Job Description

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 Fellow, Distributed Acoustic Sensing to advance research on distributed fiber-optic sensing for infrastructure, urban, and environmental applications. The role will focus on distributed acoustic sensing on pre-existing telecom fiber networks, wavefield analysis, structural and geophysical interpretation, multi-modal data fusion, and lab-scale and field experiments for real-world deployment.

Key Responsibilities:

Develop algorithms for DAS signal processing, wavefield analysis, feature extraction, and interpretation across infrastructure monitoring, urban geophysics, and environmental sensing applications.
Design and execute lab-scale experiments to validate DAS methodologies, sensing configurations, and multi-modal measurement strategies.
Plan and conduct field deployments using telecom fiber networks or dedicated fiber-optic sensing systems in civil infrastructure and dense urban environments.
Build scalable pipelines for DAS data quality control, denoising, event detection, inversion or imaging, system identification, and data fusion.
Integrate DAS with complementary sensing modalities and computational tools, including AI or ML where appropriate, to improve monitoring performance and scientific understanding.
Prepare publications, presentations, technical reports, and proposal inputs mentor students and collaborate with the PI and external partners.

Job Requirements:

PhD in Civil/Structural Engineering, Geophysics, Seismology, Engineering Mechanics, Electrical/Computer Engineering, Applied Physics, Optical Engineering, Computer/Data Science, or a related field.
Strong research record in distributed fiber-optic sensing, DAS, wave propagation, structural health monitoring, passive seismology, geophysical imaging, or related areas.
Experience processing large-scale DAS datasets, including signal processing, quality control, feature extraction, system identification, imaging, inversion, or source characterization, is highly desirable.
Proficiency in Python, C++, or Julia, with strong numerical modeling, data analysis, and reproducible code development skills experience with Git-based workflows and AI or ML for science is a plus.
Experience designing and executing laboratory or field experiments, with willingness to engage in fieldwork using telecom fiber networks or other DAS deployments.
Good written and oral communication skills, with the ability to publish high-quality research and collaborate across interdisciplinary teams.
Ability to work independently, mentor students, manage multiple research tasks, and contribute to a fast-paced collaborative research environment.

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