Physics PhD - Scientific Computing Expert - AI Trainer

Mercor; Dallas (TX); 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. You will author original, executable research problems that today’s frontier models cannot solve.

Source material, write prompts, build grading criteria, and calibrate against frontier models so a task ships only when strong models fail it more often than they succeed.

Engagement lasts 6 weeks, part-time (20+ hours per week) with start date available immediately.

Qualifications

• PhD in physics, applied physics, or a closely related field.
• Demonstrated depth in two or more of: 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.

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

GitHub

Education

PhD in physics

Master's in physics (or related field)

Tools

Docker

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 motivations

3. Follow up within a few days with next steps and onboarding