PhD in Mathematics, Applied Mathematics, Network Analysis, and AI for Conservation
Arizona State University (ASU) is inviting applications for a PhD position in mathematics, applied mathematics, network analysis, explainable artificial intelligence, machine learning, and the use of AI in conservation. The opportunity is associated with the ISEE program and involves research areas such as mathematical biology, population dynamics of migratory species, and the development of novel modeling methods for complex biological systems. The position is supervised by Assistant Professor Sheila Miller Edwards, whose research spans mathematical biology, set theory, and philosophy, with a focus on modeling long-lived, migratory species like leatherback sea turtles.
Applicants are expected to have a strong background in mathematics, applied mathematics, computer science, or related fields, and a keen interest in interdisciplinary research involving AI and conservation. The application process requires submission of an academic CV and a 500-word statement outlining research and educational background, graduate school research interests, and how the chosen graduate program and faculty mentor align with the applicant's goals. Additionally, applicants should describe how they plan to advance the ASU Charter during their graduate studies.
For full consideration, application materials must be submitted to the proposed ISEE primary faculty mentor by January 1, 2026. Following selection by the ISEE program committee, students will apply through one of the relevant ASU graduate programs and must meet the specific admission requirements of their anticipated PhD program home. The research environment at ASU offers opportunities to engage in cutting-edge work at the intersection of mathematics, AI, and conservation, with mentorship from faculty like Dr. Sheila Miller Edwards.
For more information, visit the faculty profile at
ASU Search
or connect with the announcer, Lamini NURUDEEN, on
LinkedIn
. Application details and further instructions can be found at the provided links.