About the job
Postdoctoral Researcher – AI for Climate Science
Location: ADIA Lab, Abu Dhabi
Eligibility: PhD completed within the last three years in Climate Science, Atmospheric Science, Agrometeorology, Physical Oceanography, Applied and Computational Mathematics, Physics, Engineering, or a related field.
About the Role
Join the innovative team at ADIA Lab as a Postdoctoral Researcher in AI for Climate Science, where you will spearhead research initiatives that leverage artificial intelligence, data science, and high-performance computing to enhance our understanding of Earth's systems. You will collaborate on impactful projects that intersect AI, climate modeling, and sustainability, contributing to our mission of tackling global challenges through advanced computational sciences.
Research Focus Areas
The Postdoctoral Researcher will focus on one or more of the following key areas:
1. Earth System Data Curation and Platforms
- Innovate new datasets and fusion methodologies that integrate satellite, in-situ, IoT, and citizen-science Earth system data.
- Utilize AI-driven interpolation, transfer learning, and synthetic data generation to address spatiotemporal data gaps in crucial environmental parameters.
- Construct quality-controlled, scalable climate data platforms enriched with metadata, ML annotations, and standardized classification schemes.
- Enhance data pipelines for Earth System Digital Twin (ESDT) case studies.
2. AI and Hybrid AI-Physics-based Earth System Models
- Develop and refine foundational models that integrate satellite, reanalysis, and sensor data.
- Incorporate physics-aware machine learning into climate and weather models to improve process representation at sub-kilometer scales.
- Advance AI-driven data assimilation, emulation, and post-processing techniques for predicting weather-to-climate transitions.
- Establish large language model (LLM) frameworks to enhance synthesis and scientific reasoning in Earth system analysis.
3. AI for Climate Adaptation and Resilience
- Assess uncertainty in downscaled projections of future extreme weather and climate hazards.
- Conduct case studies that link climate impacts to water security, energy systems, infrastructure performance, and financial risk.
- Foster partnerships with sectoral experts and policymakers to co-design AI tools that inform scenario planning, adaptive investment strategies, and early-warning systems.
4. Ethical Climate AI and Governance
- Create operational science infrastructures for benchmarking AI methodologies in climate science.
- Contribute to the establishment of shared experimental standards and reproducibility protocols.
