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A prestigious university in Singapore is seeking a Research Engineer focused on AI and Fluid Mechanics to advance shoreline protection methodologies. The position requires developing innovative AI-based tools that integrate environmental fluid mechanics with modern machine learning techniques. Candidates are preferred with relevant educational backgrounds and skills in Python and laboratory experiments.
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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.
• 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
Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department : Civil and Environmental Engineering
Employee Referral Eligible: No
Job requisition ID : 29268
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