Staff Scientist, Modeling Applications
Role Overview modeling systems for CDR quantification, we are seeking a Staff Scientist to build and apply near-field and regional model configurations to strategically identified oceanic systems. The role will sit within our Applications team, which takes on projects at the intersection of applied regional modeling, model development, and process-level ocean alkalinity enhancement (OAE) research. Activities will include standing up, validating and running near-field, regional, and simplified OAE models to characterize the physical and biogeochemical controls on OAE efficiency, and develop the knowledge and data products that inform MRV and deployment design.
This is a unique position, which sits at the intersection of academia and industry, offering multiple learning and career-advancing opportunities:
Answer central scientific questions at the frontier of ocean-based CDR research
Develop and use cutting edge open-source ocean modeling tools, paving the way for others to follow your steps
Leverage AI & ML to expand impact and enhance tooling for CDR
Design and deploy data visualizations of large geospatial datasets
Interact with academic, government, and industry researchers and practitioners of ocean-based CDR
Contribute to collaborative open-source software packages
The successful candidate will be a technically well-rounded ocean modeler who can contribute across the full modeling lifecycle—from model and scientific software development to model application, analysis, and interpretation. The ideal candidate will be comfortable working collaboratively as a member of a larger technical team, moving across a variety of projects, learning new tools and scientific domains, and helping expand our capabilities into new areas of oceanographic modeling.
Required Qualifications Ph.D. in oceanography, atmospheric science, geophysical fluid dynamics, marine biogeochemistry, or a closely related field
Demonstrated experience configuring, running, and evaluating global/regional ocean and/or estuary models (e.g., Oceananigans, ROMS, MOM6, NEMO, FVCOM, SCHISM, MITGCM, Delft3D, or equivalent)
Working knowledge of ocean biogeochemistry, including carbonate chemistry and air-sea gas exchange
Proficiency in Python
Strong written and oral communication skills, including the ability to convey technical results to non-specialist audiences; ability to collaborate in a small, fast-moving research team
Preferred Qualifications Interest in and familiarity with AI/ML approaches applied to scientific modeling or data analysis.
Prior work on CDR quantification, MRV methodology, or ocean carbon cycle research
Experience developing reproducible scientific workflows
Familiarity with cloud-native, multi-dimensional data formats (e.g., ZARR, HDF, netCDF, COG), visualization tools, and public dataset publication practices
Experience with HPC computing environments (e.g., Slurm)
Familiarity with uncertainty quantification, ensemble methods, or Bayesian calibration