Research Fellow (AI-Based Integrated System for Safe Management of Ammonia Fuel)
Research Fellow (AI-Based Integrated System for Safe Management of Ammonia Fuel)
University-Level Unit: Centre for Hydrogen Innovations
Faculty/Department-Level Unit: Centre for Hydrogen Innovations
Employee Category: Research Staff
Location: Kent Ridge Campus
Posting Start Date: 24/03/2026
Job Description
We are seeking a highly motivated Research Fellow to join the project of ‘Development of an AI-based integrated system for safe management of ammonia fuel in maritime sector’ led by Prof. Yang Wenming and Dr. Zhou Xinyi. Major duties and responsibilities include:
- Design an intelligent fiber optic monitoring system that provides real-time detection of incidents such as ammonia fuel leaks and pipe deformations, and prevents accidents through early detection of pipeline cracks.
- Establish the scaled-down integrated test-bed to validate the effectiveness of the developed intelligent monitoring system.
- Formulate detailed R&D experimental plans and carry out system setup, signal acquisition and processing, as well as algorithm design, implementation, and optimization.
- Assist the team in the establishment of the ammonia fuel engine and its associated systems.
- To supervise/mentor undergraduate and graduate students that work in the lab.
Qualifications
The candidate must:
- PhD in Optical Engineering, Energy and Power Engineering, or a related field.
- Strong expertise and a solid publication record in advanced optical diagnostics, experimental test bench development, and algorithm design and optimization.
- Demonstrated in-depth research and practical experience in distributed sensing principles, system architecture, and advanced signal processing or deep learning algorithms.
- Proficient in MATLAB, Python, or C++, with strong capabilities in algorithm development and data analysis.
- Preference will be given to candidates with experience in ammonia engines and the design of their fuel supply systems.
- Excellent problem-solving skills and the ability to work both independently and collaboratively.
For further inquiries, please contact Dr. Zhou Xinyi (zhou_xy@nus.edu.sg)
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