ResponsibilitiesLead independent research within a collaborative team using machine learning and process-based models to generate regional and global products and advance understanding of drivers of carbon stock change. Main areas of research will be selected from the following:
- Geospatial analysis of climate, disturbance (land use change, logging, mortality), fire fuel loads, and biomass/carbon dynamics across tropical forests
- Analysis of the accuracy of forest biomass change maps based on satellite, airborne, and forest inventory inputs.
- Development of advance machine learning models including generative and foundational AI to map time series of biomass change from airborne and satellite data
- Develop, implement, and document algorithms and reproducible code for data processing, analysis, and science-product generation.
- Lead preparation of peer-reviewed publications and present results to interdisciplinary teams and stakeholders.
Desired qualifications- PhD completed or near completion in remote sensing, computer science, environmental science/engineering, statistics/mathematics, ecology, geography, or a closely related field, with relevant experience in forest applications.
- Demonstrated experience with quantitative geospatial and satellite data analysis, including Synthetic Aperture Radar (SAR) and/or LiDAR forest remote-sensing methods.
- Proficiency in advanced machine learning (including time-series methods and experience with generative/foundation AI models) and data-assimilation or ecosystem-model coupling.
- Strong programming skills in scientific languages (e.g., Python, MATLAB, or R) and solid statistical background.
- Track record of quantitative research and peer-reviewed publications, and ability to work effectively in interdisciplinary, collaborative teams.
Preferred qualificationsPrior experience with carbon monitoring systems, forest inventory data, cloud-native geospatial workflows, or large-scale remote-sensing product development. Experience working across tropical ecosystems and with stakeholder-relevant applications (policy, management, MRV).
ApplicationTo apply, submit a CV, a brief cover letter describing research interests and which task you wish to lead, a publication list, and contact information for three references. Review of applications will begin immediately and continue until positions are filled.
JPL has a catalog of benefits and perks that span from the traditional to the unique. This includes a variety of health, dental, vision, wellbeing, and retirement plans, paid time off, learning, rideshare, childcare, flexible schedule, parental leave and many more. Our focus is on work-life balance, and living healthy, fulfilling lives as we Dare Mighty Things Together. For benefits eligible positions, benefits are effective the first day of the month coincident with or immediately following the employee's start date.
For further benefits information click Benefits and Perks
The hiring range displayed below is specifically for those who will work in or reside in the location listed. In extending an offer, Jet Propulsion Laboratory considers factors including, but not limited to, the candidate's job related skills, experience, knowledge, and relevant education/training.
The typical full time equivalent annual hiring range for this job in Pasadena, California.
$83,820 - $83,820
