Review and analyze AI-generated Materials Science content using proprietary software and provide expert feedback
Ensure high-quality data curation to enhance AI model accuracy
Collaborate with technical teams to refine annotation tools and methodologies for Materials Science-related tasks
Evaluate AI-generated and human responses across biomaterials, nanomaterials, electronic materials, and structural materials
Interpret, analyze, and review tasks based on evolving guidelines
Participate in improving annotation rubrics and data quality for scientific education
Requirements
PhD in Materials Science or a closely related field (in progress or completed within the last 10 years)
Proficiency in materials characterization techniques, property analysis, and laboratory methodologies
Excellent communication and organizational abilities
Ability to make independent evaluations based on limited data
Passion for AI, scientific education, and technology
Personal device supporting Windows 10 or macOS Big Sur 11.0+ and reliable access to a smartphone
Must be able to work remotely in the USA (no visa sponsorship available)
Extra Credit: research experience with published work in reputable Materials Science journals; experience in AI-assisted education or tutoring; teaching experience; technical/science writing experience