2,913 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" positions at University of Washington
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hourly Other 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
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hourly Other 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
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maintain hand tools and power equipment such as brooms, mops, squeegees, vacuums, carpet cleaners, floor machines, power washers, and other tools required for the cleaning and general maintenance of the UW
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designated area on foot or in a patrol car to enforce institution rules and regulations, local, state, and federal statutes, and ordinances Inspect buildings and grounds for trespassers, fire, property damage
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benefits that may be available at https://faculty.uwmedicine.org/wp-content/uploads/2019/09/UWP-Benefits-Summary-for-recruitingef-edits-v3.pdf Qualifications Applicants must have an MD or DO degree
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skills Ability to handle multiple tasks concurrently Ability to adapt to changes in the external environment to include being exposed to inclement weather and work in environments or under conditions that
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% at WashU and 40% elsewhere after seven years with us. For policies, detailed benefits, and eligibility, please visit: https://hr.wustl.edu/benefits/ EEO Statement Washington University in St. Louis is
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with us. For policies, detailed benefits, and eligibility, please visit: https://hr.wustl.edu/benefits/ EEO Statement Washington University in St. Louis is committed to the principles and practices
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undergraduate-level college tuition up to 100% at WashU and 40% elsewhere after seven years with us. For policies, detailed benefits, and eligibility, please visit: https://hr.wustl.edu/benefits/ EEO Statement
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extracted from electronic health records, using Python, R, and other relevant tools. Applies statistical and machine learning methods (e.g., descriptive statistics, supervised and unsupervised learning