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mathematics, machine learning, uncertainty modeling and/or statistics; developing in a Linux environment; high-performance, GPU, or cloud-computing experience. Additional experience in the areas mentioned in
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, GPU, or cloud-computing experience. Proven ability to work independently, formulate research questions, and take initiative. Cumulative GPA of 3.0. General Notes An agency designated by the federal
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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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the Signal and Information Sciences Laboratory (SISL). Responsibilities Developing algorithms and software applications in Python and C++ to support remote sensing, geospatial data analysis, computer vision
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for applications in the Life Sciences and Engineering. This cluster hire is part of The University of Texas at Austin’s Cluster Hiring Program in AI and Data Analytics (AI DA). Outstanding candidates who either (i
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computing environment, with access to HPC and GPU clusters for large-scale simulations. Collaboration with DoD researchers, Army engineers, and academic teams. Occasional travel to Army test sites for field
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intelligence (AI) and data science with core applications in the life sciences. This cluster hire is part of The University of Texas at Austin’s Cluster Hiring Program in AI and Data Analytics (AI DA