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for entanglement detection and classification. The algorithms are supported by affordable, spatial surface and subsea sensing and a low-power edge computing to collect and compress datasets at-sea, allowing the
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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 bulk and single
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/or experience with large-scale data analysis, algorithm development, or computational modeling. Required Qualifications: Doctoral degree in linguistics, cognitive science, psychology, hearing and
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. Prior Research Fellows have been accepted by PhD programs in computer science, economics, and political science and JD programs at top schools (e.g., Harvard, Stanford, Princeton, Yale). In recent years
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will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
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disease progression. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will