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The New York Times has called ?the most ambitious campus design program in the country." UC's momentum has never been stronger as the anchor of the Cincinnati Innovation District, the oldest cooperative
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legal practitioners and risk managers to pursue research questions with practical applications. SSLA's Social Science Research Professional position is designed for recent college or master's program
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
). Its faculty perform high-quality basic, translational and clinical research in the fields of drug development, pharmacogenomics, therapeutic engineering and computational biology. This research
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) in Electrical Engineering, Computer Engineering, or Computer Science 2. Demonstrated, successful experience (academic or professional) programming in algorithm level languages such as Matlab/Simulink
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research teams. Preferred Qualifications Experience with commercial and/or open-source GIS tools and technologies. Experience in parallel computing (e.g., MPI, Spark) and/or cloud computing (e.g., AWS
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Policy concentration for the MA program in a parallel role. This position works alongside the Associate Director of Initiative Operations and the Program Management team who are responsible for all
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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. We develop and apply both experimental and computational approaches, including in vivo Massively Parallel Reporter Assays (MPRAs), to define the sequence basis and functional consequences of enhancer
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, and parallel computing, with a proven ability to work within highly secure and regulated environments. This role involves close collaboration with security teams, scientists, and IT leadership to ensure
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing