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Field
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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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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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not required as part of this position. Required Qualifications: Strong mathematical background, including expertise in one or more of the following areas: machine learning, statistics, and algorithms
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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
of models and observational data using Python, Matlab, R, etc. Expertise required in developing new models, algorithms for dispersion, gas-phase chemistry and/or aerosol microphysics model Preferred
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PV inverters), synchronous generators, loads, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component/device models into open-source software
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
, algorithms for dispersion, gas-phase chemistry and/or aerosol microphysics model. Preferred Qualifications, Competencies, and Experience Desired qualifications are a) atmospheric and aerosol chemistry, b
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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
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. Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). A broad understanding of machine learning methodologies and