Postdoctoral Researcher - AI for Urban Heat & Human Resilience: Smarter Risk Intelligence for a Future-Ready Dubai

Job Description

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.

Education & Experience

• PhD (completed or near completion) in Computer Science, Data Science, Climate Science, GIS, Environmental Engineering, Urban Informatics, or related fields.
• Demonstrated experience in AI/ML modeling and geospatial analytics.
• Experience working with satellite remote sensing datasets.
• Strong publication record in peer-reviewed journals.
• Experience in collaborative academia–government or academia–industry projects.

Technical Skills

• Proficiency in Python/R for machine learning and spatial analysis.
• Experience with GIS platforms (ArcGIS, QGIS, Google Earth Engine).
• Familiarity with remote sensing data processing workflows.
• Strong quantitative skills in statistical modeling and index construction.
• Experience designing and conducting survey/interview-based or field-based research (preferred).

Compensation

Application Process

• Interested candidates should submit:
• A detailed CV highlighting academic and research experience.
• A cover letter outlining interest in urban heat resilience research and relevant expertise.
• Two academic or professional references.
• Evidence of prior publications, research outputs, or technical portfolio.
• Applicant should be based in the UAE and should have a valid residence visa