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Bioinformatics PhD - Genomics Specialist - AI Trainer

Role overview

Qualifications

  • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience)
  • Proven proficiency with at least one of the listed scientific software libraries
  • Strong Python skills
  • Ability to work independently and refine problem designs

Responsibilities

  • Design challenging computational problems to evaluate AI capabilities in scientific research
  • Create problems requiring skilled use of specialized scientific software like scanpy, scvelo, squidpy, and gudhi
  • Test and refine problems against state-of-the-art AI models to achieve target difficulty
  • Develop problems that require strategic planning and efficient narrowing of possibilities

Key facts

Other skills

  • Strategic Planning

About the company

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Mercor

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Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Bioinformatics & Computational Single-Cell Genomics Expert
Type: Contract
Compensation: $70–$100/hour
Location: Remote
Commitment: 15–20 hours/week

Role Responsibilities

  • Design challenging computational problems to evaluate AI capabilities in scientific research.
  • Create problems requiring skilled use of specialized scientific software like scanpy, scvelo, squidpy, and gudhi.
  • Test and refine problems against state-of-the-art AI models to achieve target difficulty.
  • Develop problems that require strategic planning and efficient narrowing of possibilities.
  • Work independently to refine problem designs based on feedback.

Qualifications

Must-Have

  • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
  • Proven proficiency with at least one of the listed scientific software libraries.
  • Strong Python skills.
  • Ability to work independently and refine problem designs.
  • Comfortable working in a Linux/terminal environment.

Preferred

  • Experience across multiple listed domains or tools.
  • Familiarity with benchmark or evaluation design.
  • Background in scientific teaching or exam/problem-set design.
  • Experience with computational reproducibility and containerized environments.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.



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