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Field
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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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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become part of a new holotomography software package actively being developed by the team. Position Requirements Required Knowledge, Skills, and Experience: PhD (recently completed or soon-to-be completed
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position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
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algorithm development in conjunction with extensive applications in the fields of nanoscience and energy-related materials. Position Requirements a PhD in physics, or closely related field. Degree must have
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Education and Experience Requirements : This level of knowledge is typically achieved through a formal education in Nuclear Engineering, Physics, or a related field at the PhD level with zero to five years
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inverter-based resources for performing real-time simulations in Opal-RT. Develop and prototype advanced control algorithms for grid forming and grid following inverters. Develop and demonstrate
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algorithms to analyze OMICS data (e.g., genome, transcriptome, proteome, microbiome) from patient samples and basic research perform single-cell RNA-Seq and spatial transcriptomics analysis apply artificial
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it; as well as have theoretical skills including algorithm implementation/development and data visualization. Experience and interests include designing machine learning pipelines, building web