Research Associate (Distributed Acoustic Sensing)

The School of Civil and Environmental Engineering (CEE) is a leading school for Sustainable Built Environment. Our mission in research is to achieve excellence by providing a conducive and intellectually stimulating environment to enable high quality work in strategic directions that are of significant impact to industry, science and technology.

For more details, please view https://www.ntu.edu.sg/cee.

We are looking for a Research Associate to develop automated methods for mapping telecommunications fiber-optic cable routes using distributed acoustic sensing (DAS) and geospatial data. The role will reconstruct the likely surface alignments and geographic coordinates of existing underground cables by integrating DAS-derived route information with mobile GNSS, inertial and camera measurements, satellite or aerial imagery, road networks, building footprints, utility features, and other digital maps. The research will emphasize spatial accuracy, confidence estimation, and uncertainty-aware mapping to support reliable DAS interpretation and urban infrastructure monitoring.

Key Responsibilities:

• Develop automated, uncertainty-aware algorithms to infer and map fiber-optic cable routes from DAS-derived information and complementary geospatial data.

• Plan and conduct field data collection along accessible fiber corridors using smartphone-based GNSS, inertial sensors, and cameras, while maintaining clear metadata and quality-control procedures.

• Process, register, and fuse satellite or aerial imagery, road networks, building footprints, utility features, and other available digital maps.

• Build reproducible Python pipelines for DAS and geospatial datasets, including preprocessing, coordinate transformation, feature extraction, database management, and visualization.

• Apply geospatial analysis, computer vision, image processing, machine learning, and spatial optimization to reconstruct cable surface alignments and geographic coordinates.

• Validate inferred routes against reference or field observations and quantify spatial accuracy, confidence, uncertainty, and mapping resolution.

• Prepare journal papers, conference presentations, technical reports, documentation, and proposal inputs, and collaborate with the PI, students, industry partners, and other researchers.

Job Requirements:

• Master's degree in Civil or Environmental Engineering, Geomatics, Geospatial Science, Electrical or Computer Engineering, Computer or Data Science, Remote Sensing, or a related field.

• Proficiency in Python and experience with geospatial data processing, spatial analysis, scientific programming, data visualization, or reproducible research workflows.

• Knowledge of one or more of the following: GIS, remote sensing, computer vision, image processing, machine learning, spatial statistics, or map-based data fusion.

• Experience working with GNSS, inertial-sensor, camera, satellite, aerial, road network, building-footprint, or utility-map datasets is advantageous.

• Familiarity with distributed acoustic sensing, fiber-optic sensing, signal processing, or telecommunications infrastructure is desirable but not essential.

• Good written and oral communication skills, with the ability to prepare technical documentation and research publications and to work collaboratively with academic and external partners.

• Ability to work independently, manage multiple research tasks, and participate in field data collection in a fast-paced research environment.

We regret to inform that only shortlisted candidates will be notified.