Life Sciences Subject Matter Expert at Turing

Life Sciences Subject Matter Expert | Varies | Remote

About the Role

Turing is seeking Life Sciences Subject Matter Experts to design advanced scientific-reasoning tasks for LifeSciBench. This is a non-coding role focused on biological knowledge, experimental interpretation, data analysis, and rigorous scientific reasoning.

You will create challenging, objectively defensible problems based on realistic research scenarios, experimental results, biological data, figures, sequences, structures, and literature-style evidence. Tasks should test synthesis and interpretation rather than factual recall and help distinguish advanced AI reasoning capabilities.

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.

Required Qualifications

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

Relevant backgrounds include molecular biology, genetics and genomics, cell biology, biochemistry, neuroscience, microbiology, immunology, evolutionary biology, ecology, structural biology, biophysics, developmental biology, cancer biology, pharmacology, and related life sciences disciplines.

Preferred Qualifications

• Experience designing graduate-level problems, assessments, or research exercises.
• Experience reviewing scientific manuscripts or research.
• Ability to translate complex scientific concepts into precise, self-contained questions.
• Experience evaluating AI-generated scientific responses or working with AI/ML evaluation datasets.
• Peer-reviewed publications or graduate-level teaching and mentoring experience.

Schedule and Engagement

• Commitment: at least 8 hours per day, minimum 40 hours per week, with 4 hours of overlap with PST.
• Engagement type: Contractor assignment/freelancer (no medical/paid leave).
• Duration: 1 month.

The role offers competitive compensation, flexible working hours, and a remote work environment, with the opportunity to work on cutting-edge AI projects.

Important Note

This role does not involve programming or executing code. For coding-based or workflow-oriented opportunities, please explore GeneBench Pro, Agentic Life Sciences, or Terminal Bench Science.

Evaluation Process

• Job interest form.
• Assessment.
• Based on answers and scores, selected candidates are contacted to discuss pre-onboarding requirements.