174 machine-learning "https:" "https:" "https:" "https:" positions at University of Texas Rio Grande Valley
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resources and watershed issues, locally and beyond, is expected. We expect the successful candidate to acquire external funding from organizations like the NSF, NOAA, and other environmental agencies while
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responsibilities. The successful applicant will teach in our BSW, MSSW, and dual-degree programs; contribute to the development of our doctoral program and teach doctoral courses; and work with our Office for
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and publications in human genetics. The successful candidate will conduct research in bioinformatics and computational genomics, teach at the doctoral level, and mentor graduate students in the Ph.D
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epidemiology. The successful candidate will conduct statistical genetics research, teach at the doctoral level, and mentor graduate students in the Ph.D. Program in Human Genetics. The successful candidate is
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years teaching experience, which enables them to teach combinations of molecular/cell biology, biochemistry, neuroscience, cell and molecular biology, microbiology, immunology, genetics/genomics
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or a strong aptitude for using advanced computational tools, AI, or machine learning techniques to address engineering challenges; and interest or initial experience in interdisciplinary collaboration
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journals or conferences; experience with or a strong aptitude for using advanced computational tools, AI, or machine learning techniques to address engineering challenges; and interest or initial experience
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expected to teach in our undergraduate and/or graduate nursing programs. About UTRGV: UTRGV serves the Rio Grande Valley and beyond via an innovative and unique multicultural education dedicated to student
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candidate will be expected to: 1) teach undergraduate and graduate courses in rangeland management, covering topics such as range ecology, rangeland improvements and restoration practices, and rangeland
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the participation of all health-related programs and create a stronger framework for collaboration and impact among health-related programs. The goal is for the division to boost interdisciplinary learning, enhance