*Revised* Postdoctoral Scholar, Interdisciplinary Data Science, College of Engineering [R0144891]

The University of Nevada, Las Vegas (UNLV) appreciates your interest in employment. We ask that you keep in mind the following when completing your application:  

• Once you start the application process you cannot save your work. Please ensure you have all required attachment(s) available to complete your application before you begin the process.  
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The University of Nevada, Las Vegas invites applications for Postdoctoral Scholar, Interdisciplinary Data Science, College of Engineering [R0144891].

*Revised* ROLE of the POSITION

The Howard R. Hughes College of Engineering at UNLV invites applications for a full-time, 12-month, Postdoctoral Scholar of Interdisciplinary Data Science, commencing as early as September 1, 2025. The position is renewable for up to two additional years (3 years total), pursuant to availability of funds. This postdoctoral scholar will work on research topics related to AI-Driven Wildfire Detection Using Drones and Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI-Based Wildfire Smoke and Air Quality Monitoring; Deep Learning for Post-Wildfire Damage Assessment.

PROFILE of the OFFICE OF POSTDOCTORAL AFFAIRS (OPA)

The mission of the UNLV Office of Postdoctoral Affairs (OPA) is to enhance and support postdoctoral training and career development; serve as the central resource office for postdoctoral questions and issues for faculty, supervisors, mentors, and prospective and current postdocs; build a community for all UNLV postdocs; and provide professional development programs and networking events for postdocs.

UNLV currently employs postdoctoral scholars across a wide range of disciplines. Learn more about UNLV’s postdoctoral scholars.

MINIMUM QUALIFICATIONS

This position requires a PhD Degree in Computer Science, Electrical Engineering, Environmental Engineering, Geospatial Science, Data Science, Computer Engineering, or a closely related field, with an emphasis on machine learning, AI, remote sensing, computer vision, or interdisciplinary data science applications to environmental ch