83 engineering-computation-"https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "TCAT Dickson" Postdoctoral positions at Argonne in United States
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Requirements To perform the essential functions of this position successful applicants must provide proof of U.S. citizenship, which is required to comply with federal regulations and contract. PhD completed
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Requirements Ph.D. completed in the past 5 years or soon-to-be completed in Chemical Engineering, Materials Science, Chemistry, Nuclear Engineering, or related field with zero to five years of experience
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. The successful candidate will be a key contributor to a multidisciplinary co-design team spanning material science, computing, and electronic engineering, with the goal of enabling next-generation detector
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Applications are invited for post-doctoral positions in the Cosmological Physics and Advanced Computing Group (CPAC) Group in Argonne National Laboratory’s High Energy Physics (HEP) Division
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for predicting the reliability of high-temperature structural components. This involves working with various continuum damage mechanics models and statistical reliability models. The goal is to enhance engineering
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The Vehicle Technology Assessment (VTA) Group within the Vehicle and Mobility Systems at Argonne National Laboratory is seeking to hire a postdoctoral appointee to assess vehicle technologies
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at conferences and ALCF/DOE venues. Position Requirements Required Skills and Qualifications: Ph.D. in Computer Science, Physics, Chemistry, Biology, Engineering, Mathematics, or a related computational discipline
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computational scientists, economists, engineers, and other researchers to develop data-driven, decision-relevant analytical tools for complex industrial systems. Key Responsibilities: Develop, improve, and apply
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. Position Requirements Ph.D. completed in the past five years or soon-to-be completed in Chemical Engineering, Materials Science, Chemistry, Nuclear Engineering, or related field. Skill in devising and
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Because of the drastically increasing demand from AI/ML applications, the computing hardware industry has gravitated towards data formats narrower than the IEEE double format that most computational