8 parallel-processing Fellowship research jobs at University of Texas at Austin in United States
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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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on advanced seismic monitoring using DAS and nodes, with emphasis on DAS processing and dense acquisition techniques for land-based applications. This in-person position is located at J.J. Pickle Research
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-edge semiconductor manufacturing equipment and processes that will set the course for future advancements in semiconductor logic, memory, heterogeneous integration, chip cooling and more. Situated in the
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thinking skills, and ability to work as part of a multidisciplinary team. High computer proficiency, including basic MS Office, MS Access, graphics, and database software. Basic project management and
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collection, including cognitive assessments such as computer-based testing, questionnaires, and health measurements, as well as brain measures such as electroencephalography and near-infrared spectroscopy
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have been received within the last three years, 1 year of experience with machine learning, natural language processing, AI tools and frameworks, data integration, and/or explainable AI. Proficiency in
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-edge semiconductor manufacturing equipment and processes that will set the course for future advancements in semiconductor logic, memory, heterogeneous integration, chip cooling and more. Situated in the
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Experience with high performance computer clusters (e.g, TAMU-HPRC, UT-TACC, NVIDIA Data Center). Preferred Qualifications Background in estuarine ecology, aquatic vegetation Experience with image analysis