Summary:
The USGS Eastern Ecological Science Center is searching for a highly motivated and talented quantitative researcher or statistician to work on (as a co-author) a suite of ecology, spatial modeling, and avian disease research. The Eastern Ecological Science Center, formerly Patuxent Wildlife Research Center, is a world-renowned research institution located within 30 minutes of Annapolis, Baltimore, and Washington, D.C. This position will consist primarily of office work focusing on understanding the role of wild waterfowl in the spread and persistence of avian influenza viruses and will require understanding of both animal movement as well as disease ecology. The selected candidate will also be asked to regularly consult on a variety of other projects including waterbird and habitat restoration efforts in the Chesapeake Bay. There would be opportunities to participate in field work if desired, though this is not a requirement of the position. Additional information about our broader scope of ongoing work can be found at https://www.usgs.gov/staff-profiles/diann-prosser

Types of services required: Examples of working tasks include designing and/or performing analyses to answer questions related to wild bird ecology and disease transmission. For instance, ongoing projects include informing agent based models with quantitative telemetry data, prevalence rates, and pathobiology parameters. In addition to the main projects included in this position, the successful applicant will be asked to regularly consult on analytical methods for previously collected data as well as the design of new studies. The selected candidate will work with lab members of various backgrounds (B.S. to postdoc) and assist in experimental design and in guiding selection of analytical methods. Knowledge of R is critical, with experience in ArcGIS or other GIS platforms being beneficial. The candidate must be willing to assist with various projects other than those mentioned above, as this lab works on a variety of topics.

Required expertise/skills:
The ideal candidate has a doctoral degree in Ecology, Wildlife Biology, Natural Resources, GIS, Statistics, or a related field. The candidate must be highly motivated and able to work independently, with a strong track record of producing published research. Experience with both frequentist and Bayesian methods is highly desirable, as is demonstrated proficiency with a wide breadth of analytical methods for ecological analyses.

Eligibility requirements: To be eligible for a contract position, candidates must be eligible for employment within the United States.
Description of working conditions: Work will be performed primarily in the office environment located in Laurel, Maryland with extended periods of computer use. If interested, the selected candidate may have the opportunity to participate in field work though this is not a requirement of the position.

Compensation: Annual salary for this position is ~ $60K depending on experience. This is a contract position, and not federal employment. Employee is responsible for all costs of transportation to and from the principal duty station location (i.e., to the office or main field site). The Government does not provide housing, meals or other living expenses while working at the principal duty station. While the duty location is Laurel, MD there is some flexibility for telework or remote work.

Approximate start date for the position is Msrch 2023, although there is some flexibility based upon the needs of the selected candidate. This is a one-year position (1920 hours) with aims for multi-year extension based upon funding and performance.

Principal Duty Station: USGS Eastern Ecological Science Center, 12100 Beech Forest Road, Laurel, MD 20705.

How to apply: Send the following to PWRC_application@usgs.gov by January 15, 2022 with “Quantitative Ecologist” in the Subject header:

1. Cover letter, resume, writing sample, and 3 references in a SINGLE Word or PDF document titled with your name (eg. JohnDoe.doc or JaneSmith.pdf). Applications will be reviewed as received.