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, conducting research on key aspects of the foundations of data science. Areas of focus include sublinear, streaming, and sketching algorithms; learning-augmented algorithms; algorithmic fairness; and learning
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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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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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, 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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, the postdoctoral associate will help to coordinate evidence-based learning networks of NPS units and other educational organizations to (1) direct data collection and conduct research on their programs and
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facilitate team meetings. (6) Mentor master’s and PhD students. (7) Teach a 1:1 course load in year 2 of the position.
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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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well as part of a project team with a remote sensing professor and PhD student. The university values diversity and continually strives to maintain and promote an inclusive learning and research environment