ADIA Lab - Postdoc Researcher - AI for Climate Science

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 ADIA Lab is seeking a Postdoctoral Researcher in AI for Climate Science to advance the application of artificial intelligence, data science, and high-performance computing to the Earth system.
The successful candidate will lead research at the intersection of AI, climate modeling, and sustainability applications, contributing to ADIA Lab’s mission of addressing global challenges through data and computational sciences.
Topics of interest The Postdoc will lead research efforts in one or more of the following focus areas:   Thrust Area 1: Earth System Data Curation and Platforms  Develop new datasets and data fusion approaches integrating satellite, in-situ, IoT, and citizen-science Earth system data.
Address spatiotemporal data gaps in key environmental variables using AI-based interpolation, transfer learning, or synthetic data generation.
Build quality-controlled, scalable climate data platforms with metadata, ML annotations, and standardized classification schemes.
Improve data pipelines for Earth System Digital Twin (ESDT) case studies   Thrust Area 2: AI and Hybrid AI-Physics-based Earth System Models Build and/or fine-tune foundation models integrating satellite, reanalysis, and sensor data.
Integrate physics-aware machine learning into climate/weather models to improve sub-kilometer-scale process representation.
Advance AI-driven data assimilation, emulation, and post-processing for weather-to-climate prediction.
Develop large language model (LLM) frameworks for synthesis and scientific reasoning in Earth system analysis.
  Thrust Area 3: AI for Climate Adaptation and Resilience Quantify uncertainty in downscaled projections of future extreme weather and climate hazards.
Conduct region-specific case studies linking climate impacts to water security, energy systems, infrastructure performance and financial risk.
Integrate domain and decision science, co-designing AI tools with sectoral experts and policymakers to support scenario planning, adaptive investment strategies, and early-warning systems.
  Thrust Area 4: Ethical Climate AI and Governance Develop operational science infrastructures for benchmarking AI methods in climate science.
Contribute to defining shared experimental standards, reproducibility protocols, and responsible-AI practices for climate applications.
Support open science and ethical data governance aligned with ADIA Lab’s sustainability and transparency principles.
    Other Topics Applicants with innovative ideas at the intersection of AI, sustainability, and environmental sciences are encouraged to propose their own topics with demonstrable scientific or societal impact potential.
Additional responsibilities include mentoring graduate students and interns, co-authoring high-impact publications, contributing to competitive grant proposals, and presenting research at major conferences.
Postdoctoral researchers are encouraged to take full advantage of ADIA Lab’s interdisciplinary collaboration opportunities and to contribute to projects across its other research pillars   Required Skills We seek candidates with strong research and publication records in AI, data science, or Earth system sciences, with demonstrated ability to conduct interdisciplinary work.
Required skills include:  Work with large geospatial datasets and locally collected (single point) earth system measurements - experience in analysing raw and processed multimodal data (surface, airborne, and space-borne measurements), reanalysis datasets, climate/weather model output (e.
g., ICON, WRF, MPAS) and developing climate data analytics; Working experience with AI weather models, weather forecasting, and climate modeling/dynamics; Experience in implementing advanced ML algorithms, including generative models, for downscaling climate data; Proficiency in Python, PyTorch, TensorFlow, JAX or similar ML frameworks.
Expertise in high-performance computing (HPC), cloud platforms, and GPU clusters.
Strong understanding of deep learning, time-series modeling, causality frameworks, and data assimilation; Ability to work both independently and as part of a multidisciplinary team; Ability to work in a fast-paced environment; Strong communication skills.
What We Offer Mentorship and support with leading research projects.
Collaboration opportunities within and beyond UAE.
Resources to succeed - compute, conference attendance opportunities, etc.