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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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research. The ideal fellow will be interested in developing and applying novel computational algorithms to novel datasets generated in the setting of non-neoplastic and neoplastic disease. Key
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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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into the brain's algorithms of perception and cognition while serving as a key resource for aligning artificial intelligence models with human-like neural representations. As part of this project, we are seeking
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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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University is recruiting postdoctoral scholars with prior training in statistics, biostatistics, computer science, bioinformatics or a closely related area. Applications are invited from ambitious, independent
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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
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the
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internal equity. Pay Range: 76,383-86,383 Our lab investigates the functional principles, development, and computational properties of organism-wide circuits for brain-body interactions. We