Our program uses a suite of quantitative spatial modeling approaches, decision support tools, and data visualization products to understand impacts of stressors on coastal ecosystems and to inform coastal ecosystem management. Primary focus areas include (1) developing quantitative spatial predictive models of resource distribution and habitat use for coral species on the Endangered Species List, (2) using data sets of variable spatial and temporal scales (e.g., long and short-term, large and small-scale) to estimate population trends through space and time, and (3) applying analytical techniques for evaluating predictors and sampling design.
This position will work with a team of scientists in Beaufort, as well as with colleagues at the NCCOS Biogeography Branch and other project collaborators from multiple NMFS offices.
Applicants should have a Ph.D. in quantitative ecology, biology, biostatistics, statistics, or related field, along with (1) demonstrated experience applying Bayesian and frequentist approaches to statistical analysis of spatial data sets (e.g., Bayesian hierarchical models, occupancy models, mixed-effects models, GAMs, BRTs, GLMs, resource selection functions); (2) demonstrated ability to script in R; and (3) demonstrated publication and communication of science, ability to collaborate across disciplines. Preferred qualifications include experience in high-performance computing (e.g. MCMC, STAN, JAGS, cloud computing) and version control software (e.g., Github). Familiarity with ecological systems or coral reefs is a plus.
Marine ecology; Statistical modeling; Quantitative ecology; Species distribution modeling; Coral reef ecology;