227 parallel-and-distributed-computing-phd positions at California Institute of Technology
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laboratory at LHO. In parallel, the chosen candidate will assist in forging results of this R&D into a conceptual reference design, construction plan, and parametric cost estimate for CE. These will form
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research projects. The successful candidate will collaborate closely with science and engineering teams at JPL. Additionally, the successful candidate will oversee a database of globally distributed GNSS
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system, processes those data into calibrated image and source detection products, performs automated searches for moving Solar System objects, assesses the quality of the survey data, and distributes data
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technologies. Essential Job Duties Collaborate with Principal Investigator(s) to determine direction of research projects in the fundamental and applied study of natural isotope distributions. Coordinate
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distributed system developments to evaluate and implement new networking technologies to ensure fast and reliable data transfers to/from the computing clusters and new data access methods. The successful
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, particularly of regularly updated GNSS data from globally distributed locations. May include time for individual research if desired. Other duties as assigned. Basic Qualifications PhD in geophysics and at least
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CEBEX laboratory at LHO. In parallel, the chosen candidate will take a lead role in forging results of these investigations into a conceptual design, construction and installation plan, and parametric
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publication. Solid understanding of statistical analysis methods (NHST, probability distributions, etc.) Ambition to pursue advanced training or career in computational biology, bioinformatics, ambition
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for the Undergraduate Deans Office and answers inquiries that require overall understanding of its policies, procedures, and current program offerings. Provides support to members of the Undergraduate Deans Office team
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out research on distributed acoustic sensing (DAS) data analysis and participate in continued development on the inclusion of DAS data within the network monitoring systems. We seek applicants who like