Life Sciences Scientific Reasoning Task Designer

The work

You will create difficult but fair life sciences problems for evaluating AI systems. The work focuses on biological knowledge, experimental interpretation, data analysis, and careful scientific reasoning rather than coding.

You will turn realistic research scenarios into precise questions with defensible reference answers. Your work may involve experiments, datasets, figures, sequences, structures, and literature-style evidence.

• Design graduate-level life sciences questions grounded in realistic research contexts.
• Interpret experiments, datasets, figures, sequences, structures, and biological research evidence.
• Check biological claims, calculations, assumptions, and conclusions for accuracy.
• Identify ambiguity, competing interpretations, and questions that lack enough information.
• Keep tasks self-contained, reproducible when appropriate, and clearly documented.
• Use reviewer feedback while maintaining quality and throughput.

What it pays and takes

The pay rate is not provided in the listing. This is a remote contractor assignment for one month. The listing includes a 20+ hour weekly commitment, while the role details specify at least 40 hours per week and at least four hours of overlap with Pacific Time.

• Pay: Not provided.
• Engagement: Remote contractor assignment lasting one month.
• Time: At least 40 hours per week, with at least four hours overlapping Pacific Time; the listing also states 20+ hours per week.
• Language: English.
• Location: Worldwide and remote.
• Education or experience: Ph.D., postdoctoral experience, or equivalent advanced research experience in the life sciences.
• Expertise: Strong knowledge in at least one area such as molecular biology, genetics and genomics, cell biology, biochemistry, neuroscience, microbiology, immunology, ecology, structural biology, or pharmacology.
• Skills: Scientific experiment and data interpretation, precise scientific writing, careful review of assumptions, assessment of competing interpretations, and creation of self-contained questions.
• Helpful background: Graduate-level problem or assessment design, manuscript review, evaluation of AI-generated scientific responses, AI or machine learning evaluation datasets, peer-reviewed publications, or graduate teaching and mentoring.

How it works

Apply on OpenTrain with your resume and then complete the application on the hiring site.

About AI training work

AI training work uses human-written examples, reviews, and evaluations to help improve artificial intelligence systems. People with advanced scientific expertise are needed to create reliable tasks and judge whether AI reasoning is accurate, well supported, and complete.