficiency in Python, R, or another relevant programming language for scientific computing
• Comfortable with Git/GitHub and running code in Docker — authoring runs through a pull-request workflow with automated quality checks

Preferred

• Publications in peer-reviewed journals
• Prior scientific software or research engineering experience

Engagement

• Duration: 6 weeks
• Commitment: part-time, 20+ hours per week
• Start date: immediate

Process

1. Upload your resume and application form
2. A 25-minute conversational interview covering your background, experience, and motivationsFollow up within a few days with next steps and onboarding