14 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" uni jobs at University of New Mexico in United States
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to apply computational approaches to research questions. Experience or familiarity with artificial intelligence and machine learning methods is highly desirable. Prior research experience in a laboratory
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system setpoints and outputs using remote computer links and programmable logic controls. Ensure proper care and maintenance of tools, equipment, and supplies. Promote continuous improvement in workplace
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substituted for experience on a year for year basis. Preferred Qualifications Adept on multiple computer software applications and confident learning new systems Experience with complex scheduling, preferable
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hiring a Data Scientist 2 to support cutting-edge machine learning modelling of carbon and water fluxes and scaling to the watershed scale. The candidate will be responsible for processing of in situ
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for year basis. Preferred Qualifications Adept on multiple computer software applications and confident learning new systems Experience with complex scheduling, preferable in Outlook Experience
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to effectively communicate, orally and in writing, analytic results to clinicians and the study team. Knowledge and experience in informatics techniques (i.e. machine learning) Additional Requirements Campus
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photography lab, scheduling printing time with student (via google docs), troubleshooting Epson printers, scanners, Adobe Photoshop and Lightroom, fielding general computer/camera questions, maintaining
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for year basis. Preferred Qualifications Adept on multiple computer software applications and confident learning new systems Experience with complex scheduling, preferable in Outlook Experience
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Writing Consultant for assistance with your application materials. Go to this page to find Bookings, where you can make an appointment: https://valencia.unm.edu/campus-resources/learning-commons/index.html
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. · Experience developing, testing, and refining statistical and machine learning models to identify key drivers of student learning, retention, and academic success. · Supervising and mentoring staff and