86 engineering-computation-"https:"-"https:"-"https:"-"https:"-"Simons-Foundation" positions at Argonne
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Argonne National Laboratory invites applications for postdoctoral research positions in experimental physics, with a focus on advancing superconducting particle detector technology for next
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lead efforts to develop experimental techniques using conventional and coherent imaging in the ultrafast time domain, as well as a computational framework for modeling and reconstructing images
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to the development of new research directions aligned with program goals. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in Chemical Engineering, Materials
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Argonne’s Nanoscience and Technology Division seeks a postdoctoral scientist to advance transmission electron microscopy (TEM) studies of materials and interfaces relevant to microelectronics
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information science and light–matter engineering, while engaging with CNM’s cleanroom and characterization capabilities, APS ultrafast and nanoprobe X-ray beamlines, MSD’s THz initiatives, and Q-NEXT’s national quantum
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Qualifications: Ph.D. (completed within the past 0-5 years) in computer science, electrical engineering, applied mathematics, or a related field. Strong proficiency in Python, with additional experience in C, C
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electrochemical methods such as cyclic voltammetry and electrochemical impedance spectroscopy is desired, but not required. · Experience working directly or collaboratively with computational methodologies
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contribute to open-source code repositories and documentation. Position Requirements Required skills, knowledge and qualifications: PhD in physical oceanography, coastal engineering, computational science
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the past five years or soon-to-be completed in physics, materials science, chemistry, engineering, or a related discipline. Demonstrated expertise in one or more synchrotron X-ray methods such as BCDI, XPCS
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for critical energy and technology sectors. Ability to assess the economic and operational impacts of large-scale AI adoption (e.g., data centers, compute infrastructure) on U.S. electricity demand, generation