244 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at University of Oregon in United States
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Apply now Job no:536154 Work type:Classified Staff Location:Eugene, OR Categories:Administrative/Professional, Administrative/Office Support, Computer and Information Science, Data Science
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with the ability to teach various applied real estate courses, including but not limited to real estate finance, real estate investment analysis, real estate development, commercial real estate, real
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plans, and paid time off. For more information about benefits, visit https://hr.uoregon.edu/about-benefits . The University of Oregon is an equal opportunity, affirmative action institution committed
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, retirement plans, and paid time off. For more information about benefits, visit https://hr.uoregon.edu/about-benefits . The University of Oregon is an equal opportunity, affirmative action institution
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(dark matter, baryogenesis) and machine learning applications in these topics. The University of Oregon also has an experimental high energy physics group involved in the ATLAS experiment at the LHC and
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Department of Biology may be found by visiting the Biology website at http://biology.uoregon.edu/. Position Summary The Department of Biology is soliciting applications for its open applicant instructor pool
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is a thread that runs through our majors and programs while focusing on critical and effective pedagogies. We are committed to building and sustaining an inclusive and equitable working and learning
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problems across diverse domains. Through collaboration with industry and academic partners, the Data Science Department fosters a vibrant and dynamic learning environment, preparing students for a successful
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ourselves on the diversity of our faculty and the broad range of our course offerings and research projects. We aim to build a sense of intellectual collaboration among members of the department’s learning
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, overall facilitating interdisciplinary collaboration across the university. Current faculty and affiliates reflect strengths in machine learning, biological modeling, data ethics, data sovereignty