Postdoc: ML for Materials & Data Infrastructure

Berkeley Lab; Berkeley (CA); On-site; USD 99,000 - 111,000; Full time

Job summary

Lawrence Berkeley National Laboratory is hiring a Postdoctoral Researcher - Machine Learning for Materials Science in the Molecular Foundry. The role focuses on developing data infrastructure and ML models for memristor materials, collaborating with Argonne and Oak Ridge on a DOE-funded project.

You will work in a multidisciplinary setting, publish results, and present at conferences. Appointment is full-time for 2 years with renewal possible and competitive salary.

Qualifications

• Ph.D. in a physics, chemistry, materials science or computer science related field.
• Experience with Python and ML methods for data analysis.
• Ability to organize technical information and publish results.

Responsibilities

• Develop data infrastructure to capture and curate experimental and simulation data.
• Build ML models to predict behavior of materials for memristors.
• Collaborate across multidisciplinary teams and present results.

Skills

Ph.D. in a relevant field

Python

Machine learning

Data analysis

Communication skills

Team collaboration

Education

Ph.D. in Physics, Chemistry, Materials Science, or CS

Job description

Lawrence Berkeley National Laboratory is hiring a Postdoctoral Researcher - Machine Learning for Materials Science in the Molecular Foundry. The role focuses on developing data infrastructure and ML models for memristor materials, collaborating with Argonne and Oak Ridge on a DOE-funded project.

You will work in a multidisciplinary setting, publish results, and present at conferences. Appointment is full-time for 2 years with renewal possible and competitive salary.