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the best interest of our communities. We are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by
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will join a multidisciplinary team to work on cutting-edge research projects to develop and apply data mining/machine learning approaches on high dimensional biological and clinical datasets. The initial
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are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and
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of educational technology, instructional design, and learning theories. • Design and evaluation of AI-powered learning environments that personalize instruction using machine learning, Natural-Language Processing
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++, and Python. Preferred Qualifications Prior research experience in computer systems and distributed computing is preferred. However, strong research experience in developing/applying machine learning
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are seeking excellent candidates with interests in a wide range of topics within the mathematical, statistical, machine learning, artificial intelligence, data analytics, and foundations and applications
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or an equivalent doctoral degree in a related field (e.g., learning sciences, human-computer interaction, information sciences) by August 2025. Demonstrate a strong understanding of learning theories and solid
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for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your work as part of our UNT
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standards and acting in the best interest of our communities. We are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure
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candidates in research areas of Artificial Intelligence/Machine Learning, Autonomous Systems, Bioinformatics/Computational Biology, and Computer Architecture. Candidates are encouraged to look at our current