Applied Scientist, Materials Characterization and Simulations, Amazon Center for Quantum Computing

Amazon Amazon · Big Tech · Pasadena, CA · Research Science

This role focuses on materials science and computational modeling for quantum computing, specifically understanding and mitigating materials-driven loss mechanisms in superconducting quantum processors. It involves combining characterization and simulations to investigate material defects' impact on qubit performance, inputting into materials design, and developing simulation tools. The role supports fabrication teams and translates insights into process improvements, with potential for publication.

What you'd actually do

  1. You will combine materials characterization and numerical simulations to investigate how material defects affect qubit performance.
  2. This includes implementing multi-technique characterization workflows for thin films and interfaces, providing input on the design of materials with targeted properties, and developing computational tools for simulations of disordered structures.
  3. You will provide characterization support for the Fabrication team, investigating materials sources of loss in production-relevant films and processes.
  4. You will coordinate with cross-functional teams to translate materials insights into actionable process improvements, and publish results in scientific journals when appropriate.

Skills

Required

  • PhD in mechanical engineering, electrical engineering, material science, physics or equivalent
  • Expertise in materials characterization techniques
  • Experience with computational modeling of materials or disordered systems

Nice to have

  • Experience successfully delivering on projects as part of a cross-team collaboration
  • Proficient in a scientific programming environment
  • Expertise in superconductivity theory and sources of dissipation in superconducting quantum devices
  • Familiarity with thin-film deposition, surface preparation, or semiconductor fabrication processes
  • Track record of translating materials research into actionable process or design recommendations

What the JD emphasized

  • track record of original scientific contributions in experimental and computational studies of materials defects
  • Track record of translating materials research into actionable process or design recommendations