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Postdoctoral Research Scientist, Ocean CDR Atlas
Convergent Research
Postdoctoral Research Scientist, Ocean CDR Atlas
This job is still taking applications, but it's been up a while.
About the job
[C]Worthy is a nonprofit focused on oceanographic models for carbon removal. The role involves building high-res ocean datasets to support MRV, enabling transparent, science-backed ocean decisions worldwide.
Requirements
- Configuring regional ocean models
- Experience with ocean biogeochemistry
- Proficiency in Python programming
- HPC computing experience
- Independently designing experiments
Qualifications
- Ph.D
- in oceanography or related
- Experience with ROMS or NEMO
- Strong communication skills
- Research software development
Full job description
About [C]Worthy
Role Overview
Key Responsibilities
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.
Required Qualifications
- 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.
Preferred Qualifications
- 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.
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