81 quantum-engineering-"https:"-"https:"-"https:"-"Embry-Riddle-Aeronautical-University" positions at Argonne
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regular channels. Position Requirements A formal education in chemical engineering, mechanical engineering, or a related field at the PhD level with zero to five years of experience. To perform
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the last 0-5 years) in geology, earth sciences, chemistry, chemical engineering, or materials engineering (those with other degrees but have similar skills to those listed will be considered). Experience in
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-be completed (typically within the last 0-5 years ) Ph.D. in engineering, operations research, computer science, applied mathematics, or a related field. Demonstrated expertise in mathematical
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/modelers, and data scientists Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Materials Science, Chemical Engineering, Chemistry, or a closely related field
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Recent or soon-to-be completed (typically within the last 0-5 years ) Ph.D. in Computer Science, Electrical Engineering, or a related field. Demonstrated research expertise in AI and machine learning, with
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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We are seeking a highly motivated postdoctoral researcher to conduct independent research on foundation models for scientific and engineering applications, with an emphasis on training, adaptation
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to contribute to other large-team scientific projects in materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Required skills: Recently completed PhD (within the last
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pressure diamond anvil cell technology. Excellent oral and written communication skills. Ability to model Argonne's Core Values: Impact, Safety, Respect, Integrity, and Teamwork. Preferred Knowledge, Skills
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scientists and engineers are accustomed to. Moreover, the vast majority of the performance associated with these reduced precision formats resides on special hardware units such as tensor cores on NVIDIA GPUs