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Field
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, a person in this position will be a key contributor to the design and implementation of algorithms, AI/ML models, and workflows to enable the discovery of valuable information in large volumes of data
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and AI applications. This includes ensuring compliance with federal, state, and institutional regulations, as well as industry best practices related to data privacy, algorithmic fairness, and
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will apply state-of-the-art machine learning algorithms and custom disease-relevant genomic datasets (e.g., coronary artery single-nucleus chromatin accessibility and RNA sequencing) to develop targeted
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or gender identity, genetic information, military service, national origin, pregnancy and related conditions, race, religion, sex, veteran status, or any other basis prohibited by law. Essential Job Functions
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to, benefit-harm analysis of cancer early detection tests, development of clinical decision rules in cancer early detection leveraging Electronic Medical Records (EMRs), and development of EMR-based algorithms
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at an accelerated pace ? radically affecting our homes, workplaces, streets, and neighborhoods. Often, the effects of these transformations are hidden from clear view, occurring in the black box of the algorithm
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of Health (NIH)'s Genomics Research to Elucidate the Genetics of Rare disease (GREGoR) Consortium. The GSS (https://gregor.stanford.edu/ ) mission is to provide a platform for functional genomics research and
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and algorithm-based technologies in service occupations, with a focus on how collective bargaining and other forms of collective worker voice influence these strategies and worker outcomes. The US
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bioinformatics, computational biology, and clinical genomics to assist in identifying, evaluating, and incorporating relevant algorithms and software. Educates and mentors colleagues, investigators, fellows, and
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Description Primary Duties & Responsibilities: Implements: Algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical]; Data management