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a focus on data analytics, AI, ML, advanced process control, and digital twin technologies in semiconductor manufacturing. Experience with handling industrial big data problems, physics-informed AI/ML
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of sedimentology, geochemistry, and microbiology, and general use of destructive, extraction-based methods that are designed for the analysis of large sediment samples. These bulk methods are quantitative but
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issues, develop ML approaches to analyze water quantity/quality data, and assess spatiotemporal variability in various resource datasets. Responsibilities Conducting research using large databases
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spirit. UT Austin, recognized by Forbes as one of America’s Best Large Employers , provides outstanding employee benefits and total rewards packages that include: Competitive health benefits (employee
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data. Present results to the scientific community and broader public. Publish results in peer-reviewed journals. Required Qualifications Ph.D. in Geophysics, Physics, Earth Sciences, Applied Mathematics