428 parallel-computing-numerical-methods-"Simons-Foundation" positions at Carnegie Mellon University
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developing countries around the world. We provide education on important issues of public policy that involve technology, such as the digital divide, cybersecurity, and green energy. Our program helps
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university’s creative, dedicated and close-knit community. We place emphasis on practical problem solving, interdisciplinary learning, a visionary spirit, and collaboration. The Computer Science Department (CSD
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behavior and theory, economics, finance, and accounting. Carnegie Mellon University’s Tepper School of Business is searching for a Full-Time Fixed Term Academic Program Manager to join their team. This is an
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What We Do: The SEI helps advance software engineering principles and practices and serves as a national resource in software engineering and computer security. The SEI works closely with academia
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, faculty members, researchers, and students are revolutionizing focus areas in advanced manufacturing, bioengineering, computational engineering, energy and the environment, product design, and robotics. In
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numerical. Analytical results for classical problems of high symmetry also will be presented to serve as a basis for comparison and validation. Software: A finite element and computational transport tool
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, faculty members, researchers, and students are revolutionizing focus areas in advanced manufacturing, bioengineering, computational engineering, energy and the environment, product design, and robotics. In
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by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational
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-omics datasets (genomics, proteomics, etc.) related to schizophrenia research. Integrate multiple high-dimensional datasets using canonical correlation methods. Modify and adapt existing statistical
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-omics datasets (genomics, proteomics, etc.) related to schizophrenia research. Integrate multiple high-dimensional datasets using canonical correlation methods. Modify and adapt existing statistical