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

MBZUAI (Mohamed bin Zayed University of Artificial Intelligence); Abu Dhabi; On-site; AED 335,000 - 469,000; Full time

Benefits offered by this job

Tax-free salary

Housing allowance

Medical insurance

Annual return flight

Full visa support

Job summary

MBZUAI invites applications for a fully funded two-year Postdoctoral Researcher position in AI for Weather Forecasting under Prof. Souhaib Ben Taieb.

The role is embedded in a collaboration with the AI for Climate initiative at the University of Chicago, supported by UAE and Gates Foundation funding. The position includes a competitive tax-free monthly salary, housing allowance, medical insurance, a return flight, and visa support.

Qualifications

• PhD in a relevant field with strong research record in AI or ML for weather/climate.
• Experience applying ML to weather forecasting or climate analysis.
• Proficiency in Python and ML frameworks (PyTorch or JAX).
• Familiarity with weather/climate datasets (reanalysis, satellite, observations).
• Excellent written and spoken English with publications in top venues.

Responsibilities

• Conduct original research in probabilistic and ensemble weather forecasting.
• Develop and evaluate AI-based forecasting methods with diverse datasets.
• Assess forecast metrics, calibration, extremes, and regional performance.
• Create models suitable for operational settings and regional needs.
• Publish results in AI or domain-relevant venues and present findings.
• Collaborate with MBZUAI, Chicago initiative, and external agencies; support knowledge transfer.

Skills

ML for weather

Spatiotemporal modeling

Python + PyTorch/JAX

Weather datasets

Publications & English

Education

PhD in CS / Atmospheric Science / Applied Math

Tools

xarray

Dask

NetCDF

Zarr

Job description

Job Description

MBZUAI invites applications for a fully funded two-year Postdoctoral Researcher position in AI for Weather Forecasting under the supervision of Prof. Souhaib Ben Taieb. The role is embedded within a collaborative research program between MBZUAI and the AI for Climate initiative at the University of Chicago, supported by funding from the International Affairs Office at the Presidential Court of the United Arab Emirates and the Gates Foundation. The program advances AI-based weather forecasting methods and supports their operational use in low- and middle-income countries. The position includes a competitive tax-free monthly salary, housing allowance, comprehensive medical insurance, an annual return flight, and full visa application support.

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.

Why Join MBZUAI?

• Top-Tier Compensation: Competitive salaries aligned with leading global academic institutions
• Exceptional Benefits:
  • Comprehensivehealth & life insurance
  • Relocation supportfor 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

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.