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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
Apply for this position

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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