Research Engineer II (Remote Sensing and Machine Learning)
Core
Develop a machine learning model to forecast forest growth by integrating microclimate and connectivity data from UAV mapping missions for NUS Ecology and Geospatial teams.
Role type
Predoctoral researcher (Data Scientist, ML Researcher, ML Engineer)
Builds
Biodiversity classification and LIDAR canopy analysis algorithms; a professional data portal for stakeholder data input and result visualization.
Domain
Environmental science, remote sensing, forestry
Deliverable
production ML models | product features
Required skills
remote sensing, machine learning, data science, software engineering, UAV data curation, LIDAR canopy analysis, data visualization
Preferred skills
part-time PhD or Master's enrollment in EEE or related program
Technologies
UAV mapping, LIDAR, industry-standard software engineering practices
Responsibilities
Perform fieldwork and curate remote sensing data from UAV mapping missions; develop biodiversity classification and LIDAR canopy analysis algorithms; build system infrastructure to serve UAV data; construct a professional data portal for stakeholders; liaise between NTU, NUS, and NParks.
Seniority
Predoctoral researcher