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genetics and genomics, with expanded interests in computational biology, functional genomics, and neuroscience. Example projects within the university and with external partners: ⢠Noncoding Variation in
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, computational genomics, functional assays, and integrated data analysis. We are seeking a highly motivated Postdoctoral Researcher who shares our passion for solving foundational problems in human genetics and
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learning algorithms into professional software with an intuitive user interface, incorporating feedback from CHWs through iterative design and evaluation cycles. The selected candidate will be part of a
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, applying state-of-the-art sensing technologies and self-developed algorithms. Minimum Qualifications • Ph.D. in Mechanical or Industrial Engineering, and other fields that explore Artificial Intelligence
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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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, and experience in the algorithms used to analyze these datasets. The appointee will ultimately create an independent research effort with dedicated extramural funding that complements existing strengths
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architectures and training algorithms, uncertainty quantification, high-dimensional stochastic systems and high-dimensional partial differential equation systems. Multiple positions available. About the T-5 Group
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Preferred Qualifications: Experience with one or more of the following: Building novel 3D and super-resolution ultrasound systems. Developing deep learning algorithms for 3D biological data. Designing and
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that integrate simulation, machine learning, and data analysis. Numerical optimization methods (e.g. machine learning including deep neural networks, reinforcement learning, data mining, genetic algorithms
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expertise across multiple levels—from circuits and architectures to algorithms, models, and systems—and includes opportunities for radiation testing at the NASA Space Radiation Laboratory (NSRL