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Field
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lead analyses of large-scale datasets, applying advanced computational and statistical methods to integrate multimodal data (including MRI, MEG, EEG, and genomic data). The postholder will work with a
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lead analyses of large-scale datasets, applying advanced computational and statistical methods to integrate multimodal data (including MRI, MEG, EEG, and genomic data). The postholder will work with a
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metagenomics and Oxford Nanopore Technologies sequencing. Large experience in bioinformatics, machine learning and high-performance computing in relation to microbial metagenomics and analysis of horizontal gene
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FieldComputer science » OtherEducation LevelPhD or equivalent Skills/Qualifications CANDIDATE ’S PROFILE The candidate should possess a PhD in machine learning or computer vision and have a strong publication
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
generation (RAG) Experience deploying large-scale machine learning models in cloud environments. Special Physical/Mental Requirements Special Instructions For information on UNC Postdoctoral Benefits and
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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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Research Associate. The Goodwill Computer Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning
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metagenomics and Oxford Nanopore Technologies sequencing, wet lab method development and DNA library preparation for Oxford Nanopore sequencing. Large experience in bioinformatics, machine learning and high
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solutions for large-scale scientific data models in federated learning environments. You will advance privacy-preserving machine learning by developing efficient techniques that maintain robust privacy
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Observation data analysis. You are fluent in Python and have solid experience with relevant machine learning and geospatial libraries such as PyTorch, TensorFlow, GDAL, rasterio, and zarr. You have experience