798 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at University of Colorado
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bottom line. Total Compensation Calculator: http://www.cu.edu/node/153125 Equal Employment Opportunity Statement: The University of Colorado (CU) is an Equal Opportunity Employer and complies with all
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on building and maintaining workflows for the analysis of large-scale genomic datasets, data management, and machine learning methods application. The ideal candidate will be proficient in, or highly motivated
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, health plans and retirement contributions that add to your bottom line. Total Compensation Calculator: http://www.cu.edu/node/153125 ADA Statement: The University will provide reasonable accommodations
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. The University of Colorado provides generous leave, health plans and retirement contributions that add to your bottom line. Total Compensation Calculator: http://www.cu.edu/node/153125 Equal Employment Opportunity
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setting and individually. We seek an individual who thrives in a team environment, is willing to learn, and prioritizes customer service. Key Responsibilities: Creates job postings in the applicant tracking
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Department of Family Medicine (DFM) mission is “To heal, teach, discover, and connect. Together." by educating, nurturing, fostering, and enhancing those in family medicine and the communities we live in and
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/interpret the physical exam process and record exam details. Ability to attest to computer proficiency and learn new computer applications. Ability to keyboard/type, write legibly, and accurately record
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and ability to meet deadlines. Ability to work well in a group setting. Excellent computer skills. How to Apply: For full consideration, please submit the following document(s): 1. A letter of
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of Colorado provides generous leave, health plans and retirement contributions that add to your bottom line. Perks & Benefits: https://advantage.cu.edu/search Total Compensation Calculator: http://www.cu.edu
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of Department of Ophthalmology in the University of Colorado School of Medicine focuses broadly on quantitative and machine learning techniques in multiple modalities of medical imaging (e.g. fundoscopy images