Postdoctoral Associate

Job Description

The increased cost and effort required for monitoring catastrophic disturbances in southeastern forests has led to a need for improved tools for rapid, accurate assessment of timber damage caused by tropical storm systems. A Postdoctoral Associate is being sought to collaborate with Virginia Tech faculty and U.S. Forest Service researchers to pursue advances in model-assisted disturbance estimation methods that leverage data from satellite and aerial remote sensing along with post-hurricane field surveys coordinated through the Forest Service Forest Inventory and Analysis (FIA) program. The selected participant will pursue research evaluating a number of competing data sources for suitability in model development, identifying tradeoffs in temporal, spatial, or sensor information where different data sources provide information correlated with different storm-damage related variables of interest. The project participant will develop expertise in working with large data sets to answer questions relevant to forest management and policy in one of the world’s most actively managed forest ecosystems, as well as sharing findings with other scientists and a range of stakeholders at conferences and professional meetings.

Under the guidance of a small team of faculty supervisors and mentors, the selected participant will further their professional development by (a) in-depth study of a dynamic and societally important regional forest management challenge, (b) gaining experience with decision support for forest timber and carbon assessment and management at multiple scales, (c) furthering collective understanding of complex natural resource management and policy challenges in the U.S. Southeast, (d) pursuit of research through to publication at the intersection of natural resource management and carbon dynamics in managed and unmanaged forests.

Required Qualifications

- A Ph.D. in natural resources, forestry, remote sensing, or other suitable discipline with emphasis on the application of statistics to problems involving multiple data sets from extensive field surveys and remote sensing. PhD awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
- Demonstrated skills in working with large datasets from multiple sources, including publicly-available data from sources such as airborne and/or spaceborne remote-sensing platforms to field survey data such as those conducted as part of national forest Inventories.
- Excellent spoken and written English language skills, with a demonstrated ability to deliver technical information to peer audiences in spoken or written English.
- Experience with technical writing, especially in publishing research findings in peer-reviewed English-language publications.
- Experience or aptitude in working in high-performance computing platforms/environments such as Linux and applications/languages such as R or Python.

Preferred Qualifications

Preferred qualifications and interests for the ideal applicant include:
- ability to review and synthesize scientific literature from fields of forest biometrics, geomatics, and applied statistics;
-strong analysis skills, including the ability to develop, document, and implement procedures for working with large datasets in a scientific-computing environment;
- ability to focus on research goals that inform policy-related goals and management decisions; - experience in technical and scientific writing and reporting; and
- a strong willingness to work in a collaborative environment that spans academic, agency, and private-sector cooperators.

Appointment Type


Salary Information

Commensurate with experience

Review Date

February 1, 2021

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 veteran 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.

If you are an individual with a disability and desire an accommodation, please contact Mary Williams at during regular business hours at least 10 business days prior to the event.

Advertised: December 22, 2020
Applications close: