Model exploration of iron fertilization at Princeton University

The Atmospheric and Oceanic Sciences Program at Princeton University in cooperation with NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL) seeks a postdoctoral or more senior research associates to enlist global earth system models to assess the effectiveness and risks of ocean iron fertilization as a carbon dioxide removal strategy to slow the pace of climate change. The work will be conducted as part of a recently funded collaborative project with Woods Hole Oceanographic Institution and the National Center for Atmospheric Research on assessment of potential marine Carbon Dioxide Removal strategies. The incumbent will leverage GFDL?s existing 1/2 degree fully-coupled Earth System Model (ESM4.1) and high-resolution coupled physical-biological ocean configurations. The incumbent will assess the effectiveness, implications, and observational requirements for both small- and Petagram- scale fertilization. Personnel will join an active group at Princeton and GFDL studying the connect ions between biogeochemistry, ecosystems, and climate (

This is a one-year position with the possibility of renewal for a second year (contingent upon satisfactory performance and funding) based at GFDL in Princeton, New Jersey. Complete applications, including a cover letter, CV, publication list, a one to two-page statement of research interests and names of at least 3 references in order to solicit letters of recommendation, should be submitted online at by August 31, 2023 11:59 p.m. EST for full consideration, though evaluation will be ongoing. Princeton is interested in candidates who, through their research, will contribute to the diversity and excellence of the academic community.

Essential Qualifications: PhD is required. Candidates with quantitative, interdisciplinary knowledge from subsets of fields including climate dynamics, ocean and coastal biogeochemistry, marine ecosystem dynamics, and fisheries science and management are particularly encouraged to apply. Experience analyzing large data sets and/or model output is also critical, as is model development experience for those positions.

This position is subject to Princeton University’s background check policy. Princeton University is an equal opportunity/affirmative action employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.