Graduate Research Assistant - AI for Urban Heat & Human Resilience: Smarter Risk Intelligence for a Future-Ready Dubai

Job Description

Graduate Research Assistant (Gra)

1. Research Support & Technical Development

• Assist in deploying and monitoring field sensors during ground-truth validation campaigns.
• Assist in processing and analyzing satellite datasets (MODIS, Sentinel, Landsat) for Land Surface Temperature (LST) mapping.
• Support machine learning model development for urban heat analysis and spatial risk modelling. Contribute to data cleaning, feature engineering, and geospatial visualization tasks.
• Assist in developing components of the Heat Vulnerability Index (HVI).
• Support preparation of technical reports, research documentation, and datasets.
• 2.
• Establishment of the AI for Resilient Cities Lab
• A major responsibility of this role will be supporting the setup and operationalization of the AI for Resilient Cities Lab, including:
• Coordinating the physical setup of the lab space (equipment arrangement, sensor setup, computing infrastructure, display systems).
• Assisting in procurement tracking and installation of hardware (e.g., environmental sensors, GPUs, thermal cameras if applicable).
• Developing lab documentation, safety guidelines, workflow templates, and onboarding materials.
• Supporting the creation of demonstration dashboards and visualization screens for visitors and stakeholders.
• Maintaining lab datasets, servers, and research repositories.
• Plan and coordinate urban heat and climate resilience hackathons, workshop, and trainings.
• Prepare presentation materials, lab demonstrations, and technical walkthroughs.

Education & Experience

• Currently pursuing or completed Master’s degree in Computer Science, Data Science, GIS, Environmental Science, Engineering, Urban Informatics, or related fields.
• Proven-track record of academic excellence
• Interest in climate resilience, urban sustainability, and AI applications.

Technical Skills

• Proficiency in Python or R for data analysis.
• Basic knowledge of machine learning concepts.
• Familiarity with GIS tools (ArcGIS, QGIS, Google Earth Engine preferred).
• Experience working with datasets and dashboards.
• Basic understanding of remote sensing is an advantage.

Compensation

Application Process

• Interested candidates should submit the following:
• A detailed CV highlighting academic and research experiences.
• A cover letter explaining your interest in the position and relevant skills.
• Two academic or professional references
• Any evidence of experience to support the application
• Academic transcripts
• Portfolio/GitHub (if available)
• Applicant should be based in the UAE and should have a valid residence visa