🌍Materials Science Expert, Remote- Contract
Role Title: Materials Science Expert
Role Type: Contract
Location: Remote
Required Skills:
Technical Depth in a Subdomain
Engineering Judgment Under Constraints
Knowing When an Answer Is Wrong
Material-science
Opportunity Snapshot:
Commitment: Flexible - fits alongside your current role
Location: Fully remote
You’ll need: Master’s or PhD in materials science or a closely related field, plus principal-level industry experience or a faculty appointment
Your tasks: Build challenging technical problems from your own domain and define what makes an answer correct
You'll be working on:
The problems where the textbook answer isn’t enough, where the right approach depends on reading the constraints correctly, where a plausible-looking solution is quietly wrong. You’ll build those problems, provide the correct analysis, and define what separates a right answer from one that only looks
What you’ll do:
Design difficult technical problems from your own area - structure-property relationships, processing, characterization, failure analysis, computational materials - with realistic constraints and supporting data.
Provide the correct solution and walk through the reasoning that gets there.
Define objective criteria for correctness, so another expert reviewing the work would reach the same verdict.
Review problems built by other contributors for technical accuracy and soundness of method.
Flag problems that turn out to be ambiguous or ungradable rather than submitting them.
What we’re looking for:
Master’s or PhD in materials science, metallurgy, ceramics, polymer science, condensed matter physics, or a closely related field.
Principal, staff, or fellow-level experience in industrial or national lab research, or a faculty appointment at a leading university.
Deep technical depth in at least one materials subdomain, with hands-on ownership of the work.
Able to explain why an answer is correct clearly enough that another scientist could verify it.
Publications, patents, or a record of technical leadership is a strong plus.
AI or LLM evaluation experience is a plus, but not required.