Biology PhD - Scientific Coder

Obsidian

San Francisco (CA)

On-site

USD 96,000 - 138,000

Part time

14 days+
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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 author original, executable research problems that today's frontier models cannot solve.

Domains require depth in biology with focus on ecology, biochemistry, or genetics. You will source material, write prompts, build grading criteria, and calibrate against frontier models during a 6-week, part-time engagement starting immediately.

Qualifications

  • PhD in biology or closely related field.
  • Depth in at least two subdomains: ecology, biochemistry, genetics.
  • Proficiency in Python or R for scientific computing.
  • Experience with Git/GitHub and running code in Docker — authoring runs through PR 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

Ecology
Biochemistry
Genetics

Education

PhD in biology or related field

Tools

Python
R
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

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