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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
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characterization. The TEM postdoctoral fellow will collaborate with companion postdocs specializing in liquid-phase synthesis and thin-film formation, integrating structural characterization directly with
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of this fellowship will join a vibrant community of postdocs, students and faculty where they are expected to pursue self-directed research in any scientific subfield. Successful applicants may take up residence as
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models, (d) experience in using high performance computing systems with multiple nodes and GPUs and (e) drought metrics. Familiarity with Texas water resources and management practices. Experience working
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| Human Resources and UT Austin Employee Experience | Human Resources Must be authorized to work in the United States on a full-time basis for any employer without sponsorship. Purpose The Postdoc employed
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has also been developing physics-based machine learning algorithms for three dimensional seismic modeling, imaging and inversion using high performance computation including parallelization on GPUs
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. Collaborate effectively with staff, postdocs, and students in the research group and collaborators of the group. Present results to the scientific community and broader public through conference presentations