Computing And Mathematical Sciences Division - Postdoctoral Researcher AI For Weather Forecasting

Job Overview

Key Responsibilities

• Conduct original research in probabilistic and ensemble weather forecasting, deep learning for spatiotemporal data, uncertainty quantification, data assimilation, or related areas.
• Develop and rigorously evaluate AI-based weather forecasting methods using reanalysis, satellite, observational, and forecast datasets.
• Assess forecast accuracy, calibration, extremes, and regional performance using appropriate probabilistic and deterministic metrics and reproducible benchmarks.
• Develop forecasting models suitable for operational settings, with particular emphasis on agriculturally relevant products and regional and sector-specific needs.
• Publish research in top-tier AI or domain-relevant venues and communicate findings to technical, interdisciplinary, and operational audiences.
• Collaborate with research institutions, government agencies, national meteorological and hydrological services, agricultural institutions, and practitioners; contribute to training and knowledge transfer.

Qualifications

• Experience applying machine-learning methods to weather forecasting, climate analysis, or spatial data.
• Strong background in spatiotemporal modeling, probabilistic prediction, or time-series analysis.
• Proficiency in Python and hands-on experience with PyTorch or JAX.
• Experience working with weather or climate datasets, such as reanalysis, satellite, observational, or forecast data.
• Strong publication record in top-tier AI or domain-relevant venues and excellent written and spoken English.
• PhD in Computer Science, Atmospheric or Climate Science, Applied Mathematics, Statistics, or a closely related field.

Preferred Qualifications

• Experience with data assimilation, uncertainty quantification, ensemble methods, or evaluation frameworks such as WeatherBench 2.
• Experience with xarray and scalable scientific-data workflows using Dask and NetCDF or Zarr datasets.
• Experience with GPU or distributed training and familiarity with agricultural or environmental applications of weather forecasts.
• Experience working in interdisciplinary or international research collaborations.
• Advanced training in spatiotemporal modeling, probabilistic prediction, numerical weather prediction, data assimilation, or uncertainty quantification.

Why Join MBZUAI?

• Top-Tier Compensation: Competitive salaries aligned with leading global academic institutions.
• Exceptional Benefits: Comprehensive health & life insurance; relocation support for international hires.
• Live in Abu Dhabi: World's safest city, year-round sunshine, rich culture, and modern amenities.
• Industry & Government Collaborations: Work with top AI researchers, leading tech firms, and policymakers.

Application Instructions

• Interested candidates should submit a cover letter, curriculum vitae (C.V.), a link to their Google Scholar profile, a 1-2 page research statement, and name and contact details for two referees.