Model Development

This role involves designing and implementing a hybrid physics-AI spatiotemporal modeling framework to translate satellite-derived Land Surface Temperature data into high-resolution ambient air temperature maps. The position requires developing and training Graph Neural Network and Long Short-Term Memory architectures to model complex spatial and temporal dependencies in urban microclimate data. The role also encompasses data collection, validation, model interpretability, and stakeholder engagement to support policy application and downstream adoption.