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reconstruction algorithms that incorporate multiply-beam coherent scattering imaging in a grazing incidence geometry to improve the spatial resolution to ultimately demonstrate the utility of the novel coherent
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PhD level with zero to five years of employment experience. Expertise in testing, characterizing, and measuring MEMS devices and designing feedback loops and control algorithms for the precise operation
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Laboratory seeks a postdoctoral appointee to join a multidisciplinary team developing complex systems models, including agent-based models, and new algorithms and tools for machine learning and optimization
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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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for projects related to the integration of microgrids, distributed energy resources (DERs), and advanced transmission & distribution (T&D) coordination. This role is ideal for a researcher passionate about
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
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reconstruction algorithms that incorporate multiply-beam coherent scattering imaging in a grazing incidence geometry to improve the spatial resolution to ultimately demonstrate the utility of the novel coherent
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PhD level with zero to five years of employment experience. Expertise in testing, characterizing, and measuring MEMS devices and designing feedback loops and control algorithms for the precise operation
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. Experience with uncertainty quantification and multi-modal deep learning. Experience with distributed training. Skill in written and oral communications. Experience interacting with scientific staff and
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within the last 0-5 years) in computational science, mathematics, physics, or a related field with a focus on image processing. Proven experience in algorithm and software development. Expertise in Python