This ad is also available at http://www.neoninc.org/jobs/ecologicalinformatics
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. As part of NEONs mandate to ensure free and open access and interoperability of this data, assuring2 that NEON data products are both standardized and standards-based is a key responsibility of the Data Products team. The Staff Scientist-Ecological Informatics will work to both define and refine NEONs strategy for data, data product, and metadata architecture as applied to the heterogeneous data products NEON will produce. This involves understanding NEONs data and sample acquisition systems, the computational impacts of organizing this information, the scientific drivers for collecting these data, and the communitys needs for this data, weaved through interactions with NEON staff scientists, its Cyberinfrastructure team, and internal and external working groups providing expertise and feedback. The incumbent will also provide high-level expertise in designing, developing, and implementing state-of-the-art tools for finding, utilizing, and analyzing scientific data, as well as providing full documentation enabling provenance and traceability. This position reports to the Assistant Director for Data Products. Essential Duties and Responsibilities: Help guide development of an integrated approach to data and metadata architecture useful and appropriate for NEON data and data products. Contribute to the development of NEONs data and sample acquisition systems architecture, using an understanding and consideration to the computational impacts of organizing the ecological information, the scientific drivers for collecting these data, and community needs for this data. Coordinate and collaborate with NEON staff scientists and engineers to gather requirements for metadata architecture design and implementation. Provide expertise and feedback in designing, developing, and implementing state-of-the-art tools for finding, utilizing, and analyzing scientific data. Prepare and provide full documentation of the rationale for, and design of, data product and metadata architecture. Develop process improvements for organizing diverse ecological data. Investigate and recommend effective techniques to organize, standardize, and deliver comprehensive and diverse NEON data and supporting documentation for diverse audiences. Travel to national conferences (1-3 times per year). Required Education, Experience, Knowledge, Skills: M.S. (Ph.D. Preferred) in Ecology, Environmental or Earth Sciences, Astronomy, Computer Science or Physics. Two or more years experience. Expertise with major data and information technologies and standards, including World Wide Web Consortium (W3C), Information Standards Organization (ISO), Federal Geospatial Data Committee (FGDC), and Open Geospatial Consortium (OGC). Extensive knowledge and experience with biodiversity informatics project architecture, including that of DataONE, LTER, Earth Microbiome Project, and GBIF. Experience with scientific data formats, including NetCDF, HDF, EML, XML, and others. Experience with data structures, such as ISO 19123 and 19109 standards, OGC Common Data Model. Expertise with metadata standards, including ISO 19115, Darwin Core and extensions, FGDC, and NetCDF CF conventions. Experience with scientific data repository architectures, such as USGS EROS, or NASA DAACs. Demonstrable knowledge of modern programming languages, such Java, Python, and C++. Preferred Education, Experience, Knowledge, Skills: Data modeling experience (relational and unstructured). Experience as a user community-facing data provider. Extensive knowledge of data and metadata standards communities, such as ESIP, KNIB. Extensive, advanced understanding of data processing algorithm paradigms, including high-performance computing (parallel, massively parallel, etc.), GPUs, Hadoop ecosystem.
