Postdoctoral Research Associate Jobs in Virginia

Postdoctoral Associate
Job no: 524417
Work type: Research Faculty
Senior management: Natural Resources
Department: Fish and Wildlife Conservation
Location: Blacksburg, Virginia
Categories: Research / Scientific, Natural Resources
Job Description
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 that can be used to estimate lost mussel service-years and replacement value for damage cases. The project will focus on native mussels and the REA model will accommodate life history knowledge about this unique animal group, which has special conservation significance in North America. The ecology and reproduction of mussels provides unique opportunities for developing and testing REA models, including modeling their longevity, breeding age, fecundity, and other life history factors. 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. A main goal of the modelling is to allow for flexibility to inform of a wide variety mussel restoration planning options, including injury quantification, restoration scaling, and incorporating varied mussel life history and demographic scenarios.
Required Qualifications
- PhD in quantitative ecology, natural resource economics, or a related discipline. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
- Experience in programming in Excel and r-script coding in Program R
- Demonstrated scientific productivity, including peer-reviewed publications
- Strong statistical modeling and analytical skills
- Demonstrated ability to work independently and collaboratively
Preferred Qualifications
- Proficiency with programming in R
- Experience with Leslie matrix-based demographic modeling
- Excellent writing and speaking skills
- Emphasis on aquatic ecosystems and freshwater mussel restoration
Pay Band
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Appointment Type
Restricted
Salary Information
Review Date
2/6/23
Additional Information
The successful candidate will be required to have a criminal conviction check.
About Virginia Tech
Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.
Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.
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Advertised: January 25, 2023
Applications close:
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