21 high-performance-computing-postdoc Fellowship positions at University of Texas at Austin
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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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parts of the world and are also involved in planetary missions and climate modeling. These research projects produce large data sets and require computational analysis and visualization. Your skills will
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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
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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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defined benefit retirement plan, with 8.25% employer matching funds Additional Voluntary Retirement Programs: Tax Sheltered Annuity 403(b) and a Deferred Compensation program 457(b) Flexible spending
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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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, geology, or related field. Demonstrate experience and aptitude in remote sensing of complex thermal systems (e.g., fires, volcanoes, or urban heat). Ability to develop code/algorithms for data analysis and
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. This is a temporary training position that can be renewed annually, for a maximum of five years, based upon performance review, progress towards research goals, and continuation of funding. Purpose To work
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subject to satisfactory performance and funding availability. Responsibilities Join field and lab-based experiment, perform data collection and interpretation. Present research results at national
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program of the Department of Mathematics is consistently ranked among the best by US News, with several research areas in the top ten. Our core faculty includes around 50 tenured and tenure-track members