376 parallel-and-distributed-computing-"Meta"-"Meta" positions at Baylor College of Medicine
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- both digital and analog, high-definition and standard definition, including, but not limited to: projectors, computers, video cameras, lighting equipment, audio gear, and video conferencing software as
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interpret the findings. Additionally, this position entails maintaining patient experience data and overseeing existing patient survey processes using a variety of software and computer applications. Job
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Qualifications Associates degree or certificate from an accredited program in Health Information Management. Three to six months of coding training which includes but not limited to medical terminology, human
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an assessment, if warranted, and follow-up with health and/or mentalhealth providers. Coordinates and triages consultations and referrals for students when identified as at-risk. Assists school/program leadership
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Education in Adolescent Health (LEAH) training grant. The LEAH Program is designed to reduce health disparities and improve the health and well-being of adolescents and young adults by training future leaders
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with the Business Development staff to coordinate relationships with external/referring physicians for the program, as appropriate. Actively participates in a wide range of performance improvement and
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, shipping and receiving of research materials. Performs other laboratory job related duties as assigned. Conducts preclinical computer tomography (CT), positron emission tomography (PET), optical, ultrasound
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state and federal regulations. Participate in on-call rotation as scheduled. Minimum Qualifications MD or DO from an accredited institution. Completion of an accredited Anesthesiology residency program
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Qualifications Education Required: Master's degree from an accredited Anesthesiology Assistant Program by the Commission on Accreditation of Allied Health Education Programs (CAAHEP). Note: Bachelor's degree in
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original research in intestinal regeneration and repair with a focus on the intestinal stem cell. This project utilizes state of the art organoid model systems combined with computational and cell biology