[ES_JOBS_NET] Environmental Data Science Postdoctoral Fellow, Berkeley Lab

[Christine Wiedinmyer]

https://lbl.referrals.selectminds.com/jobs/virtual-ecosystem-postdoctoral-scholar-932



Berkeley Lab's Energy Geosciences<https://eesa.lbl.gov/our-divisions/energy-geosciences/> Division has an opening for a Environmental Data Science Postdoctoral Fellow. The DOE's Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE<http://ess-dive.lbl.gov/>) is a new data archive for Earth and environmental science data. ESS-DIVE will store diverse datasets from various environmental sciences that include hydrology, geology, ecology, geochemistry, biology, climate and geophysics.

Defining and adopting the right data and metadata standards for these data are active research topics, involving an interdisciplinary community of data scientists, digital librarians and environmental scientists. The project will involve working with the DOE's Environmental System Science (ESS) community as well as the broader earth science informatics community (e.g. NCEAS, AGU, RDA, ESIP) to select or develop metadata and data formats and standards for the diverse data types, build automated parsers to ingest standardized data, enable data integration and use of these datasets in ecosystem models.

The incumbent will join the research and development team working on community standards and extracting data submitted to ESS-DIVE. Challenges to be tackled include, but are not limited to: (1) evaluation of various existing standards/formats for organizing environmental data and metadata (2) development of new community data standards as needed for priority data types; (3) enabling integration of diverse data and their use in ecosystem models (4) automatic parsing and ingestion of data submitted to ESS-DIVE in standardized formats; (5) collaboration with ESS community to enable implementation of these standards. The solutions developed within the postdoctoral project will allow ESS-DIVE users to conduct advanced queries, analytics visualization and modeling on integrated datasets. You will join a dynamic interdisciplinary team based at LBNL and will work closely with data scientists, digital librarians and a diverse set of environmental researchers including field scientists, modelers and experimentalists. LBNL is a renowned center of scientific expertise in many facets of ecosystem-related fundamental and applied science.



What You Will Do:

*         Researching and providing recommendations on various existing community standards/formats for organizing environmental data and specifying file-level metadata for diverse data types.

*         Working with the community to define new environmental data standards if needed.

*         Participating in curation of submitted environmental data.

*         Structure metadata to enable integration of diverse data by location or sample information, and use by the terrestrial and subsurface ecosystem modeling community.

*         Enable advanced search and visualization for data files submitted in standardized formats.

*         Collaborate with ESS projects and cyberinfrastructure working groups to enable implementation of these standards.

*         Working in a multidisciplinary team environment, including backgrounds in earth and environmental sciences, digital librarians, and computer science.

*         Author peer-reviewed journal articles and contribute to grant proposals.



What is Required:

*         Ph.D. or equivalent experience in earth and environmental sciences or data sciences related fields.

*         Graduate Student or Postdoctoral research experience in field measurements, analysis or modeling of complex and diverse datasets.

*         Experience with writing and/or adapting scientific software.

*         Experience with scientific programming languages such as Python, R or MatLab.

*         Excellent written and oral communication skills.

*         Established record of peer reviewed publications.



Additional Desired Qualifications:

*         Previous research activities focused on environmental data standards.

*         Experience with integration of large data sets from different sources.

*         Experience with land models or earth system models and their required inputs.



The posting shall remain open until the position is filled.



Notes:

*         This is a full time, 2 years, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.

*         Full-time, M-F, exempt (monthly paid) from overtime pay.

*         This position is represented by a union for collective bargaining purposes.

*         Salary will be predetermined based on postdoctoral step rates.

*         This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.

*         Work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.



Berkeley Lab <http://www.lbl.gov/> (LBNL) addresses the world's most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab's scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy's Office of Science.



Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision <https://www.dol.gov/ofccp/PayTransparencyNondiscrimination.html> under 41 CFR 60-1.4.  Click here<http://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm> to view the poster and supplement: "Equal Employment Opportunity is the Law."

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