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readout circuit designs informed by device characterization and electromagnetic simulations Contribute to the development of complete instrument systems for characterization of solid-state single-photon
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efforts in nanomaterials synthesis and in situ/operando characterization of liquid–solid interfaces during electrochemical conversions. This position offers the opportunity to leverage CNM’s advanced user
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are highly desirable: DoE, continuous/batch co-precipitation reactions (e.g., CSTR), solid state synthesis, ability to work with larger equipment or experience in kilo-scale synthesis, electrochemistry, and Li
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). This position focuses on The investigation of coupled land-river-ocean processes in coastal flooding applications by developing a coupled E3SM configuration that incorporates a subgrid-scale version of the MPAS
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apply funding from federal agencies (e.g., the Department of Energy and National Science Foundation). A successful candidate should have a solid background in power system engineering, optimization
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Comprehensive knowledge of imaging systems and/or semiconductor or solid-state detector design and simulation Experience with GEANT4 simulations and detector characterization is highly desirable Familiarity with
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optical transition and favorable spin properties of individual solid-date erbium ions (Er3+) to store quantum information necessary for practical, robust, and scalable quantum communication. The focus
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with strong expertise in machine learning for cyber-physical systems and a solid understanding of electric power distribution systems, and microgrid operations. The selected candidate will develop and
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staff scientists, engineers, postdocs, and students, with an active research portfolio that spans: Leading electron-scattering experiments at Jefferson Lab (CLAS12, SoLID, Hall A, B, and C) Major
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at a fraction of the computational cost. Recently Argonne successfully implemented, AERIS, a state-of-the-art seasonal-to-subseasonal (S2S) weather model AI model. A successful candidate will collaborate