Job Description

The Research Assistant/Engineer will participate in experimental research, with a specific focus on the integration of artificial intelligence (AI) into coastal engineering to advance shoreline protection. Specifically, the project will develop AI-based models using Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) to predict water flow velocity—a key parameter in assessing coastal vulnerability and the performance of protective structures. Students will work with video and/or sensor data from laboratory or field environments to train and validate their models. The project combines AI, computer vision, and environmental fluid mechanics to deliver predictive tools that can support real-time monitoring and decision-making for coastal infrastructure.
 

The research assistant/engineer will work with Assistant Professor Gary Lei from Civil and Environmental Engineering at NUS. Ideally, we are interested in candidates with prior experience with laboratory experiments and machine learning.
 

Job Requirements

•    Possess at least a Bachelor and or master’s degree in civil engineering, Environmental Engineering, Environmental Science, Mechanical Engineering in related field.
•    Priority will be given to applicants who have prior research experience in AI, deep learning, eco-hydraulics, and/or environmental fluid mechanics.
•    Has strong verbal and written communication skills.
•    Proficient with Python.
•    Open to fixed-term contract

More Information

Location: Kent Ridge Campus

Organization: College of Design and Engineering

Department : Civil and Environmental Engineering

Employee Referral Eligible: No

Job requisition ID : 29268