156 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Baylor College of Medicine
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anesthesia machines, and digital radiography in proper working order. Minimum Qualifications Associate's degree in a related field. Two years of related experience may substitute for degree requirement
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and computer analysis work spaces. Maintains patient records and results documentation. Utilizes computer appropriately for entry of patient inquiry, specimen inquiry, test results, and quality control
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Qualifications High school diploma or GED. Six months of relevant experience. Preferred Qualifications Knowledge of HIPAA. Computer literacy. Work Authorization Requirement: This position is not eligible for visa
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.) Familiarity with community-engaged public health research. Experience answering or administering questionnaire. Experience with using or designing computer-based survey instrument (e.g., RedCAP, SurveyMonkey
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regulations and procedures. Recommends processes to improve efficiency and reduce costs. Tracks and documents the logistics of material using computer software and scanners. Provides assistance to internal and
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physician orders and explaining processes. Operates radiographic equipment and computer systems to produce and document diagnostic images. Performs daily, monthly, and quarterly quality control checks
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; multi-level regression, semi-parametric models, latent variable modeling, and machine learning methods. Ability to use different software to address the increasing complexity of health-related data
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phenotyping, handling of infectious diseases, and in vivo imaging Experience with or willingness to learn Microsoft PowerApps, PowerBi, and PowerAutomate Work Authorization Requirement: This position is not
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administrative functions. Coordinates learning BCM & TCH's applications and administrative processes. Composes formal and informal correspondence including, but not limited to, creating and formatting
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understanding regulations related to human subjects’ research. The internship is designed to help the participant learn how research teams operate, how study data are collected and verified, and how to contribute