163 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Baylor College of Medicine
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next-generation CAR T-cell therapies for pediatric solid tumors. The fellow will apply high-throughput screening, T-cell engineering, and single-cell analytics to identify and validate novel receptor
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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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of relevant experience. Department-Specific Requirements SQL and R programming. Machine Learning and NLP. Preferred Qualifications and Skills Master's degree in Management Information Systems, Computer Science
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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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be expected to teach fellows within the BCM Endocrinology Fellowship program. The Section of Endocrinology at BCM has over 20 faculty members with multiple active research grants from NIH, VA, and
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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