715 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" research jobs in United States
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to be part of a unique and diverse community that works on high-impact research, educational, business, and societal problems. Position Summary The Machine Learning Researcher - Epidemiology will report
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/ ). The successful candidate will develop web pages and front-ends to showcase new drug discovery tools and databases used to train innovative machine learning models. This is an outstanding opportunity
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performance management system. Physical Requirements (With or Without Accommodations): • Visual acuity to read information from computer screens, forms and other printed materials and information. • Able
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and quantitative gene expression analysis Excellent organizational, communication, and teamwork skills Certificates/Credentials/Licenses Computer Skills General office suite and willingness to learn lab
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 14 hours ago
and machine learning, and for the public to see the worlds of the outer solar as they would appear to our eyes for the first time. The envisaged project includes: image selection, cleaning and
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the world. Each of the four campuses (two in Chicago, one in London, and one in Hong Kong) reflects the architectural traditions of its environs while offering a state-of-the-art learning environment. Chicago
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well as leading efforts in mutual learning among researchers, practitioners, advocates, community organizers, and policymakers. The Associate will conduct research in the context of research practice partnerships
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to launch impactful careers. To learn more about the SCALES Postdoctoral Fellowship Program, visit our program page: https://climate.duke.edu/what-were-doing/scales-postdoctoral-fellows-program/ . Key
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techniques, microscopy, immunohistochemistry protocols and protein biochemistry. Certificates/Credentials/Licenses N/A Computer Skills Basic Word and Excel software knowledge as well as proficiency with
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, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental