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Verified partner opportunity

Life Sciences Subject Matter Expert

Pay listed by partner

TuringRemote · Country eligibility: check the official listingContract

About Turing

Is this a fit?

  • Ability to translate complex scientific concepts into precise, self-contained problems.

Apply on Turing

Complete your application with Turing. No HumanitApp account or fee.

What happens next

  1. Continue to the official listing and enter your application details; have your resume ready.
  2. Complete the role-specific screen or assessment requested by the partner.
  3. Confirm availability, location eligibility and work authorization if requested. The partner determines the exact process.

Last verified 2026-10-23

Exact listing verified. HumanitApp is independent from Turing and may receive a referral fee; the partner controls assessment and hiring.

Ready to continue?Life Sciences Subject Matter Expert

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Official role description

About Turing

Turing is one of the world's leading AGI infrastructure companies, working with frontier AI labs to accelerate model development through high-quality training data, evaluations, and engineering talent.

About the Role

We are seeking Life Sciences Subject Matter Experts to develop advanced scientific reasoning tasks for LifeSciBench. Unlike coding-focused benchmarks, this role emphasizes deep biological knowledge, scientific interpretation, and rigorous reasoning. You will create challenging questions based on realistic scientific scenarios, experimental results, biological data, figures, literature-style evidence, and research problems.

This is a non-code benchmark: tasks are not executed, and no programming is required. Who this is for. Life scientists who want to author rigorous scientific-reasoning problems with objectively defensible answers

no coding involved. If your strength is interpreting experiments, spotting ambiguity, and constructing questions that reward synthesis over recall, this is the fit. Who this isn't for. If you want to build tasks where agents write and execute code, see GeneBench Pro (genomics), Agentic Life Sciences (broad life-sciences workflows), or Terminal Bench Science (cross-STEM terminal tasks).

Key Responsibilities

Design novel, challenging life sciences problems requiring advanced scientific reasoning.

Create tasks grounded in realistic research scenarios, experiments, biological datasets, figures, sequences, structures, or scientific evidence.

Develop clear questions with well-defined and objectively defensible answers.

Write rigorous expert reference answers explaining the scientific reasoning required.

Ensure tasks require synthesis and interpretation rather than simple factual recall.

Validate all biological claims, calculations, assumptions, and conclusions.

Identify ambiguity, alternative scientifically valid interpretations, and insufficiently constrained questions.

Create tasks capable of distinguishing frontier AI models based on scientific reasoning ability.

Ensure outputs are clearly documented and reproducible where applicable. • Maintain high quality and throughput while incorporating reviewer feedback. Note on inputs: Tasks may involve scientific text, structured data, sequences, experimental results, and other scientific evidence depending on project requirements.

Qualifications Required

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. 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 or related disciplines

Preferred

Experience designing graduate-level scientific problems or assessments.

Strong familiarity with experimental design and interpretation.

Experience reviewing scientific manuscripts or research.

Ability to translate complex scientific concepts into precise, self-contained problems.

Experience evaluating LLM-generated scientific responses.

Bonus Points For

Publications in strong peer-reviewed journals or conferences.

Teaching or mentoring experience at the graduate level.

Experience with AI/ML evaluation datasets

Relevant skills

PhD BiologyBioinformatician / Computational Biologist

Compensation context

Compensation is not stated in the current feed. Confirm the rate and workload before accepting an assessment or project.

Qualification checklist

  • Ability to translate complex scientific concepts into precise, self-contained problems.

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Before you apply

Referral and application questions

How should I compare the listed pay?

Compensation is not stated in the current feed. Confirm the rate and workload before accepting an assessment or project.

Does Apply use a referral link?

Yes. The button opens the exact verified Turinglisting using the referral URL published for this role.

Is HumanitApp the employer?

No. HumanitApp independently curates the opportunity. The partner platform manages applications and hiring decisions.

Must I share my details here?

No. Choose the primary Apply action to continue directly without giving HumanitApp your name or email address.

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