Research Fellow (Distributed Acoustic Sensing)

Nanyang Technological University

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NTU Main Campus, Singapore Until 10/3/2026 First posted August 4, 2026 Last posted August 4, 2026
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.

Hiring Institution: NTU

About this role

Summary

Research on distributed fiber-optic sensing, signal processing, field experiments, and data analysis.

Job title

Research Fellow (Distributed Acoustic Sensing)

Experience level

PhD

Industry

education

Location requirements

Singapore, on-site; remote work not specified

Salary

Not specified

Management role

No

Skills & keywords

Required skills

PythonC++signal processinglarge-scale DAS datasetsfield experiments

Preferred skills

JuliaAIMLdata analysisGit

Specializations

distributed fiber-optic sensingwave propagationgeophysical imagingsignal processingAI
Locations

Structured locations inferred from the posting.

Unknown location

On-site