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, reinforcement learning, and/or wireless communications. The candidate should hold a doctoral degree in electrical or computer engineering or related fields. The successful candidate will have a strong publication
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degree in industrial engineering, operations research, statistics, or machine learning and have a strong research record. • Qualified candidates should have prior research and publications in optimization
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analysis, expertise in multi-omics data integration, and working experience with computational modeling and machine learning. The ideal candidate will be able to process and analyze high dimensional
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of genomic, epigenomic, and transcriptomic data processing and analysis, expertise in multi-omics data integration, and working experience with computational modeling and machine learning. The ideal candidate
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integration, and working knowledge of computational modeling and machine learning. The ideal candidate will be able to analyze high dimensional sequencing data, perform network-based analysis (e.g. , WGCNA) and
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of gerontology: https://gero.usc.edu The Irimia Laboratory leverages neuroimaging, neurogenomics, and deep learning to study the aging brain in health and disease, particularly in neurodegenerative conditions like
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tissue samples. The ideal candidate will have prior experience in the analysis of single-cell transcriptomic datasets and is eager to learn and develop new spatial transcriptomics approach