157 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Baylor College of Medicine in United States
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Candidates with computer skills (email, Excel, Word) are preferred. Work Authorization Requirement: This position is not eligible for visa sponsorship. Candidates must be legally authorized to work in the
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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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Education the scheduling, collection and analysis of all student and course assessment activities. • Coordinate with the Associate Director of Experiential Learning the scheduling, collection and analysis
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candidate will have operational experience with addressing human health and performance challenges in limited resources environments such as space, military or extreme environments such as expeditionary treks
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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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; 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