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Field
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distributed systems techniques. Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and parallel computing. Demonstrated hands-on experience and
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research computing, systems engineering, or a closely related technical field supporting research environments Hands-on experience managing HPC clusters, job schedulers, and parallel file systems  PREFERRED
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for designing, deploying, and maintaining advanced research computing infrastructure and services in support of the university’s research mission. This role collaborates closely with faculty, research staff, and
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 3 months ago
; strong physical, mathematical, and computational background; experience with programming in at least one general-purpose language (preferably Julia) and parallel computing; demonstrated effective written
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Position Details Position Information Position Title Research Engineer Requisition # S01463P FLSA Exempt Location IIT-Mies Campus (MC), 10 West 35th St., Chicago Department Computer
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/technical programs and university-parallel/college transfer programs. This position will work with a variety of complex HR topics. Position is primarily responsible for the design, development, and delivery
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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
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into agent-based models. Familiarity with parallel computing and cloud-based simulation environments. Knowledge of specific domains such as epidemiology or social sciences. Familiarity with web-scraping and
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Berkeley Lab researchers to accelerate discovery through advanced computing, artificial intelligence, and data-driven science, supported by state-of-the-art cyberinfrastructure (CI) systems, tools
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well as experience with HPC environments and parallel computing. Demonstrated hands-on experience and understanding of developing scientific data management, workflows and resource management problems. Strong problem