Postdoc: AI-Driven Autonomous Semiconductor Research

National Renewable Energy Laboratory; Golden (CO); On-site; USD 77,000 - 126,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Pension benefits

403(b) plan with employer match

Paid holidays and PTO

Job summary

National Laboratory of the Rockies (NLR) seeks a postdoctoral researcher to develop autonomous experimentation for semiconductor materials, enabling closed-loop systems across synthesis and characterization instruments. The role integrates AI, robotics, and data infrastructure to accelerate discovery of advanced thin-film materials.

The candidate will work with superconducting and wide-bandgap materials teams, contribute to METALLIC platform goals, and engage in cross-disciplinary collaborations

Qualifications

• Must have recently completed a PhD within the last three years.
• Demonstrated hands-on proficiency in Python and scientific software development.
• Experience with software for scientific instrumentation and laboratory automation.

Responsibilities

• Design and deploy advanced algorithms and closed-loop workflows for autonomous experimentation on synthesis and characterization instruments.
• Integrate laboratory instrumentation, data infrastructure, and workflow orchestration systems into scalable autonomous platforms.
• Apply AI methods to accelerate materials discovery and characterization workflows.
• Collaborate with scientists and engineers to apply autonomous experimentation to multiple research projects.
• Troubleshoot instrumentation, automation hardware, and software interfaces with safety and procedures in mind.

Skills

Python

Git

Machine learning

Laboratory automation

Data workflows

Education

PhD in materials science or related field

Tools

SCPI

MBE/PLD/PVD

XRD/XRF

Job description

National Laboratory of the Rockies (NLR) seeks a postdoctoral researcher to develop autonomous experimentation for semiconductor materials, enabling closed-loop systems across synthesis and characterization instruments. The role integrates AI, robotics, and data infrastructure to accelerate discovery of advanced thin-film materials.

The candidate will work with superconducting and wide-bandgap materials teams, contribute to METALLIC platform goals, and engage in cross-disciplinary collaborations