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Field
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fields include (but are not limited to) Computer Science, statistics, mathematics, automation, informatics, and Engineering. • Experience in deep learning, machine learning and medical imaging processing
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primary mentor on research at the intersection of educational data science, AI in Education, and the learning sciences, with additional advisory support from faculty and researchers in the learning sciences
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-on experience that provides an understanding of the mission, operations, and culture of the DOE. As a result, fellows will gain deep insight into the federal government's role in the creation and implementation
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in Dr. Xiaoyi Lu’s PADSYS Lab to investigate scalable system software for emerging applications such as precision agriculture, digital twins, deep learning, and so on. The Postdoc will also be focused
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Computational Biology, Machine Learning and Deep Learning for Computational Biology, Computer Science, Applied Physics and Mathematics, or a related field. - Strong background in protein modeling, structural
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and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation-tools.php CBC Requirement It is the policy
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scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) novel development of deep learning ML models and adaptation of existing ones
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
the ability to design and implement novel artificial intelligence algorithms. Examples of research directions could include: multimodal foundational models for biomedical data, deep-learning architectures
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opportunity promises deep academic inquiry, industry collaborations, and the chance to influence future practices and research directions in these fields. Key Responsibilities: Develop robust mathematical and
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field with a strong background in AI, machine learning, or deep learning). Demonstrated experience with CFD and/or FEA, particularly in biomedical applications preferred. Proficiency in programming