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Northern Virginia schools; Experience in technical learning environments and project-based experiences in computer science, data analytics, artificial intelligence, and other emerging technologies in
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critical role in advancing computational materials science by developing and applying first-principles and machine learning methods, with a focus on interatomic potential development and large-scale
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, genomic datasets, machine learning, and experimental methods to investigate how the tumor microenvironment and gene regulatory factors control tumor metastasis cascade. By advancing our understanding
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Alexandria, Virginia. The focus of these positions will be on quantum computing, quantum algorithms, quantum learning, quantum error correction, and quantum fault-tolerance. The successful candidate will join
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interdisciplinary team at the NSF COMPASS Center, which integrates tissue engineering, stem cells, materials, virology, computational biology, machine learning, molecular environmental engineering, science
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and networking, with a particular focus on 5G and Beyond 5G technologies and applications of artificial intelligence and machine learning to wireless systems. The candidate will oversee the design and
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, machine learning, optimization, and statistical data analytics are sought. Successful applicants will have experience applying these tools to a range of data problems, such as time-series analysis