PhD-Level Computational Biologists at AuraOne Human Data Remote

Healing Strides Counseling; United States; Remote; USD 83,000 - 117,000; Part time

Job summary

AuraOne seeks PhD-level computational biologists to remotely review AI outputs in geospatial science, assess derivations, reproduce results, and document correct methods for training the modeling team. You will adjudicate disputes using textbooks and papers and maintain calibration through inter-rater scoring.

Ideal candidates have graduate-level training in geospatial science, publication experience, and the ability to reason clearly with cited sources.

Qualifications

• Graduate-level training or equivalent applied experience in geospatial science or a closely related field for PhD-Level Computational Biologists work.
• Hands-on experience publishing, teaching, or advising on the topic at a professional level.
• Clear written reasoning that cites methods, papers, or worked examples.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against current geospatial science methods, conventions, and prior work for PhD-Level Computational Biologists 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

Geospatial science

Python

Education

PhD-level training

Tools

Python

Job description

PhD-Level Computational Biologists is a remote review track for evaluating AI outputs across geospatial science reasoning, calculations, and research workflows. Reviewers grade derivations and assumptions, reproduce key results, and document the correct method so the modeling team can train on it.

Why this role matters

Geospatial science models live or die on whether their derivations actually hold up under scrutiny. AuraOne uses scientific specialists to grade outputs the way a peer reviewer would — checking assumptions, reproducing key steps, and capturing the right method alongside the wrong one.

Responsibilities

• Review AI outputs against current geospatial science methods, conventions, and prior work for PhD-Level Computational Biologists 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.

Qualifications

• Graduate-level training or equivalent applied experience in geospatial science or a closely related field for PhD-Level Computational Biologists work.
• Hands-on experience publishing, teaching, or advising on the topic at a professional level.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that cites methods, papers, or worked examples.
• Reliable async availability for at least 10 hours per week.

Example tasks

• Reproduce a geospatial science derivation from a model output and flag any algebraic or dimensional errors.
• Grade a model's literature summary against the cited papers and rate the citation quality.
• Adjudicate a disputed answer between two reviewers using textbook methods.
• Audit a 25-row batch for rubric consistency and report drift to the program lead.

Nice to have

• PhD, postdoc, or industry research experience in the topic area.
• Prior work reviewing AI-assisted research tooling and its failure modes.
• Multilingual fluency for non-English papers and corpora.

Skills

• Scientific reasoning
• Method validation
• Citation review
• Quantitative analysis
• Geospatial science
• Python

Work model

Remote - US-eligible. Remote · Independent specialist contractor. Employment type: CONTRACTOR. Applicants must be authorized to work from US.

Compensation

$60-85 / hr