Research focused on reducing bias and uncertainty in the measurement and monitoring of forest carbon uptake Indiana University at Bloomington in United States

This postdoctoral research scholar position in the Novick Group at Indiana University Bloomington focuses on reducing bias and uncertainty in the measurement and monitoring of forest carbon uptake from local to global scales. Forests play a dominant role in the land carbon sink, and strategies for forest-based carbon removal offer significant benefits for both the environment and the bio-economy. However, current estimates of forest carbon uptake and storage (FCUS) can vary widely, sometimes by 50-100% or more, across different spatial scales. The overarching goal of this project is to use the best available science to address these discrepancies and to develop tools that enable seamless integration between project-scale FCUS monitoring and broader policy-making at regional to global levels.

The postdoctoral scholar will lead the synthesis of network observations, including forest inventory data (such as from the USDA Forest Inventory and Analysis program) and flux tower data (from networks like AmeriFlux and FLUXNET). The role also involves integrating these ground-based observations with advanced remote sensing data that describe forest structure and function. The position requires computationally intensive data analysis, preparation and submission of journal articles, and mentoring of students and technicians involved in the project.

The successful candidate will be supervised by Professor Kim Novick at the O’Neill School of Public & Environmental Affairs, with opportunities to collaborate with other IU scientists, academic partners at other institutions, and organizations from the civic and public sectors. The preferred work location is Bloomington, Indiana, but remote arrangements may be considered. Applicants should have a Ph.D. in environmental science or engineering, ecology, environmental informatics, or a related field, along with strong communication skills, experience in collaborative research teams, and expertise in analyzing ecological time series and remote sensing datasets.

The position offers a competitive salary commensurate with experience and includes full benefits. The best consideration date for applications is November 15, 2025, with an expected start date of January 15, 2026. For more information or to apply, visit the provided application link or contact Professor Kim Novick.