Material Sciences - Graduates - AI Training

Material Sciences - Graduates - AI Training - US

Remote

We’re looking for Materials Science Specialists to join our Expert Network to help train and evaluate cutting‑edge AI models using real scientific expertise. If you have a background in materials research, engineering, or technical analysis, we’ll send you a quick 10‑to‑15 minute test to assess your skills and suitability for AI tasks. If successful, you’ll be invited to join Prolific as a participant, where you’ll get paid to train and evaluate powerful AI models.

Researchers looking for your skills tend to pay $40+/hr, depending on skills and experience level
. You must be prepared to complete paid tasks that require one hour of uninterrupted work
, though many are shorter.

• Educational Background: at minimum, a BSc (Bachelor of Science) in Materials Science
  , Metallurgy, Chemical Engineering, or a closely related STEM field.
• Technical Literacy: deep interest or experience in materials research, including the ability to interpret phase diagrams, crystalline structures, and property data.
• Analytical Rigor: strong attention to detail and the ability to concentrate on complex technical tasks for extended periods.
• Professional Verification: a valid Linked In profile or professional history to verify your credentials during the screening process.
• A Pay Pal account to receive payment from our clients

• AI Evaluation & Ranking: comparing multiple AI-generated technical explanations or research summaries and ranking them based on scientific accuracy and logic.
• Strategic Document Audit: reviewing Materials Science scientific papers alongside AI-generated graphical abstracts to identify inaccuracies or misrepresentations.
• Fact‑Checking: verifying that the AI-generated data (formulas, material properties, and experimental results) faithfully represent the source scientific documentation.
• Model Alignment: providing high‑level feedback to help AI models produce “enterprise‑ready” corporate and scientific intelligence.
• Technical Verification: auditing the structural integrity of summaries involving complex chemical compositions and material behaviors.

• Generative AI (LLMs): training and fine‑tuning models specialized in STEM and corporate intelligence.
• Scientific Visualization: evaluating AI-generated graphical abstracts and data visualizations.
• Research Databases: navigating technical literature to provide “ground truth” data.