Remote Life Sciences Reviewer: Wet Lab & Computational Bio

AuraOne; United States; Remote; USD 136,000 - 194,000; Full time

Job summary

AuraOne is seeking a PhD Life Sciences Reviewer - Wet Lab & Computational Biology for a remote, US-eligible contractor role. You will evaluate AI outputs in biology reasoning, reproduce key results, and document the correct method so the modeling team can train on it.

Responsibilities include reviewing against established biology methods, reproducing derivations, flagging errors, and maintaining reviewer-quality scores.

Qualifications

• PhD Life Sciences reviewer with wet lab and computational biology evaluation experience.
• Experience publishing, teaching, or advising on the topic at a professional level.
• Ability apply multi-page rubrics consistently across long batches.
• Clear written reasoning citing methods, papers, or worked examples.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against current biology methods, conventions, and prior work for PhD Life Sciences Reviewer - Wet Lab & Computational Biology assignments.
• Reproduce or sanity-check key derivations, calculations, or experimental claims.
• Flag dimensional, methodological, and citation errors with structured severity tags.
• Capture the corrected reasoning or worked example so the modeling team can train on it.
• Adjudicate disputed answers against textbooks, papers, or community standards.
• Maintain reviewer-quality scores in inter-rater calibration cycles.

Skills

Scientific reasoning

Method validation

Citation review

Quantitative analysis

Biology

Education

PhD in Life Sciences

Graduate-level biology training

Job description

AuraOne is seeking a PhD Life Sciences Reviewer - Wet Lab & Computational Biology for a remote, US-eligible contractor role. You will evaluate AI outputs in biology reasoning, reproduce key results, and document the correct method so the modeling team can train on it.

Responsibilities include reviewing against established biology methods, reproducing derivations, flagging errors, and maintaining reviewer-quality scores.