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and existing tools to interpret, analyze, and visualize multivariate relationships in data. Create databases and reports, develop algorithms and statistical models, and perform statistical analyses
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unprecedented insights 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. We are seeking a
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the design and development of multiple projects using state-of-the-art AI models, algorithms, statistical models, and other programs designed to improve the public sector. Work with large untapped data
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and implement generalizable algorithms and tools for analysis of biological data, including high-throughput functional genomics assays Evaluate and recommend new emerging technologies, approaches, and
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. This work involves developing novel techniques, algorithms, and software packages that enable more robust and scalable approaches to cybersecurity using AI-based techniques. In addition to technical
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into tangible products. Critically, this work will generate a large open-source dataset of child-created games that can inform future designs of educational games and AI algorithms. The postdoctoral fellow will
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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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systems. Includes establishing medical reasoning benchmarks and automated / scalable evaluation methods. Developing recommender algorithms to predict specialty care with large-language model based user
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. 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 involve both method
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cancer epidemiology with a Ph.D. degree in biostatistics, operation research, epidemiology (with strong computation skills), or related fields and hands-on experience in algorithmic implementation and