Hyperspectral Geology - Postdoctoral Researcher

Lawrence Livermore National Laboratory’s Postdoctoral Research Program provides mentored training to enhance professional skills and research independence for individuals who have recently earned their doctoral degree and are pursuing their chosen career path.
We have an opening for a Postdoctoral Researcher to investigate mineral assemblages and geochemical signatures in legacy mine tailings as indicators of critical-mineral potential. Candidates from mineralogy, geology, geochemistry, mining, hyperspectral imaging, multimodal data science, machine learning, and/or related disciplines are encouraged to apply.
This position is in the Atmospheric, Earth, and Energy Division, within the Physical and Life Sciences Directorate.
You 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.
Evaluate relationships among site geology, ore-processing history, mineral alteration, weathering, and spectral response, with a major focus on identifying the visible and near-infrared to short-wavelength infrared (VNIR-SWIR) features and wavelength bands most useful for recognizing 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, and/or machine learning and artificial intelligence techniques and reproducible quantitative workflows in one or more of the above areas.
Actively participate in conception, design, and execution of independent (but complementary) research and collaborate with a broad spectrum of scientists (geologists, mineralogists, microscopists, spectroscopists, data scientists, physicists, and engineers developing field-deployable characterization systems) internally and externally to the Laboratory to achieve project goals.
Organize, analyze, and present results at external conferences, seminars and/or technical meetings; and publish research results in peer-reviewed scientific or technical journals.
Perform other duties as assigned.
PhD in geology, geochemistry, mining, or a related field.
Experience with one or more of the following areas: quantitative mineralogical or geochemical characterization; hyperspectral imaging or reflectance spectroscopy; scanning electron microscopy/energy dispersive 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 to collaborate effectively in a team environment; demonstrated ability to explain technical information; and record of independent research and publication.
Effective initiative and interpersonal skills and ability to work in a collaborative, multidisciplinary team environment.
Qualifications we desire
Additional experience with spectral calibration, spectral unmixing, feature extraction, spectral library development, reflectance spectroscopy, and/or reduced-band sensor design.
Experience with machine learning (e.g., image segmentation, spatial analysis, chemometrics, clustering, classification, probabilistic modeling) or artificial intelligence methods 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, UV-excited fluorescence, etc.
Pay Range
$123,048 Annually
This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.

Employment type
Full-time

Work arrangement
No