Vanderbilt University Fully Funded PhD Position in Vegetation Remote Sensing and Urban Ecology – Fall 2027

Overview

Vanderbilt University offers a fully funded Doctor of Philosophy position in the Department of Earth and Environmental Sciences, operating through the Meng Lab. The position focuses on vegetation remote sensing, urban ecology, and environmental change, and begins in Fall 2027. The selected researcher will examine how urban conditions such as rising temperatures, artificial light pollution, and air pollution impact vegetation dynamics and human health exposures. The research environment integrates NASA satellite observations, advanced geospatial analysis, and artificial intelligence and machine learning methods.

Who can apply

The opportunity is open to prospective doctoral researchers with a strong quantitative and scientific background who are motivated to conduct independent research. Applicants need a solid academic foundation in land-surface processes, vegetation remote sensing, or urban ecology, alongside proficiency in spoken and written English. Candidates should be interested in interdisciplinary ecological research, environmental change, and computational methods. Relevant experience in GIS, Python programming, machine learning, environmental modelling, satellite data analysis, or remote sensing is particularly useful.

What you get

The successful applicant receives a fully funded doctoral position within the Department of Earth and Environmental Sciences at Vanderbilt University. The role provides opportunities to work with advanced scientific technologies, participate in innovative research projects, and contribute to high-impact scientific publications. The doctoral student also benefits from research mentoring, professional training, and career development within an interdisciplinary research group.

Requirements

Applicants must submit their applications through the Department of Earth and Environmental Sciences at Vanderbilt University by the specified closing date. Candidates are expected to demonstrate strong quantitative and programming skills, the ability to work with scientific data and computational methods, and an interest in developing innovative approaches to ecological challenges.

Key dates

The application deadline is 1 January 2027. The position is expected to commence in Fall 2027.