Post Doctoral Researcher in Remote Sensing

University of Doha for Science and Technology UDST

The Postdoctoral Researcher will contribute to developing an early warning system for dust and air quality prediction in Qatar. The project integrates remote sensing, geospatial data science, and predictive modeling to create real-time forecasting tools supporting public health resilience and climate adaptation. The researcher will work within a multidisciplinary team at UDST and collaborate with national and international stakeholders, including government agencies, industry partners, and academic institutions

Responsibilities

• Design and implement a comprehensive data collection strategy integrating natural, built, and societal factors using satellite imagery, ground sensors, and urban datasets.
• Develop predictive models for dust events, particulate matter (PM) concentrations, and air quality dynamics using geospatial regression, Getis-Ord Gi*, and Copula-based statistical techniques.
• Build a cloud-enabled predictive framework (Google Earth Engine, AWS, or Azure) automating data cleaning, processing, and forecasting.
• Conduct hotspot and temporal trend analyses to assess relationships among soil moisture, wind, vegetation cover, and PM concentrations.
• Generate high-resolution environmental maps of dust susceptibility and vegetation-sheltering efficiency.
• Collaborate on extending Quantitative Microbial Risk Assessment (QMRA) models to evaluate health impacts associated with airborne fungal spores.
• Support the design of interactive dashboards or decision-support systems for stakeholder engagement.