Postdoctoral Research Scientist, Ocean CDR Atlas

Job Description

Job Description

About [C]Worthy

[C]Worthy is a non-profit research organization focused on  transforming research-grade oceanographic models into open, reproducible, and auditable decision-support tools for ocean-based carbon dioxide removal (CDR). Our mission is to deliver trustworthy, science-backed tools for Monitoring, Reporting, and Verification (MRV)—enabling governments, communities, and markets to make high-stakes ocean decisions grounded in transparent, scientifically credible evidence.

We are building three interlocking open-science capabilities: C-Star, an open-source modeling platform that systematizes regional ocean model configuration, execution, and evaluation through versioned inputs, automated workflows, and comprehensive provenance tracking; the C-Star Ocean Network (C-SON), a growing constellation of standardized regional modeling domains designed to support consistent CDR accounting across sites and regions; and the Ocean CDR Atlas, an open dataset library and web tools that map CDR performance, connectivity, and risk drivers across ocean regions—providing the basis for low-cost MRV evaluation and standard-setting worldwide.

These capabilities are not CDR tools alone—they are the foundation for scalable ocean science. Robust shared infrastructure makes knowledge transferable and auditable: once validated domains, standardized workflows, and reusable tooling are in place, the marginal cost of each additional application falls and the benefits of research innovation can flow across a network of projects and regions. We aspire to democratize access to sophisticated ocean information tools, empowering diverse scientific communities to participate in ocean governance and marine resource management on their own terms.

[C]Worthy is headquartered in Boulder, Colorado.

We are seeking a Postdoctoral Research Scientist to work with our team on the development of a high-resolution Ocean CDR Atlas dataset for the West Coast of North America. This dataset will provide a library of uptake efficiency kernels enabling MRV quantification for OAE deployments across the eastern Pacific without requiring new model runs for each scenario—dramatically lowering the modeling burden for individual project MRV and providing a broadly accessible reference for market standards, accounting frameworks, permitting and regulatory decision making, public communication, and research applications.

The Atlas simulations will be performed with the ROMS-MARBL regional ocean model within C-Star. The postdoc will configure and validate a mesoscale-resolving domain spanning the Eastern Pacific, co-design a nested submesoscale-resolving subdomain with external collaborators, run targeted sensitivity experiments, and aid in the release the Atlas as a public, fully documented dataset with reproducible C-Star workflows.

Regional Modeling and Atlas Generation

• Configure a mesoscale-resolving ROMS-MARBL domain for the West Coast of North America within C-Star; establish baseline model performance and validation benchmarks.

• Validate the CDR Tracer (two-tracer) framework within the regional configuration; confirm fidelity against full MARBL reference simulations.

• Design and execute targeted sensitivity experiments addressing geographic release season and location, surface vs. bottom-intensified release configurations, and submesoscale resolution sensitivity.

• Co-design and configure a nested submesoscale-resolving subdomain (in collaboration with external partners) to examine mixed-layer exchange dynamics at 1–10 km scales.

• Develop derived data products using linear superposition of OAE and DOR signals to support multi-intervention simulations (ERW, riverine alkalinity enhancement, partially equilibrated OAE).

Reproducible Workflows and Data Release

• Manage production runs under the resulting HPC allocation.

• Build reproducible, documented dataset-generation workflows within C-Star that are extensible to other regions and serve as templates for future Atlas projects.

• Work with the larger team to:

  • design and implement a data formatting, transformation, and management strategy;  

  • design and implement a public data hosting strategy, including example analysis tools;

  • and release the Atlas as a public, documented dataset with an uptake efficiency kernel library enabling convolution-based MRV for arbitrary deployment configurations.

Community Engagement and Scientific Communication

• Work with the larger team to actively engage the data user community — including CDR deployment operators, MRV practitioners, and academic collaborators — through direct outreach, workshops, and/or collaborative design.

• Submit a peer-reviewed manuscript documenting methodology, validation, and key scientific results.

• Contribute to [C]Worthy's broader scientific program, including participation in field-building activities, user roundtables, and community engagement.

• Ph.D. in oceanography, atmospheric science, geophysical fluid dynamics, or a closely related field.
• Demonstrated experience configuring, running, and evaluating regional ocean models (ROMS, MOM6, NEMO, FVCOM, or equivalent).
• Strong background in ocean biogeochemistry, including carbonate chemistry and air-sea gas exchange.
• Scientific software development proficiency in Python; ability to work with large geospatial datasets.
• Experience with HPC computing environments (e.g., NERSC, NCAR/Wyoming, NSF ACCESS).
• Ability to independently design and execute model experiments and interpret results in the context of real-world applications.
• Strong written and oral communication skills; ability to collaborate in a small, fast-moving research team.

• Familiarity with ROMS or MARBL source code; experience with coupled physical-biogeochemical model configuration.
• Prior work on CDR quantification, MRV methodology, or ocean carbon cycle research.
• Experience developing reproducible scientific workflows (e.g., Prefect, Snakemake, or similar orchestration tools).
• Familiarity with data formats designed for large, cloud-native, multi-dimensional spatial data (e.g. ZARR, HDF, netCDF, COG), visualization tools, and public dataset publication practices.
• Experience engaging with non-academic stakeholders (industry, policy, NGOs) or contributing to applied science products.
• Interest in and familiarity with AI/ML approaches as applied to scientific modeling or data analysis.

This position is full-time, fixed-term (1 year, with possibility of renewal). We expect this role to start in the Fall (September, 2026).

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.