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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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, and (5) increase situational awareness during large fire incidents. The postdoctoral fellow will join a team developing novel thermal imagers and other sensors for UAVs to improve our observations and
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laboratory experiments for monitoring fluid movement in the subsurface (brine, CO2, H2, etc.) and leakage. Responsibilities Acquire and process time-lapse ultrasonic data from sand tank laboratory experiments
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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
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with incoming Assistant Professor Dr. Adela Timmons. Research in the TIES Lab focuses on big data analytics and pervasive computing methods for building adaptive and responsive mental health
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/CCUS, and geothermal energy. The researcher will also lead efforts in data mining, market research, and modeling to assess value chains and perform financial analyses, including Net Present Value (NPV