Post-doctoral research appointment using data integration to model bird responses to local and landscape patterns across Missouri grasslands

Description:  We are seeking a post-doctoral associate to use quantitative approaches to model  grassland bird patterns at landscape and local scales across Missouri. Analyses will involve the integration of local distance sampling data with large-scale survey data such as breeding bird survey, eBird, and state surveys to evaluate relationships between grassland bird densities and management practices (e.g., burning and grazing), map distributions of grassland birds across the entirety of the Southwest, Kansas City, and Northwest regions of Missouri in relation to landscape factors related to grassland habitat, and examine priority landscapes for investment in public or private lands conservation efforts. The postdoc will use state of the art hierarchical and integrative methods to combine from multiple scales for a suite of grassland bird species of concern. They will also incorporate novel data on climate and landcover (e.g., warm-season vs. cool season grasses) to understand examine the relative importance of local management and landscape condition for bird populations.

Qualifications:  Ph.D. in statistics, wildlife ecology or closely related field; Skills in Program R; Demonstrated excellence in verbal and written communication; Ability to work independently and as part of a research team. Preferred candidates will possess: skills in JAGS, NIMBLE, Stan; experience forming and running integrated and abundance/occupancy models; knowledge and experience in avian ecology. Preference will also be given to candidates that possess a demonstrated record of publishing.

Salary:  $50,000 per year plus full benefits. Appointment is for 2 years. 

Application reviews will begin March 1st and remain open until the position is filled.  The anticipated start date is July/August 2023. 

To apply, email letter of interest, CV, and contact information for three references (preferably as one pdf) to Thomas Bonnot (bonnott@missouri.edu)