95 linked-data-"https:"-"https:"-"https:"-"Embry-Riddle-Aeronautical-University" positions at Argonne
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data processing and analysis techniques is a plus Strong written and oral communication skills Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Candidates with a
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-system data, simulation platforms, and digital-twin or real-time environments as appropriate. Collaborate with researchers across power systems, controls, cybersecurity, and AI/ML to develop publications
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optical and THz techniques. Ability to analyze and understand complex data set is required. Experience to lead ultrafast x-ray scattering or electron scattering experiments is a plus but not required
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design, development of supervisory control logic, validation of vehicle models against test data etc. The projects and interests of this group span all modes of transportation including off-road, rail
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will receive full consideration. Key Responsibilities AI-ready data and analysis for the ePIC Barrel Imaging Calorimeter and our Jefferson Lab program Support for the PRad-II and X17 experiments
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the ability and motivation to develop expertise in large-scale model training and scaling on HPC systems, as well as in handling the unique characteristics of scientific data, including large-scale numerical
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cryogenic environments Participate in synchrotron-based characterization and data analysis Contribute to high-impact publications, internal reports, and scientific presentations at conferences and workshops
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities
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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