23 machine-learning-"https:"-"https:"-"https:"-"https:" research jobs at Indiana University in United States
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college) Preferred Bachelor's degree WORK EXPERIENCE Preferred 1 years of experience working in an office environment utilizing computer programs to complete a variety of detail-oriented tasks SKILLS
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Proficient in personal computer (PC) use and Microsoft Office Attention to detail Possesses excellent communication and organizational skills Demonstrates dependability, as well as positive phone and people
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using laboratory machinery and computer programs. Test and set up lab equipment. Collect data and prepare reports based upon established protocols. Attend and participate in departmental meetings. Order
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Location Indianapolis Position Summary Are you passionate about genomics, big data, drug discovery, and AI/machine learning? Interested in advancing cutting-edge multi-omics research to explore genetic and
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Qualifications Experience with machine learning and AI models. Ability to communicate clearly with colleagues, Data presentations Scientific publication experience Special Instructions Priority Application Review
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off plans Paid leave for new parents and IU-sponsored volunteer events Employee assistance program (EAP) Learn more about our benefits by reviewing the IU Benefit Programs Brochure . Career Level: Part
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excellence. We seek candidates whose research, teaching, and community engagement efforts contribute to heterogenous, robust, and collaborative learning, working, and patient care environments for all of our
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whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our
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year Generous paid time off plans Paid leave for new parents and IU-sponsored volunteer events Employee assistance program (EAP) Learn more about our benefits by reviewing the IU Benefit Programs
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to grant development IUSM is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working