Senior Research Fellow – Climate & Urban Sustainability

About the role

The National Institute of Education (NIE) seeks a Senior Research Fellow to lead an 18‑month project investigating the unprecedented 2023 Southeast Asia heatwave. The role combines climate science, AI‑assisted modelling, and urban sustainability research to improve forecasting and inform regional policy.

Key responsibilities

• Develop and apply AI‑enhanced weather and climate models with high spatial and temporal resolution.
• Integrate remote sensing, observational, and numerical model datasets for climate and urban sustainability analyses.
• Conduct research on urban climate processes, including heat‑island effects, boundary‑layer dynamics, air pollution, and building energy consumption.
• Apply machine‑learning and statistical methods for climate risk assessment, prediction, and scenario analysis.
• Analyse large‑scale atmospheric, environmental, and geospatial datasets.
• Support the creation of innovative AI tools and workflows for climate research.
• Collaborate with interdisciplinary teams and external stakeholders.
• Prepare scientific manuscripts, technical reports, and conference presentations.
• Contribute to grant proposals and ongoing research initiatives.

Required profile

• Ph.D. in Climate Science, Atmospheric Science, Environmental Science, Computer Science, AI/Data Science, Remote Sensing, Urban Sustainability or a related field.
• Proven experience with Linux‑based high‑performance computing environments and GPU computing.
• Demonstrated expertise in weather and climate model development and applications.
• Experience applying machine learning, deep learning, or AI to atmospheric modelling.
• Strong scientific writing record with publications in peer‑reviewed journals.
• Ability to work both independently and collaboratively in interdisciplinary research teams.

Required skills

• Linux operating system and HPC environments
• GPU computing
• Weather and climate modelling
• Machine learning and deep learning
• Python programming
• AI/ML frameworks such as PyTorch or TensorFlow
• Processing large geospatial, atmospheric or remote‑sensing datasets