Postdoctoral Scholar: AI-Ready Environmental Data Automation

Berkeley Lab; Berkeley (CA); On-site; USD 73,000 - 100,000; Full time

Benefits offered by this job

Exceptional health benefits

Retirement benefits

Winter Holiday Shutdown

Parental bonding leave

Job summary

Lawrence Berkeley National Laboratory (LBNL) seeks a postdoctoral researcher to develop AI-ready data for ESS-DIVE. You will craft guidance beyond FAIR principles and build tools to validate datasets for AI readiness, while enabling automated preparation and transformation of legacy environmental data into consistent formats.

The role involves collaborating with ESS-DIVE users and the broader community, creating examples, documentation, and benchmarks to advance AI-ready data practices across

Qualifications

• Ph.D. in environmental science, earth science, informatics, or a closely related field.
• Experience working with environmental/scientific datasets (cleaning, processing, analysis, synthesis).
• Strong programming skills, especially Python (or comparable scientific programming).
• Experience with LLM-assisted or agent-based workflows.
• Strong written and oral communication skills, including the ability to explain technical requirements to non-experts.
• Demonstrated record of scholarly or technical contributions (e.g., publications, reports, or significant software contributions).

Responsibilities

• Define AI-ready data standards: establish and maintain metadata/formatting requirements for DOE environmental datasets.
• Build automated checks and tools: develop LLM-supported methods to assess AI readiness and convert datasets into usable formats.
• Drive training and adoption: create documentation, tutorials, and outreach to promote AI-ready data practices.
• Curate benchmark datasets: select, standardize, and document ESS-DIVE datasets for AI training/validation.
• Support automated workflows: contribute to agent-based pipelines that streamline data preparation, validation, and integration.

Skills

Python programming

LLM workflows

communication

Education

Ph.D. in environmental science or closely related field

Tools

HPC/data tools

Job description

Lawrence Berkeley National Laboratory (LBNL) seeks a postdoctoral researcher to develop AI-ready data for ESS-DIVE. You will craft guidance beyond FAIR principles and build tools to validate datasets for AI readiness, while enabling automated preparation and transformation of legacy environmental data into consistent formats.

The role involves collaborating with ESS-DIVE users and the broader community, creating examples, documentation, and benchmarks to advance AI-ready data practices across