Inorganic Materials, Semiconductor & Superconductor Experts
Mercor · 100% remote · Contract · Posted
- Pay
- $84/hr
- Location
- United States
- Languages
- English
- Hours
- Up to 40 hours/week (minimum 10)
- Openings
- Not listed
- Level
- Expert
Summary
Generate and evaluate scientific data for AI models in materials science and semiconductors using hands-on experimental expertise. Review AI-generated reasoning, design problems, and structure technical knowledge into model-ready data.
What you'll do
- Contribute domain expertise across synthesis, characterization, fabrication, and device physics
- Review and evaluate AI-generated scientific reasoning
- Design and solve expert-level problems in your specialization
- Rate and rank model outputs against defined scientific criteria
- Structure technical knowledge into model-ready data
- Deliver reliable, high-quality work within defined timelines
Requirements
- Hands-on experimental experience in inorganic synthesis, superconductors, or semiconductors
- Strong materials or device characterization skills (XRD, SEM, TEM, spectroscopy, electrical/transport measurements)
- Experience with thin-film growth or device fabrication (MBE, MOCVD, CVD, sputtering, IBAD, etch, clean-room microfabrication) is a plus
- Advanced degree (PhD/MS) or equivalent hands-on experience in materials science, chemistry, physics, or related engineering field
- Clear written English and ability to explain technical reasoning concisely
Skills
- Inorganic Synthesis
- Superconductors
- Semiconductors
- XRD
- SEM
- TEM
- Spectroscopy
- Device Characterization
Full description
Mercor is seeking experimental scientists and engineers across inorganic synthesis, characterization, superconductors, and semiconductors (including advanced packaging) to support a frontier AI research lab building models for materials science and the physical sciences. This is hands-on, expert-level work: you'll apply deep, specialized knowledge to generate, structure, and evaluate the scientific data these models learn from — and your input will directly shape how advanced models reason about materials, devices, and processes.
Key Responsibilities:
Contribute domain expertise across synthesis, characterization, fabrication, and device physics to build high-quality training and evaluation data.
Review and evaluate AI-generated scientific reasoning, catching errors and improving technical accuracy.
Design and solve challenging, expert-level problems in your area of specialization.
Rate and rank model outputs against defined scientific criteria, with clear written reasoning.
Structure technical knowledge — experimental procedures, characterization results, process data — into well-organized, model-ready data.
Deliver reliable, high-quality work within defined timelines.
You're a strong fit if you have:
Hands-on experimental experience in one or more of: inorganic synthesis (solid-state, solution, solvothermal, sol-gel), superconducting materials, or semiconductors and advanced packaging.
Strong materials or device characterization skills (XRD, SEM, TEM, spectroscopy, electrical/transport measurements).
Experience with thin-film growth or device fabrication (MBE/epitaxy, MOCVD, CVD, sputtering, IBAD, etch, clean-room microfabrication) — a plus.
An advanced degree (PhD/MS) or equivalent hands-on experience in materials science, chemistry, physics, or a related engineering field.
Clear written English and the ability to explain technical reasoning concisely.
Role Details:
Type: Long-term, ongoing engagement
Engagement: Up to 40 hours/week (minimum 10)
Work arrangement: Remote (US-based)
Location: open to applicants in United States.
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