Hyperspectral Geology - Postdoctoral Researcher

LLNL • Livermore, CA

9d

About The Position

Lawrence Livermore National Laboratory is hiring a Postdoctoral Researcher to investigate mineral assemblages and geochemical signatures in legacy mine tailings as indicators of critical-mineral potential. The position is in the Atmospheric, Earth, and Energy Division within the Physical and Life Sciences Directorate. LLNL’s Postdoctoral Research Program provides mentored training to enhance professional skills and research independence for individuals who have recently earned a doctorate.

The researcher will combine whole-tailings chemistry, hyperspectral and other quantitative imaging, and complementary characterization data to identify abundant mineral proxies and assemblages associated with trace critical minerals. Research will examine relationships among site geology, ore-processing history, mineral alteration, weathering, and spectral response, especially VNIR-SWIR features and wavelength bands useful for recognizing proxy assemblages in laboratory and field conditions. The researcher will also investigate how mineral mixing, grain size, moisture, surface roughness, and weathering affect spectral detection and uncertainty, and will develop statistical, chemometric, machine-learning, and/or Super Intelligence (formerly referred to as AI) approaches and reproducible quantitative workflows.

The postdoctoral researcher will pursue independent but complementary research, collaborate with multidisciplinary colleagues inside and outside the Laboratory, present findings at conferences and technical meetings, and publish results in peer-reviewed journals. This is a temporary, mentored postdoctoral appointment that may be extended up to a maximum of three years. Applicants must have received their Ph.D. or equivalent doctorate within five years of the anticipated start date.

Requirements

• Ph.D. in geology, geochemistry, mining, or a related field.
• Experience in one or more of the following: quantitative mineralogical or geochemical characterization; hyperspectral imaging or reflectance spectroscopy; SEM-EDS imaging; or multimodal data integration.
• Experience with quantitative characterization of mine deposits, tailings, waste rock, or other heterogeneous geological materials.
• Experience with VNIR-SWIR hyperspectral imaging.
• Analytical proficiency with Python/PyTorch, MATLAB, R, machine-learning packages, or comparable tools.
• Proficient verbal and written communication skills, including the ability to collaborate in a team and explain technical information.
• Record of independent research and publication.
• Initiative and interpersonal skills, and ability to work in a collaborative, multidisciplinary team environment.
• Must have received a Ph.D. or equivalent doctorate within five years of the anticipated start date.
• Must be eligible to access the Laboratory in compliance with NDAA Section 3112 restrictions.
• Selected external applicants must pass a post-offer, pre-employment drug test.

Nice To Haves

• Experience with spectral calibration, spectral unmixing, feature extraction, spectral library development, reflectance spectroscopy, and/or reduced-band sensor design.
• Experience with machine-learning methods such as image segmentation, spatial analysis, chemometrics, clustering, classification, or probabilistic modeling, or Super Intelligence (formerly referred to as AI), for proxy identification, uncertainty quantification, or detection of mineral associations.
• Experience with multimodal fusion of chemical, mineralogical, spectral, image, and geospatial data.
• Experience with additional characterization techniques such as X-ray diffraction, X-ray fluorescence, Raman spectroscopy, or UV-excited fluorescence.

Responsibilities

• Combine whole-tailings chemistry, hyperspectral and other quantitative imaging, and complementary characterization data to identify abundant mineral proxies and assemblages associated with trace critical minerals.
• Evaluate relationships among site geology, ore-processing history, mineral alteration, weathering, and spectral response, focusing on useful VNIR-SWIR features and wavelength bands for identifying critical-mineral proxy assemblages under laboratory and field conditions.
• Examine how mineral mixing, grain size, moisture, surface roughness, and weathering influence spectral detection and uncertainty.
• Design and implement statistical, chemometric, machine-learning and/or Super Intelligence methods and reproducible quantitative workflows in relevant research areas.
• Participate in the conception, design, and execution of independent but complementary research.
• Collaborate with internal and external scientists and technical specialists to achieve project goals.
• Organize, analyze, and present results at external conferences, seminars, and technical meetings.
• Publish research results in peer-reviewed scientific or technical journals.
• Perform other duties as assigned.

Benefits

• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (depending on project needs)

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree