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radiopharmaceuticals. The project will build on the PET reporter gene technology that we have recently developed and apply it for the in vivo tracking of gene vectors and their genetic payload. The different vectors
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the thermomechanical performance of the refractory masonry; Application of advanced statistical analysis algorithms, including sensitivity analyses and comparisons of different algorithm types; Development
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algorithms are creating new opportunities for Duke students and faculty, working together in multidisciplinary teams, to actively engage with and to change the world around them. These emerging areas, in turn
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research. The Rhodes Information Initiative is a driver of exciting data science, computing, and AI initiatives at Duke. Access to unprecedented amounts of information, computing power, and AI algorithms
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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
applications for air quality management. This will include acquiring datasets related to multiple air quality sensors from diverse data sources, develop open-source, easy to use tools to compare different types
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years. There are four scientific Divisions - Structural Studies, Protein and Nucleic Acid Chemistry, Cell Biology and Neurobiology. However, scientific collaboration between the different Divisions is
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from vascular lesions and blood, combined with genetic, clinical/epidemiological and imaging parameters from patients. We also perform in depth functional studies in animal and cell culture models
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requirements: Experience using deep-learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating on scientific projects. Publications on deep-learning topics. 4. Work Plan
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be duly proven at the time of hiring. 2; 3. Preferred requirements: Experience using Machine Learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating