Remote sensing applications for mapping and monitoring global forest carbon stock and dynamics

About the role

This postdoc opportunity is for candidates with special interest in the remote sensing of global forest carbon dynamics. The successful candidate will work with optical and microwave remote sensing data to estimate and map above ground forest structure, biomass, and changes driven by anthropogenic and climate forcing. The candidate will participate with a team of scientists conducting original research using various statistical and machine learning approaches to develop regional and global products and improve our understanding of the drivers of carbon stock changes across a variety of ecosystems.

Responsibilities

• Work with optical and microwave remote sensing data to estimate and map above ground forest structure, biomass, and changes driven by anthropogenic and climate forcing.
• Participate with a team of scientists conducting original research using various statistical and machine learning approaches to develop regional and global products and improve our understanding of the drivers of carbon stock changes across a variety of ecosystems.
• Collaborate with the team to integrate a series of optical (e.g., Landsat, Sentinel-2, SBG, PlanetScope) and microwave/radar (ALOS, Sentinel-1, and in future, NISAR and BIOMASS) satellite imagery with airborne and satellite lidar (GEDI, ICESAT-2) measurements of forest structure and conventional ground-based forest inventory data to map and monitor changes of forest structure and biomass and attribute the changes to land use activities and environmental effects.
• Help improve the quantification of the global carbon cycle as a result of human and climate-induced changes and better understand the short-term and long-term responses of ecosystems to climate change.
• Formulate a research project in close collaborations with their advisors, perform technical analysis, document algorithms and codes developed for data processing, analysis, science product generation, present at technical conferences, and lead peer-reviewed publications.

Requirements

• A completed doctoral degree in Earth Science, Environmental Science, Remote Sensing, or a related field.
• Experience with remote sensing data analysis, particularly optical and microwave data.
• Strong background in statistical and machine learning techniques.
• Ability to work independently and collaboratively on interdisciplinary projects.
• Excellent communication and presentation skills.

Qualifications

• U.S. Citizenship or U.S. Lawful Permanent Resident status.
• Experience with remote sensing data analysis, particularly optical and microwave data.
• Strong background in statistical and machine learning techniques.
• Ability to work independently and collaboratively on interdisciplinary projects.
• Excellent communication and presentation skills.

Skills

• Proficiency in Python, R, or other programming languages relevant to remote sensing and data analysis.
• Knowledge of remote sensing software such as ENVI, ERDAS, or similar tools.
• Experience with GIS and spatial analysis tools.
• Understanding of forest ecology and ecosystem processes.
• Experience with machine learning and statistical modeling techniques.

Benefits

• One to three-year fellowship with competitive stipend and benefits.
• Opportunities to work with leading scientists and researchers at NASA Centers and affiliated institutions.
• Access to state-of-the-art facilities and equipment.
• Professional development opportunities through participation in technical conferences and workshops.
• Support for publication of research findings in peer-reviewed journals.

Pay

• Competitive stipend based on qualifications and experience.

Schedule

• Full-time position with flexible working hours.

Contact Information

To apply, please visit the NASA Postdoctoral Program website: How to Apply | NASA Postdoctoral Program. For questions about this opportunity, please email npp@orau.org.