Remote Sensing Research Fellow: Forest Biomass & ML

National University of Singapore; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

The National University of Singapore invites applications for a research position focusing on remote sensing-based biomass estimation. The project aims to improve AGB estimation using machine learning and SAR with satellite lidar data, with emphasis on uncertainty analysis of ESA BIOMASS estimations.

Applicants should hold a PhD in Geography/Remote Sensing/Photogrammetry, demonstrate strong programming and quantitative analysis skills, and have experience in publishing in peer-reviewed journals.

Qualifications

• A PhD degree in Geography, Remote Sensing and Photogrammetry, or a related field
• Excellent programming techniques
• Strong quantitative data analysis (spatial statistics in particular)
• Some fieldwork experience, preferably in the tropics
• Good oral and written communication skills
• Prior experience in publishing in peer-reviewed scientific journals

Responsibilities

• Contribute to a 1-year project aiming to improve forest biomass estimation through machine learning and the synergy of SAR with satellite lidar data for wall-to-wall AGB mapping.
• Emphasize uncertainty analysis of ESA BIOMASS estimation via a full error propagation procedure.

Skills

Quantitative analysis

Programming

Fieldwork experience

Communication skills

Education

PhD degree in Geography/Remote Sensing/Photogrammetry

Job description

The National University of Singapore invites applications for a research position focusing on remote sensing-based biomass estimation. The project aims to improve AGB estimation using machine learning and SAR with satellite lidar data, with emphasis on uncertainty analysis of ESA BIOMASS estimations.

Applicants should hold a PhD in Geography/Remote Sensing/Photogrammetry, demonstrate strong programming and quantitative analysis skills, and have experience in publishing in peer-reviewed journals.