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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2. Modeling for Regulatory Science – Leveraging drug development and regulatory
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(with the potential to be extended) with the Alabama Center for the Advancement of Artificial Intelligence. Leads the forefront of research in artificial intelligence, machine learning, and data science
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to teach two courses per year: one lower-level course, such as Introduction to African American Literature, and an upper-level course such as Black Aesthetics, Early African American Print Culture, or a
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, together with significant experience in computer programming and computational biological applications. A strong background in statistics and biology. Formal training and/or research experience in genomics
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who shares our values and who will support the mission of the university through their work. Qualifications: Ph.D. in a relevant field such as Learning Sciences, Human-Computer Interaction, Education
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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statistical software. Learning Objectives: Learn about the implementation of the application of machine learning methodologies in plant phenotyping and genotyping for the sugarcane molecular biology lab. Learn
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staff in exhibit preparation, including object research, selection, mounting, and installation as needed. Fellowship Learning Goals Learn and follow recognized standards and policies for collection
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who shares our values and who will support the mission of the university through their work. Qualifications: Ph.D. in a relevant field such as Learning Sciences, Human-Computer Interaction, Education
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results. Preferred Qualifications: Experience with generative AI deep learning and active involvement in data science and machine learning projects. Experience in neural network architecture, cloud