Postdoc: Neuromorphic Materials & Device Physics

Sandia National Laboratories; Livermore (CA); On-site; USD 70,000 - 90,000; Full time

Benefits offered by this job

Flexible work arrangements

Relocation assistance

Generous vacation

Job summary

Sandia National Laboratories in Livermore, CA seeks a postdoctoral researcher to join the Materials Physics Department. The researcher will join a new project focused on connecting device physics to computer science applications as part of a large, multi-disciplinary project that spans multiple departments and institutions.

The role includes prototyping and testing new memory devices and discovering their physical properties for neuromorphic computing algorithms, including material synthesis and

Qualifications

• PhD in physics, electrical engineering, materials science, or a closely related field.
• Hands-on experience in electronic materials synthesis and properties measurement.
• Record of publications and presentations at peer-reviewed venues.

Responsibilities

• Synthesis of materials with sputter deposition and related methods.
• Clean room fabrication and device testing.
• Low and high temperature electronic transport measurements.
• Electrical testing of device structures in collaboration with the team.
• Present results at meetings and publish in peer-reviewed journals.

Skills

Synthesis of materials

Electronic properties measurement

Publications and presentations

Independent work

Education

PhD in physics, electrical engineering, materials science, or closely related field

Tools

Clean room fabrication

Electronic transport measurements

Job description

Sandia National Laboratories in Livermore, CA seeks a postdoctoral researcher to join the Materials Physics Department. The researcher will join a new project focused on connecting device physics to computer science applications as part of a large, multi-disciplinary project that spans multiple departments and institutions.

The role includes prototyping and testing new memory devices and discovering their physical properties for neuromorphic computing algorithms, including material synthesis and