19-2032.00
Materials Scientists
Research and study the structures and chemical properties of various natural and synthetic or composite materials, including metals, alloys, rubber, ceramics, semiconductors, polymers, and glass. Determine ways to strengthen or combine materials or develop new materials with new or specific properties for use in a variety of products and applications. Includes glass scientists, ceramic scientists, metallurgical scientists, and polymer scientists.
You're basically automation-proof
Safer than 11% of occupations we track
Disruption Vector
Hybrid Threat
Both AI software and physical automation threaten different aspects of this role, creating a compound risk from multiple directions.
Materials Scientists are seeing generative AI models trained on the Materials Project database and tools like Citrine Informatics accelerate materials property prediction and composition optimization—work that once required extensive experimental iteration. High-throughput computational screening is increasingly AI-driven. The irreplaceable human contributions are synthesis expertise, characterization of novel failure modes, and the iterative problem-solving when materials behave unexpectedly in real systems—skills that remain central through 2027.
Salary & Job Outlook
AI Risk Timeline
Projection model: Based on current AI capability growth rates. High-risk occupations are projected to see compounding automation pressure, while human-centric roles show slower risk accumulation. These are statistical projections, not guarantees.
Skills Analysis — AI Vulnerability
Similar Safe Careers
Materials Scientists is already low-risk. Explore similarly safe occupations:
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Materials Scientists
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I just checked if I'm cooked as a Materials Scientists 🤖 AI risk score: 1.7/10 — Low Risk "Congrats — you are delightfully robot-proof. Go touch some grass." Check yours 👇 https://amicooked-five.vercel.app/results/19-2032.00 #AmICooked #AI #FutureOfWork
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You're safer than 11% of all knowledge workers we track.
This analysis is for informational purposes only and is based on statistical models and academic research. It does not constitute career advice and is not a guarantee of future employment outcomes. AI impact varies significantly by employer, region, and individual circumstances. Learn about our methodology →