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algorithms for advanced and multi-modality imaging. Work on system designs, physics models, computation, benchtop experiments with small animals, and clinical translation. Additional areas of interest are in
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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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skills, expertise, and perspectives necessary to design, conduct, sustain, and disseminate public impact research. We encourage applications from individuals from a broad diversity of PhD-granting
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the complexities of the human regulome through advanced cell-free DNA profiling and developing cutting-edge computational algorithms and molecular profiling techniques. Our research focuses on early cancer detection
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University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA
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omics to advance biological and clinical discoveries and develop next-generation theragnostics. The postdoctoral fellows will mainly focus on (1) creating novel computational algorithms to analyze and
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molecular biology. This research opportunity will be focused primarily on developing tightly integrated sequencing experiments and computational algorithms to characterize biomolecular interactions with high
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Detection: Develop and implement algorithms for identifying oscillations in the grid and extracting important oscillation modes (frequency, damping, etc.). System Strength Analysis: Use system metrics like
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optimization of optical imaging hardware, develop data acquisition software and algorithms for data processing, as well as perform phantom and human clinical studies. This candidate is expected to co-supervise
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this role you will work on some of the most challenging scientific problems facing the Department of Energy, creating new algorithms, tools, and technologies to facilitate knowledge discovery. The rate of