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, Civil Infrastructure Monitoring Using Distributed Sensing to advance scalable monitoring of bridges, tunnels, railroads, and roadway structures using distributed sensing technologies. The role will focus on distributed acoustic sensing on pre-existing telecom fiber networks, mobile sensing using vehicle fleets, multi-modal data fusion, and structural system identification through lab-scale and field experiments.

Key Responsibilities:

• Develop algorithms for guided-wave analysis, response analysis, sensor fusion, and system identification using distributed and multi-modal sensing data.

• Design and execute lab-scale experiments to study structural response and validate distributed sensing methodologies.

• Plan and conduct field deployments on bridges, railroads, and roadway structures using Distributed Acoustic Sensing and Distributed Mobile Sensing (DAS) on telecom fiber networks and mobile sensing platforms.

• Build data processing pipelines for DAS and vehicle-based sensing datasets, including quality control, signal processing, and feature extraction.

• Integrate distributed sensing with complementary sensing modalities for infrastructure diagnostics, damage assessment, and performance monitoring.

• Prepare journal papers, conference presentations, technical reports, and proposal inputs with the PI and external collaborators.

• Mentor graduate students and contribute to collaborative research activities that advance the group's infrastructure monitoring agenda.

Job Requirements:

• PhD in Civil/Structural Engineering, Engineering Mechanics, Electrical/Computer Engineering, Applied Physics, Computer/Data Science, Optical Engineering, or a related field.

• Strong research record in distributed fiber-optic sensing, structural health monitoring, structural dynamics, guided waves, system identification, or infrastructure monitoring.

• Experience with DAS or other distributed fiber-optic sensing technologies, including data processing, analysis, or deployment, is highly desirable.

• Proficiency in Python, C++, or Julia, with strong signal processing, numerical modeling, and data analysis skills; experience with Git-based workflows and AI/ML for science is a plus.

• Hands-on experience in structural testing or field experimentation, including modal testing, acoustic emission, ultrasonic testing, or related methods, is advantageous.

• Good written and oral communication skills, with the ability to publish high-quality research and work collaboratively with students and external partners.

• Ability to work independently, manage multiple research tasks, and engage in laboratory and fieldwork in a fast-paced research environment.

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