2,885 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at University of Washington in United States
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employees: https://facilities.med.wustl.edu/Careers. This role is responsible for maintaining and repairing lighting and plumbing systems, performing minor repairs, and ensuring compliance with safety
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3M computer assisted coding (CAC) to compute the final DRG assignment to diagnoses and procedures in an integrated system to ensure the appropriate coding for the facility inpatient billing and
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design, data analysis, and documentation of experiment results. Job Description Primary Duties & Responsibilities: Develops algorithms and computer software for omics-based data sets [high-throughput
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Telephones, Clinical Practice, Computer Literacy, Confidential Data Handling, Confidentiality, Customer Service, Data Entry, Electronic Medical Record (EMR) Systems, Epic EHR, HIPAA Compliance, Leadership
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Compensation: - Benefits: For information about benefits for this position, visit https://www.washington.edu/jobs/benefits-for-uw-staff/ Shift: First Shift (United States of America) Temporary or Regular
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, Benefits and Position Details Pay Range Minimum: $30.61 hourly Pay Range Maximum: $43.81 hourly Other Compensation: - Benefits: For information about benefits for this position, visit https
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: $32.82 hourly Pay Range Maximum: $51.42 hourly Other Compensation: - Benefits: For information about benefits for this position, visit https://www.washington.edu/jobs/benefits-for-uw-staff/ Shift: First
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, Benefits and Position Details Pay Range Minimum: $49.23 hourly Pay Range Maximum: $90.33 hourly Other Compensation: - Benefits: For information about benefits for this position, visit https
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$4.00/hr Weekends $1.00/hr BSN premium Benefits: For information about benefits for this position, visit https://www.washington.edu/jobs/benefits-for-uw-staff/ Shift: First Shift (United
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blood samples to advance patient care. This role will involve developing computational models (statistical, machine learning, etc.), and using them to perform high throughput analysis of clinical data