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and publications. Required Qualifications • PhD in Mathematics, Engineering, or a related field with a background in statistical and mathematical modeling. PhD must be awarded no more than four years
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Foundations of Artificial Intelligence Applications should hold a PhD in Computer Science, Electrical and Computer Engineering, Applied Mathematics, or related disciplines and must demonstrate research
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Interdisciplinary Training in Mathematics for Human Health,” supported by the National Science Foundation. RTG themes include modeling in cancer biology, computational neuroscience, and mathematical epidemiology
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. Qualifications • PhD degree in computational biology, bioinformatics, mathematics, physics, engineering, computer science, or a related field. • Computational background in areas such as AI/deep learning
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Computational Neuroscience ● Mathematical/Theoretical Foundations of Artificial Intelligence Applications should hold a PhD in Computer Science, Electrical and Computer Engineering, Applied Mathematics
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Computational Neuroscience ● Mathematical/Theoretical Foundations of Artificial Intelligence Applications should hold a PhD in Computer Science, Electrical and Computer Engineering, Applied Mathematics
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a PhD in computer science, information science, bioinformatics, biostatistics, mathematics, nutrition, epidemiology, biomedical engineering, medicine, or a related science field. Candidates should
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for duties undertaken remotely. Required Qualifications: A PhD degree in Biostatistics, Statistics, Computer Science or a related field who possess STRONG computing/programming and communication skills
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of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related
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mathematics and engineering. The Interpretable Machine Learning Lab has dedicated access to high-performance CPU and GPU computing resources provided by Duke University’s Research Computing unit and state