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USGS Mendenhall Postdoctoral Research Fellowship Program

17-29. Data Mining for Critical Minerals

The USGS Mineral Resources Program is developing research projects to improve the Nation’s understanding of domestic critical mineral resources, as mandated by an Executive Order that led to the publication of a list of 35 critical minerals (Fortier and others, 2018).One of the challenges for assessing the domestic potential for critical minerals is that many of these commodities occur as byproducts or coproducts of mining metals such as copper or zinc in a variety of deposit types. For many critical minerals, direct information about the mineral deposit type, mineralogical residence, definition of ore grade, recoverability, and presence in existing mine waste are scarce. However, different types of mineral deposits have characteristic mineral associations that can be used to classify mineral localities by their likely mineral deposit types and to identify regions that may contain new resources. Information for assessing these mineral associations, mineral deposit types, and localities of future mineral supplies can be found in various large mineral-related databases. Databases such as MINDAT, the Mineral Resources Data System (MRDS), and compilations of data for individual types of mineral deposits can be used in combination as tools to explore for potential new sources of mineral resources. MINDAT contains worldwide data on minerals, mineral localities, references, and other mineralogical information. Many localities are mine sites of known deposit type. Other databases on geochemistry of rocks, minerals, ores, and mine waste may contain information to identify important deposit types for future resources. Concepts and methods developed in big data studies would facilitate identification of new sources for critical mineral commodities.

For this Mendenhall Research Opportunity we invite proposals to and apply cutting-edge data mining tools and data analytics to develop novel approaches to assess the Nation’s critical mineral potential.  The postdoctoral researcher would explore and analyze existing data to develop new or modified mineral deposit models, identify key data gaps, and work with other researchers to identify the most important mineral deposit types for potential domestic critical mineral resources.

We seek candidates with some experience mineralogy or economic geology in addition to strong skills in data mining and data processing, programming experience with developing analysis tools (Python or R is preferred), and GIS skills particularly with ESRI software. In addition to the above, experience with Big Data and Machine Learning Analytics is a plus.

References

Fortier, S.M., Nassar, N.T., Lederer, G.W., Brainard, Jamie, Gambogi, Joseph, and McCullough, E.A., 2018, Draft critical mineral list—Summary of methodology and background information—U.S. Geological Survey technical input document in response to Secretarial Order No. 3359: U.S. Geological Survey Open-File Report 2018–1021, 15 p., https://doi.org/10.3133/ofr20181021.

MINDAT, Outreach project of the Hudson Institute of Mineralogy (a dynamic on-line database), https://www.mindat.org/.

Proposed Duty Station: Reston, VA; Spokane, WA

Areas of Ph.D.: Economic geology, mineralogy, or information science (candidates holding a Ph.D. in other disciplines, but with extensive knowledge and skills relevant to the Research Opportunity may be considered).

Qualifications: Research Geologist, Research Information Scientist. (This type of research is performed by those who have backgrounds for the occupations stated above. However, other titles may be applicable depending on the applicant's background, education, and research proposal. The final classification of the position will be made by the Human Resources specialist.)

Research Advisor(s): Jane Hammarstrom (703) 648-6165, jhammars@usgs.gov; Joshua Coyan, (509) 368-3116, jcoyan@usgs.gov.

Human Resources Office Contact: Carrie Marez, cmarez@usgs.gov, 303 236-9555


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U.S. Department of the Interior, U.S. Geological Survey
URL: http://geology.usgs.gov/postdoc/opps/2019/17-29 Hammarstrom.htm
Direct inquiries to Cara A. Campbell at ccampbell@usgs.gov
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Last modified: 11:07:40 Fri 08 Feb 2019
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