Postdoctoral Researcher Middlesex University Dubai

1. Systematic Literature Review & Research Design

• Conduct a comprehensive review of AI applications in urban heat mapping, remote sensing-based LST estimation, and Heat Vulnerability Index (HVI) development.
  
• Synthesize global best practices and adapt methodologies to Dubai s climatic and urban context.
  
• Develop and implement machine learning models (e.g., CNNs, pixel-object classifiers) for high-resolution Land Surface Temperature (LST) estimation using multi-source satellite data (MODIS, Sentinel-3, Landsat-8/9).
  
• Correct emissivity variations and improve classification of land cover types.
  
• Generate seasonal and diurnal LST maps forming a dynamic thermal atlas of Dubai.
  
• Contribute to academic publishing
  

2. Ground-Truth Validation & Field Campaigns

• Design and execute field-based climatology campaigns across representative urban typologies (dense residential, industrial zones, coastal areas, labor housing).
  
• Deploy and calibrate temperature and humidity sensors.
  
• Conduct mobile thermal imaging and validate satellite-based LST outputs.
  
• Develop validated, geo-referenced datasets for policy-grade accuracy.
  

Design and compute Dubai s first spatially calibrated Heat Vulnerability Index integrating:

• Contribute to the design and implementation of a web-based GIS dashboard.
  
• Support delivery of stakeholder workshops and training sessions.