The University of Maryland in collaboration with the USGS Eastern Ecological Science Center (EESC) is searching for a highly motivated and talented individual to work as a postdoctoral researcher on a project focused on the decision analytic process (i.e., structured decision making) to better guide management of potential highly pathogenic avian influenza (HPAI) disease spread at the wild bird – agriculture interface. The postdoctoral researcher will build on our newly developed statistical methods to investigate avian influenza transmission risk in the United States by identifying at-risk areas for introduction or establishment of HPAI viruses. Focus may also include parts of Asia and Europe, depending on subsequent funding. The position will work closely with a cross-cutting and highly productive team of wildlife biologists, disease ecologists, quantitative ecologists, and decision analysts associated with the newly formed Disease Decision Analysis and Research (DDAR) group at the Eastern Ecological Research Center (formerly, the Patuxent Wildlife Research Center). DDAR was formed to focus on emerging infectious diseases that have been identified by State and Federal management agencies as high-priority needs and that might challenge threatened and endangered species recovery, captive and wild population management, and human health. Current work in DDAR focuses on a diversity of disease systems including CWD, SARS-CoV2, avian influenza, amphibian pathogens, tick-vectored diseases, and white-nose syndrome in bats. The selected candidate for this position will work directly with Dr. Diann Prosser (USGS) and Dr. Jennifer M. Mullinax (UMD), Dr. Mike Runge (decision analysis guidance) and the DDAR team, as well as with our professional collaborators across the country and globe. In-lab interactions include other post-docs, long-term technicians, graduate students, and interns.
The ideal candidate has a doctoral degree in Ecology, Wildlife Biology, Natural Resources, GIS, Statistics, Mathematics, or a related field. The candidate must be highly motivated, able to work independently, and good at communicating within a team. It is critical that the selected candidate have extensive experience in R or other related statistical software, be proficient in GIS, species distribution modeling, and analysis of spatial data. Ability to write peer-reviewed manuscripts is a requirement. Specific experience modeling waterfowl from landscape-scale information is preferred, as is an appreciation for the value of decision analysis and familiarity with analysis / simulation modeling of ecological data. Expertise in wild birds and avian influenza is a benefit, but not required.
The selected candidate must successfully complete a criminal background check as required for access to government computers and properties.
Description of working conditions:
The associate will work closely with agency managers and biologists and local stakeholders to frame the decision problem, modify predictive models, and identify relevant data. Work will be performed predominately in the office environment located in Laurel, Maryland (EESC) and with 1-2 days per week at the University of Maryland, College Park. The potential exists for occasional field work which may require transportation via mid-sized (20-40’) open boats. Extreme weather (hot summers, cold winters, high winds) and uncomfortable environments (biting insects) may be encountered. Extended periods of computer use will be required for this position.
Salary is commensurate with experience including a full, competitive University of Maryland benefit package. Compensation for housing, meals or other living expenses is not provided while working at the principal duty station. Start date is flexible (Feb-March 2022). This position is funded for approximately 24 months with yearly review; extension to 36 months is possible based on fund availability.
How to apply: Send the following to Dr. Diann Prosser at email@example.com by February 28, 2022 with “SDM Postdoc” in the Subject header. Applications will be reviewed as received.
1) Letter of interest, CV with publication list, 3 references, and one peer-reviewed writing example in a SINGLE document titled with your name (eg. DoeJohn.doc or SmithJane.pdf).