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properties of macromolecules, developing novel ways to combine quantum chemical methods and machine learning, developing quantum algorithms for computational chemistry on quantum computers, and applying
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research should they wish it. Bucknell has numerous opportunities to both learn how to be an effective teacher and to teach courses and labs both in the electrical and computer engineering department and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 hour ago
in large language models, machine learning, and natural language processing, combined with a collaborative spirit and a drive for problem-solving. You’ll join a multidisciplinary team that values
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. Completion and approval of a UT Dallas Remote Work Agreement will be required upon employment, and use of personal computer, internet, and other standard equipment may be required. Remote work arrangements are
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deep learning / computer vision / biomedical image computing Excellent English; German is an advantage for clinical collaboration We offer Highly interdisciplinary, translational research environment
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areas in data science and engineering systems. Required Knowledge, Skills, and Abilities Demonstrated expertise in computational sciences and numerical modeling. Demonstrated expertise in machine learning
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main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications
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of research and education, covering all aspects of computer science, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking
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events. Maintain and perform analysis on large quantitative datasets; develop and implement statistical or machine learning models to recover patterns of technology adoption, task organization and skill
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and