Biology Life Sciences Problem Designer (Remote)

Aitrainer

San Francisco (CA)

Remote

USD 83,000 - 138,000

Full time

2 days ago
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Benefits offered by this job

Opportunity to work on cutting-edge AI
Competitive compensation
Flexible working hours and remote work

Job summary

Turing in San Francisco seeks Life Sciences Subject Matter Experts to design advanced scientific-reasoning tasks for LifeSciBench. This non-coding role emphasizes biological knowledge, experimental interpretation, data analysis, and rigorous reasoning.

You will craft challenging problems based on realistic research contexts, experimental results, data, figures, sequences, and literature-style evidence, focusing on synthesis over recall to differentiate advanced AI reasoning capabilities.

Qualifications

  • Ph.D., postdoctoral experience, or equivalent advanced research experience in the life sciences.
  • Strong ability to interpret scientific experiments, data, and research findings.
  • Strong scientific writing skills and attention to precision.

Responsibilities

  • Design novel, graduate-level life sciences problems grounded in realistic research contexts.
  • Develop clear questions and rigorous reference answers with defensible scientific reasoning.
  • Interpret experiments, datasets, figures, sequences, structures, and other biological evidence.
  • Validate biological claims, calculations, assumptions, and conclusions.
  • Identify ambiguity, alternative interpretations, and insufficiently constrained questions.
  • Ensure tasks are self-contained, reproducible where applicable, and clearly documented.
  • Incorporate reviewer feedback while maintaining quality and throughput.

Skills

Scientific interpretation
Scientific writing
Biology discipline expertise

Education

PhD or equivalent research experience
Postdoctoral experience

Job description

Turing in San Francisco seeks Life Sciences Subject Matter Experts to design advanced scientific-reasoning tasks for LifeSciBench. This non-coding role emphasizes biological knowledge, experimental interpretation, data analysis, and rigorous reasoning.

You will craft challenging problems based on realistic research contexts, experimental results, data, figures, sequences, and literature-style evidence, focusing on synthesis over recall to differentiate advanced AI reasoning capabilities.

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