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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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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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Description NREL is seeking a postdoc to design, train, and analyze the AI/ML and control algorithms for hybrid energy systems including industrial systems, building controls, and advanced energy systems
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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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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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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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single-cell sequencing, spatial transcriptomics, and machine learning algorithms to to understand, at the tissue and organ level, how specific cellular communications—from synaptic connectivity to neural
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computer science knowledge. Preferred Knowledge, Skills, and Abilities: Practical experience developing novel AI/ML algorithms and models. Knowledge about hardware architectures, compilers, neural network
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by publication record). Excellent programming and computer science skills. Preferred Knowledge, Skills, and Abilities: Practical experience developing novel ML and NLP algorithms and models and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
looking for a postdoctoral fellow interested in developing either machine learning algorithms for high-resolution histopathology imaging/spatial-profiling data in combination with other modalities (e.g