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Overview The National Ecological Observatory Network (NEON) is a $430 million dollar observatory project dedicated to understanding how changes in climate, land use and invasive species impact ecology. For the next three decades NEON will collect a comprehensive range of ecological data on a continental scale across 20 eco-climatic domains representing US ecosystems. NEON will use cutting edge technology including an airborne observation platform that will capture images of regional landscapes and vegetation; mobile, re-locatable, and fixed data collection sites with automated ground sensors to monitor soil and atmosphere; and trained field crews who will observe and sample populations of diverse organisms and collect soil and water data. A leading edge cyber-infrastructure will calibrate, store and publish this information. The Observatory will grow to 300+ personnel and will be the first of its kind designed to detect and enable forecasting of ecological change at continental scales. Summary: NEONs measurement systems collect a wide variety of data obtained from instruments, gathered by observations of several organismal taxa, and derived from samples from terrestrial and aquatic ecosystems, as well as data from airborne hyperspectral, LiDAR, and high-resolution optical imaging. In addition, NEON is contributing to, and leveraging from, community-built models of land surface dynamics, aquatic and terrestrial biogeochemistry, hydrology, and vegetation canopy structure. All of these efforts are geared toward providing high-quality data products to NEONs user communities, both as value-added scientific contributions to understanding driver-response feedbacks in ecosystems, but also as examples of how to utilize NEON data and data products for leveraging NEON as a platform for such studies. A major component of this effort is architecting statistically defensible algorithms contributing to our understanding of these processes, and reporting these approaches in conjunction with NEON data products. Such approaches run the gamut of applications, from simple methods to gauge data quality to highly advanced methods utilizing networked models or model-data fusion. The Staff Scientist-Ecological Statistics, will utilize their extensive expertise in statistical methods and deep background in the environmental, ecological, or earth sciences, to drive the development and implementation of community-vetted, state-of-the-art statistical methods as applied to the universe of NEON data products. This will involve working closely with all NEON science teams, including the Cyberinfrastructure, Systems Engineering, and Engineering teams, to develop, implement and document these approaches. Further, the incumbent will work as a resource for the NEON Science Division, utilizing interdisciplinary statistical methodologies applied to NEON scientific goals, broadly applied across its diverse measurement systems. This position reports to the Assistant Director Data Products. Essential Duties and Responsibilities: Contribute to the definition and optimization of NEONs approach to continental scaling of ecological processes. Help refine NEONs approach to addressing high-level science questions, such as those enabling research into terrestrial-aquatic biogeochemical links, gradient themes, and combined use of biogeochemical and microbial data, utilizing cutting-edge spatial, temporal, and spatiotemporal statistical techniques, such as hierarchical modeling, multi-model inference, and data assimilation. Develop production-grade, state-of-the-art algorithms for combining heterogeneous data and data products from NEON measurement and observation systems, spanning multiple spatial and temporal scales. Integrate deeply across NEON science teams, effectively leveraging and incorporating planned and existing scientific designs into algorithmic architecture. Contribute to the design, implementation, and operationalization of statistical techniques used by other NEON science and engineering teams. Coordinate and collaborate with Cyberinfrastructure and Systems Engineering teams. Create and make presentations at professional meetings, and reports. Travel to national conferences (1-3 times per year). Required Education, Experience, Knowledge, Skills: Ph.D. in Statistics, Ecology, Biology, Environmental or Earth Sciences, Astronomy, or Physics. Three or more years experience. Extensive knowledge of and experience with foundational statistics, both frequentist and Bayesian. Extensive knowledge of and experience of two or more ecological sciences as relevant to NEON. Peer-reviewed journal publications and high standing in the statistics and ecology communities. Extensive knowledge of statistical inference and its application to ecological sciences. Extensive knowledge of spatial, temporal, and spatiotemporal statistical techniques. Experience with coupling data at multiple spatial scales to a variety of process and statistical models. Experience with uncertainty quantification. Experience with hierarchical and/or Bayesian modeling. Experience with statistical approaches to filtering, such as particle filters or the universe of Kalman filtering techniques. Have excellent communication and interpersonal skills. Preferred Education, Experience, Knowledge, Skills: Knowledge and experience with visualization techniques.
