30 parallel-and-distributed-computing-"Multiple" Fellowship positions at University of Texas at Austin
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Job Posting Title: Director, Archer Fellowship Program ---- Hiring Department: Academic Affairs ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 40 ---- FLSA Status: Exempt
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Job Posting Title: Postdoctoral Fellow, Department of Computer Science ---- Hiring Department: Department of Computer Science ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 40
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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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MAIN CAMPUS ---- Job Details: General Notes As a top-10 engineering school with the No. 1 program in Texas, the Cockrell School of Engineering at The University of Texas at Austin has been a global
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MAIN CAMPUS ---- Job Details: General Notes As a top-10 engineering school with the No. 1 program in Texas, the Cockrell School of Engineering at The University of Texas at Austin has been a global
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of nuclear and radiation engineering, including imaging, robotics, high-performance computing, reactor design and materials development. The groups provide a supportive community striving to solve the most
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well as to provide a strong foundation for further research projects. Each position term is subject to performance as well as research program needs and funding. Multiple postdoctoral fellow positions are initially
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. Purpose We are seeking highly motivated candidates for postdoctoral fellow positions within the Bureau’s hydrology research group. These fellows will be key members of an expanding research program focused
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well as to provide a strong foundation for further research projects. Each position term is subject to performance as well as research program needs and funding. Multiple postdoctoral fellow positions are initially
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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