Biology PhD - Scientific Coder - AI Trainer

Mercor

San Diego (CA)

On-site

USD 69,000 - 103,000

Full time

5 days ago
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Job summary

Mercor is hiring PhD and Master's scientists to author AI evaluation tasks for a new benchmark in scientific computing. You will create original, executable research problems that today’s frontier models cannot solve, sourced from papers, datasets, or your own scenarios.

We expect depth in at least two subdomains like ecology, biochemistry, or genetics, and proficiency in Python or R with Docker/GitHub workflows.

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

Education

PhD in biology
Masters in biology/related field

Tools

Git/GitHub
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)
  • 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
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