Job Title: Research Fellow (AI and Visual Monitoring of Coastal Vegetation and Flows)
University-Level Unit: Coastal Protection and Flood Resilience Institute Singapore
Faculty/Department-Level Unit: Coastal Protection and Flood Resilience Institute Singapore
Employee Category: Research Staff
Location_ONB: Kent Ridge Campus
Posting Start Date: 10/11/2026
Job Description
How much can a video of swaying seagrass tell us about the flow around it? Join Asst Prof Jiarui (Gary) Lei’s team in Civil and Environmental Engineering at the National University of Singapore. You will lead the development of visual monitoring methods for the CFI Singapore VASE-R project (V2-P9).
Design wave-flume experiments that pair video of vegetation motion with acoustic Doppler measurements. Develop and test deep learning models that estimate water velocity and turbulence from that motion.
Develop computer vision methods to combine colour and depth (RGB-D) images with LiDAR surveys. Map vegetation structure and bed changes, including scour around mangrove roots and erosion at seagrass patch edges.
Validate flow estimates against flume and field measurements, and bed reconstructions against measured bed profiles. Quantify uncertainty and document the analysis code and field protocols so other teams can repeat the measurements.
Apply through NUS Careers with a CV and a short note on your research interests. For enquiries, contact Asst Prof Gary Lei at jlei@nus.edu.sg.
Qualifications
- A PhD in engineering, computer science or a related field.
- Strong Python programming and machine learning skills, including experience developing and validating models on measurement data.
- Experience with computer vision for video, depth imagery or 3D point clouds, and the ability to design and communicate a reproducible analysis.
- Familiarity with coastal hydrodynamics, flume experiments, acoustic Doppler measurements or coastal field surveys is desirable.
Req ID: 34945