91 machine-learning "https:" "https:" "https:" "https:" "https:" positions at University of Colorado
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. • Excellent computer skills, particularly with databases and e-communication. • Knowledge of study abroad management tools. • Ability to use Terra Dotta software. • Ability to learn data analysis and
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in natural sciences such as anatomic biology, chemistry, or related field. Substitution: A combination of education and related technical/military/paraprofessional experience may be substituted for a
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assistants who are looking to learn and development their dental dispensary knowledge and experience. We welcome applications from individuals who are collaborative, communicative, caring, detail oriented
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- $130,000.00 Position #00350978– Requisition #38058 About the University of Colorado - Denver Millions of moments start at CU Denver, a place where innovation, research, and learning meet in the heart of a
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an individual who will primarily work both with mice and at the bench and will interface with the whole research team. Our ideal candidate is excited to learn new skills and has had recent coursework in a
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to be eligible for overtime (non-exempt) under the Fair Labor Standards Act (FLSA). This position is eligible for paid sick leave. Information on benefits, including eligibility, is located at: http
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. Knowledge, Skills, and Abilities: Able to perform basic computer functions. Learn and develop knowledge and skills in job specific responsibilities. Effective oral/written communication skills; effective
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. Participation in regular team huddles, meetings, and staff development sessions is required. The position also encourages ongoing professional growth through CU’s robust learning and development resources. About
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processing and other computer systems, as necessary, for financial management and statistical reporting. Utilizes multiple systems for purchasing, human resources, facilities management, daily operations and
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-tenure track positions and will teach no more than two courses per semester. Appointments will be part-time (less than 50%) and will be made semester-by-semester, depending on the needs of the department