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Careers at Chai Discovery
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Scientist, Computational Biology

30 Jun 2025
San Francisco, CA, USA
Verified by Turrior

Content + Source + Freshness • 12 Dec 2025 • 95% confidence

85 / 100

Offer value

High value due to its cutting-edge tech applications in biology, strong demand for AI skills, and potential for innovative research.

  • Cutting-edge role in AI applications for biology.
  • Work in a multidisciplinary team.
  • Requires a PhD and strong technical skills.
Pros
  • Opportunity to work in a pioneering AI-driven company.
  • High relevance in the growing field of computational biology.
  • Collaborative environment with multidisciplinary teams.
Cons
  • PhD requirement may limit the candidate pool.
  • Possibly high-pressure working conditions due to project deadlines.
  • Limited information on compensation and benefits.

Who it's for

Experienced Researcher • In-office/Remote

Good fit
  • PhD holders in Computational Biology
  • Biological data analysts
  • AI researchers with a background in biology
Not recommended for
  • Candidates without a PhD
  • Those unfamiliar with programming and AI tools
  • Individuals seeking non-research roles

Motivation fit

Desire for innovative and impactful research.Passion for collaboration across scientific domains.Interest in utilizing AI for solving biological problems.

Key skills

Programming (Python or similar languages)Data analysis and modelingStakeholder communication
Score: 85/100 AI verified analysis

About the job

Position Overview:
The Applied AI/Bio Scientist will leverage Chai Discovery’s computational platform to explore novel applications of biologics. The role involves designing and running computational experiments, case studies, supporting partners, and effectively communicating results internally and externally.

Qualifications:

  • PhD in Computational Biology, Bioinformatics, or related fields.

  • Strong computational skills, including proficiency in Python or related languages.

  • Experience working with AI-driven biological modeling tools.

  • Excellent communication skills and ability to present scientific data.

  • Ability to work collaboratively in a multidisciplinary team.

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