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Field
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learning algorithms for engineering systems Programming experience in FORTRAN, C, or C++ and scripting experience in Python or similar languages Experience with parallel computing environments and Linux
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to run on parallel environments. CUDA and Fortran programming expertise. Experience with HPC job schedulers, especially job submission is required. Slurm scheduler experience. Experience and understanding
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software packages. Familiarity with core data structures, algorithms, and some exposure to parallel or distributed computing. Strong quantitative and critical-thinking abilities demonstrated through
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in AI to study natural and artificial minds in parallel, creating the opportunity to make discoveries about ourselves and to find new ways to understand and improve AI systems. Appointments will be
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, massively parallel genomic/proteomic/clinical]. Data management and analysis solutions that aid in the storage, investigation, and dissemination of large data sets. Independent research projects, including
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-engaged unit housed in the College of Health Sciences. The department offers expanding undergraduate and graduate programs and is committed to excellence in clinical education, community engagement, and
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-engaged unit housed in the College of Health Sciences. The department offers expanding undergraduate and graduate programs and is committed to excellence in clinical education, community engagement, and
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comprehensive Research Computing strategic plan in collaboration with LTS leadership, the Research Computing Steering Committee, and campus stakeholders. • Partner with University leadership, faculty, and the
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eigenvalue problems Experience of MPI, OpenMP, and other parallel programming models Understanding of quantum many-body problem and tensor eigenvalue problem Excellent oral and written communication skills
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– this role is expected to work onsite and is located in Aurora, CO. Why Join Us: The Department has grown substantially in the past 15 years, from 40 to 120 faculty in parallel with the remarkable growth