Job Description

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Job Title: Research Fellow (Machine Learning for Hydro-Meteorological Domain)
Posting Start Date: 12/11/2025
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The Department of Civil and Environmental Engineering at the National University of Singapore (NUS) invites applications for one Research Fellow (Postdoc) position in Machine Learning for Hydro-Meteorological Domain to begin as soon as possible.
The project "Enhancements of Singapore's Convective Rainfall Prediction" aims to address several key challenges: (i) How can physics-informed machine learning refine the hydrologically based model for hyperlocal representation of convective rainfall; (ii) How can we enhance convective rainfall prediction with sensing technologies and (iii) How can machine learning develop surrogate models to accelerate process-based simulations. The project is conducted under a multi-institutional and inter-disciplinary Centre of Excellence called Coastal Protection and Flood Resilience Institute (CFI) Singapore.
The candidate will be responsible for completing the scientific tasks of the project, leading and contributing to publications, and is expected to work on the integration of the different tasks with the other postdoctoral fellows working on the project. Besides contributing to the research activities of the project, the successful applicant is expected to support in a broader sense the research of the Hydro informatics group at NUS, thereby providing occasional support to graduate students (MSc and PhD).
Job Requirements

• Possess a PhD degree in Civil/Environmental Engineering or Environmental Science or related disciplines.
• Very solid numerical skills, including programming skills (e.g., Matlab, Julia, Python).
• Demonstration of innovative scientific results obtained during the PhD.
• Excellent communication skills and capability to present research findings in publications.
• Open to fixed-term contract (24 months)

Note: Applications should include in a single .pdf file: (i) a motivation letter, (ii) a detailed Curriculum Vitae including a list of publications, and (iii) contacts of 2 to 3 reference persons.

Skills Required