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