2,686 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" uni jobs at University of Washington
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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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Acrobat, Analytical Thinking, Computerized Accounting, Computer Literacy, Deadline Management, Grant Administration, Grant Applications, Interpersonal Communication, Learning New Technologies, Maintaining
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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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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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Administration, Academic Support, Adaptability, Computer Literacy, Confidentiality, Financial Systems, Human Resources (HR) Software Systems, Independent Decision-Making, Interpersonal Communication, Learning
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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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% 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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mindset with a strong desire to learn and stay current on best practices and emerging capabilities to visualize and communicate data. Proficiency with Microsoft Software Suite and project management
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safe, inclusive, and transparent clinical and educational environment. The Department fosters learning and collaborative engagement to advance patient care and medical knowledge. The Department values