Postdoc Research Associate

Developing quantitative state and transition models to improve ecosystem management

Project Description: San Diego State University, in collaboration with the University of Arizona, is seeking a postdoctoral researcher with strong quantitative skills to take a lead role in a project connecting rangeland conservation practice data to state-and-transition models (STMs) and ecological site descriptions (ESDs) in the Southwestern U.S. The project aims to develop robust methods for integrating empirical data into STMs. This work will involve compiling and verifying existing practice data, field assessments of ecological states, and incorporating remote-sensed and practitioner-informed data. Key methods include multistate modeling, data simulation, and scenario-based prediction. The postdoc will: lead development of quantitative STM methods for data-informed management; author at least two peer-reviewed manuscripts; and prepare technical reports.

Required Qualifications:

● PhD in a relevant field (e.g., Biology, Ecology, Statistics, Geography, Rangeland Ecology, etc.)
● Strong quantitative and advanced programming skills in R
● Proven ability to publish scientific research and communicate findings to diverse audiences
● Experience leading manuscript preparation for peer-reviewed journals
● Excellent written and verbal communication skills
● Ability to work independently and collaboratively
● Strong work ethic and enthusiasm for learning

Preferred Qualifications:

● Previous experience with Bayesian and/or integrated data models
● Familiarity with data simulation and model development
● Interest in integrating diverse data sources into cohesive models
● Comfortable working with complex or inconsistent data set

● We are committed to fostering an inclusive,  supportive, and collaborative work environment. We welcome all backgrounds and value diverse perspectives as essential to advancing science and conservation

Duration: 2 years, contingent upon performance

Anticipated Start Date: October 13, 2025 (earliest)