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their compilation tools in different environments. (C++, Fortran, ...) Experience with parallel computing, cloud deployment, and network license managers (FlexLM, RLM, etc.). Strong background in
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Learning in a broad sense. Particular areas of interest include, but are not limited to, development and analysis of machine learning models for scientific computing, theory and algorithms for sampling
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Description The Oden Institute for Computational Engineering and Sciences and the Department of Statistics and Data Sciences at The University of Texas at Austin have an opening for a tenured or
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skills will make a difference. You’ll be working for a university that is internationally recognized for our academic programs and research. Your work will contribute to operational excellence and enhance
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from the TexNet earth observation program or assets that provide quality data. Compare different methods and tools for deformation modelling. Engage in outside funding activities and promote programs
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involved in analyzing data collected from the TexNet seismological monitoring program and other stations or assets that provide quality data. Comparing different methods and tools for moment tensor inversion