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POSITION: Postdoctoral Research Associate – 

Resource Equivalency Modeling to Restore Freshwater Mussels

LOCATION: Virginia Tech, Department of Fish and Wildlife Conservation, Blacksburg, Virginia

SALARY: $45,000-50,000/year + benefits   

PROJECT DURATION: Once filled, the position is for 2 years

PROJECT TITLE: Development of resource equivalency analysis (REA) models for restoring freshwater mussels for NRDAR cases

POSITION SUMMARY: The Department of Fish and Wildlife Conservation at Virginia Tech is accepting applications for the position of Postdoctoral Research Associate. Research will focus on developing and publishing a resource equivalency analysis (REA) model for freshwater mussels for use in the Department of Interior’s (DOI) Natural Resource Damage Assessment and Restoration (NRDAR) cases. Accomplishment of this objective will provide NRDAR program managers and the general wildlife management community with REA modeling tools to estimate lost mussel service-years and replacement value, to be used in legal cases. The project will focus on native mussels and the model will incorporate life history knowledge of this unique group, which is highly imperiled in North America. Mussel ecology provides unique opportunities for developing and testing REA models, including modeling their longevity, breeding age, fecundity, and other traits. The incumbent will work collaboratively with Virginia Tech’s Dr. Paul Angermeier and Dr. Jess Jones and DOI economists to develop Leslie matrix-based models utilizing Excel and r-script coding in Program R, then validate and publish the models A main modeling goal is to inform a wide variety mussel restoration planning options, including injury quantification, restoration scaling, and assessment of selected life history and demographic scenarios. 

REQUIRED EDUCATION/EXPERIENCE: PhD in quantitative ecology, natural resource economics, or related discipline, with desired emphasis on aquatic ecosystems and freshwater mussels; demonstrated scientific productivity, including peer-reviewed publications; strong statistical modeling and analytical skills, including programming in Excel and R; demonstrated ability to work independently and collaboratively; excellent writing and speaking skills.

HOW TO APPLY: Electronically send a) cover letter describing interest and qualifications, b) vitae including all academic experience and employment history for past 5 years, c) copies of college transcripts, and d) names of three references, with phone numbers and email addresses, to Dr. Paul Angermeier (540-231-4501; Review of applications will begin March 6, 2023 and continue until the position is filled. Additional information about the position is available here: