75 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" positions at Johns Hopkins University in United States
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Duties and Responsibilities Run routine and ad hoc reports. Use standard tools and computer programs to review data. Assist with data cleaning measures to ensure accuracy of data and preparation of tables
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for Simulation & Immersive Learning at the Johns Hopkins School of Nursing will foster the development of an internationally recognized immersive learning and digital innovation ecosystem, leveraging technology to
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to provide background information. Obtain and maintain excellent operating knowledge of assigned clinical protocol, clinical equipment, and clinical computer systems. Oversee budget expenditures for study
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Biological/Biomedical Sciences Computer/Information Sciences Medical - Research Internal Number: A-179992-4 General Description Laboratories in the Department of Biophysics and Biophysical Chemistry at Johns
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modeling, machine learning methods, and applications involving text and other non-traditional data sources. The fellow will contribute to and extend research in these areas, engaging in projects that develop
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of clinical samples. Obtain and maintain excellent operating knowledge of assigned clinical protocols, clinical equipment, and clinical computer systems. Oversee budget expenditures for study operations. Ensure
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. Specific Duties & Responsibilities Run routine and ad hoc reports. Use standard tools and computer programs to review data. Assist with data cleaning measures to ensure accuracy of data and preparation
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to remain in a stationary position for extended periods of time. Ability to operate a computer and other equipment on a frequent basis. Ability to frequently communicate with coworkers. Ability to see within
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or similar functions/tasks for research study(ies) in support of a PI or a research team. Specific Duties & Responsibilities Run routine and ad hoc reports. Use standard tools and computer programs to review
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DSAI clusters: •Foundational methods of Machine Learning, Data Science, and Artificial Intelligence •Embodied AI Systems •Health and Medicine •Scientific Discovery •Engineered AI systems •People, Policy