Joshua M. Rosera, Ph.D.
Joshua Rosera is a Research Geologist with the USGS Geology, Energy & Minerals (GEM) Science Center in Reston, VA.
I am an economic geologist that is interested in utilizing spatial analysis, geochronology, and radiogenic isotopic measurements to test models about the origins of mineral systems related to continental magma systems. Part of my ongoing work at the USGS is focused on integrating large spatial datasets into tools that can be used to better explore, visualize, and model data related to mineral deposits. This includes developing multivariate tools that can analyze previously underutilized qualitative data attributes in historical mineral deposit datasets, as well as developing data-driven methods to assist in mineral prospectivity mapping and mineral resource assessments.
I completed my M.S. and Ph.D. at the University of North Carolina, where I studied temporal and spatial relationships between caldera-forming silicic magma systems and mineral deposits. My collaborators and I use high-precision U/Pb zircon geochronology to better resolve timescales of magmatism related to mineralization, and where and when these events occur with respect to caldera formation. I am also interested in studying the origins of fluorine enrichment that is observed in numerous magma systems in the Southern Rocky Mountain region. We test hypotheses regarding how these systems achieve high fluorine abundances by analyzing deep crustal xenoliths, and by tracking the sources of fluorine-rich melts with radiogenic isotopes.
Prior to starting my Ph.D., I worked for Chevron as a mine and petroleum geologists. I worked at the Questa molybdenum mine in northern New Mexico up until its final closure in 2014. I spent the next two years in west Texas as an operations geologist where I assisted technical work for a mature waterflood.
Professional Experience
Research Geologist (2022-present)
Mendenhall Postdoctoral Fellow, U.S. Geological Survey (2020-2022)
Graduate Research Consultant, University of North Carolina (2017; 2018)
Instructor, University of North Carolina (2016)
Research and Teaching Assistant, University of North Carolina (2010-2012; 2016-2020)
Earth Scientist, Chevron North America Exploration and Production Company (2014-2016)
Mine Geologist, Chevron Mining Inc. (2012-2014)
Research and Teaching Assistant, University of Wisconsin – Oshkosh (2008 – 2010)
GIS Intern, University of Wisconsin – Oshkosh (2010)
GIS Intern, City of De Pere, Wisconsin (2009)
Education and Certifications
Ph.D., Geological Sciences, University of North Carolina at Chapel Hill (2020)
M.S., Geological Sciences, University of North Carolina at Chapel Hill (2012)
B.S., Geology and Geography, University of Wisconsin – Oshkosh (2010)
Affiliations and Memberships*
Society of Economic Geologists
Geological Society of America
Sigma Xi
American Geophysical Union
Science and Products
Using stochastic point pattern analysis to track regional orientations of magmatism during the transition to cenozoic extension and Rio Grande rifting, Southern Rocky Mountains
Critical minerals in Climax-type magmatic-hydrothermal systems
Today’s global economy is challenged to meet the growing demand for commodities used in existing and emerging advanced technologies. Critical minerals are commodities found in a wide variety of ore deposits that are vital to the economic or national security of individual nations that are vulnerable to supply disruption. The U.S. Geological Survey is striving to advance understanding of critical m
Fluorine-rich mafic lower crust in the southern Rocky Mountains: The role of pre-enrichment in generating fluorine-rich silicic magmas and porphyry Mo deposits
Automated georeferencing and feature extraction of geologic maps and mineral sites
Genesis of the Questa Mo porphyry deposit and nearby polymetallic mineralization, New Mexico, USA
Correspondence analysis for mineral commodity research: An example workflow for mineralized calderas, southwest United States
Historical mine and mineral deposit datasets are routinely used to inform quantitative mineral assessment models, but they also can contain a wealth of supplementary qualitative information that is generally underutilized. We present a workflow that uses correspondence analysis, an exploratory tool commonly applied to multivariate abundance data, to better utilize qualitative data in these histori
Mapping multivariate ore occurrence data with correspondence analysis
Extracting data from maps: applying lessons learned from the AI for Critical Mineral Assessment Competition
MinFrame - Methodological infrastructure needed for resource assessment, modeling, and evaluation
Grade and tonnage data for lithium, cesium, and rubidium pegmatite deposits
Training and validation data from the AI for Critical Mineral Assessment Competition
Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and
MapMark4 Version Update (Version 1.1)
R Code Supporting the Manuscript: Using Stochastic Point Pattern Analysis to Track Regional Orientations of Magmatism During the Transition to Cenozoic Extension and Rio Grande Rifting, Southern Rocky Mountains
Science and Products
Using stochastic point pattern analysis to track regional orientations of magmatism during the transition to cenozoic extension and Rio Grande rifting, Southern Rocky Mountains
Critical minerals in Climax-type magmatic-hydrothermal systems
Today’s global economy is challenged to meet the growing demand for commodities used in existing and emerging advanced technologies. Critical minerals are commodities found in a wide variety of ore deposits that are vital to the economic or national security of individual nations that are vulnerable to supply disruption. The U.S. Geological Survey is striving to advance understanding of critical m
Fluorine-rich mafic lower crust in the southern Rocky Mountains: The role of pre-enrichment in generating fluorine-rich silicic magmas and porphyry Mo deposits
Automated georeferencing and feature extraction of geologic maps and mineral sites
Genesis of the Questa Mo porphyry deposit and nearby polymetallic mineralization, New Mexico, USA
Correspondence analysis for mineral commodity research: An example workflow for mineralized calderas, southwest United States
Historical mine and mineral deposit datasets are routinely used to inform quantitative mineral assessment models, but they also can contain a wealth of supplementary qualitative information that is generally underutilized. We present a workflow that uses correspondence analysis, an exploratory tool commonly applied to multivariate abundance data, to better utilize qualitative data in these histori
Mapping multivariate ore occurrence data with correspondence analysis
Extracting data from maps: applying lessons learned from the AI for Critical Mineral Assessment Competition
MinFrame - Methodological infrastructure needed for resource assessment, modeling, and evaluation
Grade and tonnage data for lithium, cesium, and rubidium pegmatite deposits
Training and validation data from the AI for Critical Mineral Assessment Competition
Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and
MapMark4 Version Update (Version 1.1)
R Code Supporting the Manuscript: Using Stochastic Point Pattern Analysis to Track Regional Orientations of Magmatism During the Transition to Cenozoic Extension and Rio Grande Rifting, Southern Rocky Mountains
*Disclaimer: Listing outside positions with professional scientific organizations on this Staff Profile are for informational purposes only and do not constitute an endorsement of those professional scientific organizations or their activities by the USGS, Department of the Interior, or U.S. Government