ESS-DIVE

Deep Insight for Earth Science Data

OPPORTUNITIES

Open Positions

AI-Readiness & Data Automation Postdoctoral Scholar

The Earth and Environmental Sciences Area at Lawrence Berkeley National Laboratory (LBNL) seeks a postdoctoral researcher to develop and curate unique and cutting-edge AI-ready data for the U.S. Department of Energy’s ESS-DIVE repository.

The DOE Biological and Environmental Research (BER) program produces uniquely valuable datasets increasingly used in AI/ML, but many are not AI-ready due to inconsistent formatting, missing metadata, or incompatible file types.

The selected candidate will join an interdisciplinary team to improve and expand upon how DOE environmental data is prepared for AI to further our understanding of Earth system processes and to enable environmental management. This includes working with ESS-DIVE users and the broader community to create machine-readable data products and develop tools and guidance for contributors.

The successful candidate will:

  • Develop practical guidance for what “AI-ready data” should include that extends beyond the FAIR (Findable, Accessible, Reusable, Interoperable) principles
  • Build and extend tools that validate datasets, and check whether they meet AI-readiness requirements.
  • Help automate dataset preparation using reporting format templates and structured workflows.
  • Enable translation of legacy DOE data into AI-ready formats, lead creation of example AI-ready benchmark datasets and supporting documentation.

You will:

  • Define AI-ready data standards: Establish and maintain guidance on metadata and formatting requirements for DOE environmental datasets.
  • Build automated checks and tools: Develop LLM-supported methods to assess AI readiness and convert datasets into consistent, usable formats.
  • Drive training and adoption: Create documentation, tutorials, and outreach to promote AI-ready data practices across the research lifecycle.
  • Curate benchmark datasets: Select, standardize, and document ESS-DIVE datasets for AI training and validation.
  • Support automated workflows: Contribute to developing agent-based pipelines that streamline data preparation, validation, and integration.

We are looking for:

  • 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).

For additional information and to apply to this position, please visit https://jobs.lbl.gov/jobs/ai-readiness-data-automation-postdoctoral-scholar-7461