Arizona State University (ASU) invites applications for fully-funded PhD positions through the Presidential Graduate Assistantship (PGA) in the Integrative Stewardship of Extreme Environments (ISEE) research cluster. This interdisciplinary opportunity focuses on conservation threats in extreme ecosystems, integrating research across environmental science, biology, computer science, data science, statistics, applied mathematics, and related fields. The ISEE cluster, based in the New College of Interdisciplinary Arts & Sciences, addresses biodiversity and ecosystem health challenges in environments such as oceans, deserts, and urban areas, with a strong emphasis on the reciprocal relationship between ecosystem threats and human well-being.

Students will have the opportunity to work with Dr. Yixuan He and a diverse team of faculty, including Becky Ball, Anthony Barley, Alli Cramer, Nilesh Dixit, Nina Fefferman, Bogdan Gavrea, Chad Johnson, Sreetharan Kanthaswamy, Sheila Miller Edwards, Ashlee Momcilovich, and Vernon Morris. Research areas span environmental justice, planetary health, pest and endangered species, soil biogeochemistry, mathematical modeling, explainable AI, network analysis, remote sensing, data science, machine learning, and genomics. The program encourages innovative approaches to conservation challenges, leveraging advanced computational and analytical methods.

Eligible applicants should have a strong academic background in a relevant discipline and be prepared to submit a CV, transcripts, and a statement of research interests. The position is fully funded, covering stipend and tuition, with additional benefits as per university policy. The application deadline is January 1, 2026. Interested candidates should email Dr. Yixuan He at [email protected] (include 'Presidential Graduate Assistantship' in the subject) and apply to the appropriate PhD program at ASU. More information can be found on the ISEE website and Dr. He's homepage.

Keywords: conservation, extreme environments, biodiversity, ecosystem health, data science, machine learning, mathematical modeling, network analysis, statistics, computer science, applied mathematics, environmental science.