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Qualifications Experience with field experiments, applied microeconomics (education, housing, labor), administrative data, or AI/machine learning applications in social science research. Salary Range $75,000
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radiochemistry, computational chemistry, and/or nuclear materials science. Preferred Qualifications Depending on the project, experience with Python, machine learning techniques, and any of the following tools is
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decision-making, and join a vibrant AI research community at the University of Texas at Austin, become members of The University of Texas at Austin’s Machine Learning Laboratory (https://ml.utexas.edu
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, including survival analysis, time-series techniques, causal inference approaches, and/or machine learning methods to large healthcare datasets. Prior experience mentoring or supervising graduate students
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microscopy systems that integrate machine learning, robotic control, and real-time data analysis to achieve autonomous imaging and interpretation of complex materials systems. The Fellow will design and
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, ability to follow-through, and strong problem-solving skills. Proficiency in Microsoft Excel and Word and willingness to learn other technologies as necessary. Ability to work independently and on a team
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, or computational methods Strong organizational skills and ability to manage multiple projects independently Preferred Qualifications Interest and/or experience with large-scale natural language processing, machine
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Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
or parallel reactors Collaborate with computational scientists to integrate machine-learning models for closed-loop materials discovery Collaborate with companion postdocs on functional materials