Posting Title Post-Master's Research Associate in Quantitative Ecologist Reference Code ORNL14-11-ESD Eligibility Requirements
* Degree: Currently pursuing a Master's Degree or have received this Degree within 60 months. * Affirmation: I certify that I have completed coursework towards a degree in science, technology, engineering, mathematics, or a related field. Description ORNL has long history of leadership in ecological modeling research, including agent-based modeling to support science-based fisheries conservation efforts. This project will use an individual-based demographic and genetic population model (IBM+G) for white sturgeon in the Snake River, Idaho to conduct a risk-benefit analysis of two conservation alternatives: 1) operating a conservation hatchery and 2) repatriating larval sturgeon. Repatriation is a progressive new strategy that may have significant advantages over providing hatchery support in terms of protecting genetic diversity and avoiding removal of broodstock. This is a unique opportunity to make a real difference in the conservation of fish species at risk and in the evaluation of a new conservation practice. The successful candidate for this position will 1) modify an existing population viability analysis model to represent aquaculture and repatriation scenarios, 2) build linkages with reservoir water quality modeling scenarios for Brownlee Reservoir, 3) perform simulations to compare conservation measures under different future water-quality scenarios, and 4) document and analyze results. Because use of the existing IBM+G model is required to be used to satisfy a Conservation Plan, no major changes in the model can be made other than those required to address the research question. Although this position will primarily focus on completing the Snake River white sturgeon project, there will also be opportunities to contribute to an ongoing project to model the viability of the threatened Snake River fall Chinook salmon ESU and to interact with fisheries scientists, ecologists, engineers and economists that support DOE Renewable Energy research. Publication of results in the peer-reviewed scientific literature is possible and funding will be made available to attend one scientific meeting to present results during the second year of this two year position. Qualifications The successful candidate must have a Master's degree in the biological, mathematical, or computer sciences (or related field) with course work in statistics and population genetics. A detail-oriented work focus and strong organizational skills are required. Experience with C and R languages is required. In addition, candidates with other quantitative skills (statistics, Python, high-performance computing, GIS, version control software) are encouraged to apply. Applicants cannot have received the most recent degree more than five years prior to the date of application and must complete all degree requirements before starting their appointment. https://www3.orau.gov/ORNL_TOppS/Mentor/PostingApplications?PostingId=510
