USA – Postdoc and PhD in AI & Remote Sensing at The University of Texas at Austin

University: The University of Texas at Austin

Country: United States

Deadline: Not specified

Fields: Remote Sensing, Computer Science, Data Science, Environmental Science, Ecology

Are you passionate about leveraging artificial intelligence and cutting-edge remote sensing technologies to address urgent ecological and agricultural challenges? Do you aspire to contribute to sustainable solutions for environmental monitoring while advancing your academic and research career at a world-class institution?

The Dao ReSEIL Lab at The University of Texas at Austin is seeking outstanding candidates for both postdoctoral and graduate (PhD/MSc) positions in the application of AI and remote sensing to ecology and agriculture. These opportunities are ideal for researchers who wish to integrate advanced computational approaches with environmental science to make a tangible impact on the future of our planet.

About The University Or Research Institute

The University of Texas at Austin (UT Austin) stands as one of the leading public research universities in the United States, renowned for its rigorous academic environment, innovative research, and vibrant campus life. Located in the heart of Austin, Texas—a city celebrated for its dynamic tech industry, cultural diversity, and quality of life—UT Austin is consistently ranked among the top universities globally. The Department of Integrative Biology, home to the Dao ReSEIL Lab, fosters interdisciplinary collaborations that bridge the gap between biological sciences and emerging technologies. Students and researchers at UT Austin benefit from access to world-class facilities, a supportive academic community, and a city that is a hub of innovation and environmental awareness.

Research Topic and Significance

The primary focus of these positions is the application of artificial intelligence, computer vision, and advanced data science techniques to analyze multi-source remote sensing data—including hyperspectral, multispectral, thermal, and LiDAR data from ground robots, drones, and satellites. This research addresses some of the most pressing ecological, agricultural, and environmental challenges of our time, such as monitoring environmental stress, understanding plant-environment interactions, and managing natural resources sustainably.

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Also See

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• USA – PhD in Environmental Engineering at Michigan State University

In an era marked by rapid climate change and increasing demand for sustainable agriculture, the ability to accurately map and monitor environmental stressors is critical. By developing large deep-learning models and integrating AI-driven analytics, the Dao ReSEIL Lab aims to provide actionable insights that will inform policy, improve agricultural productivity, and enhance ecosystem resilience.

Project Details

The Dao ReSEIL Lab, led by Dr. Phuong Dao, is housed within the Department of Integrative Biology at UT Austin. The lab specializes in the integration of remote sensing, environmental intelligence, and AI to solve complex problems at the intersection of natural and agricultural systems. Candidates will have the opportunity to work with state-of-the-art remote sensing data (hyperspectral, multispectral, thermal, LiDAR) and develop independent projects in collaboration with Dr. Dao. The lab encourages innovation and supports independent research initiatives that align with its core mission.

For the postdoctoral position, the emphasis is on characterizing and understanding interactions between natural and agricultural systems and their changing environments. For the PhD/MSc position, the focus is on developing and applying AI and deep learning models to map and monitor environmental stress impacts.

Candidate Profile

Postdoctoral Position

The Dao ReSEIL Lab is seeking highly motivated candidates with a strong academic background and a passion for interdisciplinary research. Specific qualifications include:

– PhD in remote sensing, geography, environmental science, computer science, data science, plant biology, ecology, or related fields

– Strong background in remote sensing and geospatial data analysis

– Proficiency in computational/analytical methods, machine learning, and image analysis

– Experience With R And Python Programming Preferred

– Background in plant physiology or biochemistry is a plus

PhD/MSc Position

– BSc in computer science, remote sensing, geospatial science, environmental science, or related fields

– MSc degree (for PhD entry) preferred but not required

– Experience with geospatial data, machine learning, and programming (R, Python, MATLAB, or similar)

– Knowledge in plant biology, ecology, or environmental science is an asset

Ideal applicants are independent thinkers with a collaborative mindset, capable of integrating computational skills with environmental applications. A demonstrated interest in addressing real-world ecological and agricultural problems through technology is highly valued.

Application Process

To Apply, Candidates Should Prepare The Following Documents

– Cover letter

– Curriculum Vitae (CV)

– Transcripts

– One representative publication

All documents should be combined into ONE PDF file, named as follows:

– For postdoctoral applicants: YourSurname_Postdoc_Application.pdf

– For graduate (PhD/MSc) applicants: YourSurname_Grad_Application.pdf

Applications should be submitted according to the instructions provided in the original advertisement. Please refer to the official advertisement for application details.

About

Applications are reviewed immediately and positions remain open until filled. For further information and to find out more about the positions, please visit the LinkedIn post by Dr. Dao:

https://www.linkedin.com/posts/phuong-dao-a546b236_joining-the-university-of-texas-at-austin-activity-7379552259761737728-0-HV

Conclusion

These positions at The University of Texas at Austin offer a unique opportunity to work at the forefront of AI, remote sensing, and environmental science. If you are eager to contribute to impactful research that addresses critical issues in ecology and agriculture, and wish to advance your academic career in a supportive and innovative environment, we encourage you to apply. Stay tuned for more opportunities in this field by following the Dao ReSEIL Lab and related academic channels.

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