Biology PhD - Scientific Coder

Mercor; Greater London; On-site; GBP 4,959,000 - 6,612,000; Part time

Job summary

Mercor is hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code). You will author original, executable research problems that today's frontier models cannot solve.

Domains require depth in at least two subdomains with a coding focus. You will source your own material, write prompts, and build grading criteria, calibrating against frontier models. Engagement runs 6 weeks part-time, with immediate start.

Qualifications

• PhD in biology, biological sciences, biochemistry, genetics, ecology, or a closely related field
• Demonstrated depth in at least two of ecology, biochemistry, genetics
• 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

Scientific computing

GitHub

Docker

Education

PhD in biology or related field

Master's in related field

Tools

Docker

GitHub

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)

• Biology — ecology, biochemistry, genetics

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 biology, biological sciences, biochemistry, genetics, ecology, or a closely related field
• Demonstrated depth in at least two of the following subdomains: ecology, biochemistry, genetics
• 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. A 25-minute conversational interview covering your background, experience, and motivations
2. Follow up within a few days with next steps and onboarding