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Field
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, manage and administer large-scale high-performance computing systems and networks, which include cutting edge research cluster computers containing a dozen to several hundred nodes, various types
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for driving the intellectual agenda for the Initiative (and parallel research in India), working closely with Professor Kaur, faculty investigators, and program managers to identify and proactively pursue high
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, translational and clinical research in the fields of drug development, pharmacogenomics, therapeutic engineering and computational biology. It educates PharmD, MD professionals and PhDs in bioengineering and
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curation of specialty specific resources and contribution to the broader advising program. The CSA also supports career exploration for undecided students through engagement with medical student interest
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Job Summary #CA-PS Under direction, manage and administer large-scale high-performance computing systems and networks, which include cutting edge research cluster computers containing a dozen to
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. Knowledge of multi-dimensional code development (in C++/C/Fortran) for two-phase/multiphase flow and turbulent combustion applications, and parallel scientific computing. Experience in geometry manipulation
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languages. Experience using parallel Linux computing platforms, parallel job submission scripts, common software repository tools, and parallel visualization software. Preferred Qualifications: Excellent
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turbulent combustion applications, as well as parallel scientific computing. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and
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on finding and cultivating talented people who are passionate about what they do. Join us and be a part of the diverse Caltech community. Job Summary The Research Assistant in Scientific Computing will work
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semester to execute that plan tied to a course or courses. Engagement may include working with students on assignments, conducting master classes on topics related to the main course or developing parallel