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Postdoctoral Research, Arctic Ecosystem Modeling, Alaska Fisheries Science Center

Alaska Fisheries Science Center is working towards understanding the impact of loss of sea ice in the Chukchi and Beaufort seas ecosystems. This work is especially timely because of continued ocean warming and apparent acceleration in loss of sea ice. Loss of sea ice has the potential to impact species distributions, life history and physiology; food web productivity, structure and energy transfer; and predator-prey interactions. RPP and our partners have field and laboratory data on multiple components of the Arctic ecosystems including phytoplankton, zooplankton, ichthyoplankton, benthic and pelagic fish, epibenthic invertebrates, seabirds and marine mammals. This wealth of ecosystem information is available for a synthesis of data to examine climate-mediated changes in ecosystem dynamics, structure and functioning. In particular, recent analytical developments allow us to integrate data across trophic levels and fit both population sizes and ecosystem rates in a joint spatio-temporal model. These then allow population sizes and ecosystem rates to be extrapolated across space, leveraging both local and nonlocal correlations among variables, and summed across space to measure changes with appropriate uncertainty. Results can then be used to measure overlap between ecosystem components and human activities, and to optimize future surveys given proposed objectives and scientific constraints.

  • Job Type: Post-doc
  • Application deadline: 11/01/2022
  • Organization: NOAA's Alaska Fisheries Science Center
  • Qualifications: Candidates should have attained a Ph.D. in fisheries, statistics, oceanography, or related field within the last five years. Strong quantitative abilities and good written and oral communication skills are required. Experience in recruitment dynamics, ecosystem function, and/or mechanistic processes are encouraged. Candidates should have experience with analyzing data sets and experience in statistical programming languages such as R. Similarly, candidates will ideally have experience in (or competence quickly learning) spatial and multivariate statistics, experience with advanced packages for fitting nonlinear models (R package development, and/or nonlinear optimization involving ADMB/TMB/Stan), and survey optimization. Interested candidates will be offered opportunities to participate in at-sea research. Mentors for this research would be Drs. Libby Logerwell and James Thorson.
  • How to apply: Online
  • Location: Seattle, WA
  • Web address:

Contact Information:
Elizabeth Logerwell
NOAA's Alaska Fisheries Science Center