Research Fellow (Dept of the Built Environment)

Posting Start Date: 09/03/2026

Job Description

• Conduct research to improve understanding and forecasting of extreme convective hazards in the Maritime Continent.
• Review the literature on maritime climate modelling.
• Analyse convective storms with emphasis on convection initiation, using multi-source observational datasets, remote sensing products, and reanalysis.
• Integrate and compare observations, NWP model outputs, and nowcasting model products for hazard prediction workflows.
• Develop and apply machine learning–based post-processing methods to enhance forecast skill for convective hazards.
• Perform spatio-temporal data analytics on weather and/or hydrological fields.
• Collaborate closely with project team members; contribute to end-to-end research activities and shared datasets/tools.
• Lead and contribute to peer-reviewed publications, conference presentations, and internal research reporting.
• Maintain organized research workflows (version control, reproducible experiments, documentation).
• Support broader project goals as needed (e.g., dataset curation, method benchmarking, cross-validation with partners).

Job Requirements

• Ph.D. in Atmospheric Science, Meteorology, Hydrology, Machine Learning, Physics, or related discipline (completed or expected within 2–3 months).
• Demonstrated experience with spatio-temporal data analytics for weather and/or hydrological fields.
• Proven machine learning experience (e.g., post-processing, prediction, classification/regression, uncertainty estimation, model evaluation).
• Familiarity with remote sensing products and reanalysis datasets; ability to integrate multi-source observational data.
• Strong programming skills.
• Good publication record in relevant journals.
• Strong written and oral communication skills.
• Highly organized, proactive, and able to work both independently and collaboratively in a multidisciplinary team.
• Proficient command of spoken and written English.
• Experience working with or evaluating NWP outputs and/or nowcasting systems is advantageous.
• Prior experience in international research collaborations is a plus.

More Information

Location: Kent Ridge Campus

Organization: College of Design and Engineering

Department: The Built Environment

Employee Referral Eligible: No

Job requisition ID: 31999

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