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within tissues using our in-house developed spatial transcriptomics-based technology (Spatial VDJ). Using established and newly developed algorithms, we map B cell evolution within tissues, including class
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: Employing satellite observation and machine leaning to improve model representation of ice sheet surface melt”. The candidate will work under the direction of Prof Nowicki and in collaboration with multiple
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learning algorithms into professional software with an intuitive user interface, incorporating feedback from CHWs through iterative design and evaluation cycles. The selected candidate will be part of a
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to seek an optimal integration between the physical representations of the various processes and the computing power of the AI algorithms. Key duties Develop a robust framework to simulate streamflow
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that amplify human potential. The successful candidate will engage in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems
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data pipelines Comply with data security guidelines Data analysis (25%) Data reduction of predictor and outcome measures Determine and implement optimal strategies for testing multiple hypotheses Utilize
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the readout manufacturer to adapt and refine the high-speed readout electronics and synchronization system for efficient electron detection. Implement and test real-time processing algorithms for high
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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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development as well as field data collection at multiple test sites in Ethiopia. Job assignments The successful candidate will join a large, collaborative team of researchers with expertise in electromagnetic
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
meteorology, and numerical modeling techniques with an understanding of local-scale physical and chemical processes from multiple emissions sources as represented in current models, and quantitative analysis