Evaluate AI-generated educational reports, curriculum materials, lesson resources, and school-related presentations using professional education and school administration expertise.
Students Across All Disciplines (Undergrad, Grad)
Remote (Global)
$50 – $150/hr
June 9, 2026
Job description
This is a remote, project-based opportunity for currently enrolled graduate students and strong senior undergraduates across academic disciplines to contribute to AI evaluation research projects.
Participants will apply their domain expertise to evaluate, write, and validate content that requires genuine subject-matter knowledge derived from coursework, lab work, or field research.
Work is asynchronous and flexible, allowing students to integrate projects around academic schedules.
Key Responsibilities
Evaluate, write, and validate content requiring expert knowledge in your field
Assess materials for:
- Accuracy
- Depth
- Quality
Identify errors, ambiguities, or gaps not visible to non-expert reviewers
Provide structured written rationale and feedback for each evaluation
Interpret and respond to visual or diagrammatic content such as:
- Schematics
- Spectra
- Maps
- Clinical images
- Artworks
- Data charts
Complete assigned annotation tasks within each project window (~10–20 hours/week)
Required Skills & Qualifications
Currently enrolled in:
- PhD, Master’s, MD, or MD/PhD program
- OR senior undergraduate at a research university with strong academic standing
Ability to produce clear, well-reasoned written explanations of domain-specific judgments
Deep familiarity with visual conventions and technical vocabulary in your discipline
Reliable internet access and availability for remote, asynchronous work
Strong proficiency in English writing
Preferred Qualifications
- PhD Year 2+ or MD/PhD students with completed qualifying exams or clinical rotations
- Active research experience with visual or image-based data (microscopy, imaging, diagrammatic modeling, CAD, GIS, spectroscopy, archival materials)
- Prior experience in annotation, data labeling, or AI evaluation
- Affiliation with a top research university or program
- Familiarity with AI tools, large language models, or multimodal systems
- Quantitative methods training relevant to science, social science, business, or engineering
Additional Information
This role provides students with an intellectually engaging opportunity to contribute domain expertise toward AI model evaluation and improvement, building a strong addition to research and professional portfolios.
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