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in preparation for a full time academic or research career. Associates will be co-mentored by PhD faculty with extensive technical experience with machine learning and deep learning. Lab website:https
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. Projects in the lab focus on understanding how neurobiological networks for motivation are regulated and how these networks, in turn, optimize learning. As the neural systems studied are the targets of many
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. Description of research, communication and supervisory activities: The successful candidate will have the demonstrated ability to perform, or be willing to learn, the following tasks in a BSL-2 (biosafety level
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treatment grant (PI: Andrada D. Neacsiu, PhD). This is a 2-year appointment, with the second-year contingent on renewal and with the possibility of extension to a third year. This postdoctoral fellow will be
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Bayesian modeling and machine learning using large longitudinal biomedical data, including electronic health records and mobile health data. The position will be funded by Samuel I. Berchuck, PhD who holds
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-learning methods to analyze cutting-edge single-cell and spatial genomics data in pulmonary research. There is a unique opportunity to discover functions and behaviors of cells in lung tissues and identify
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-pathogen genetics interactions that drive distinct tuberculosis disease states. We seek a post doc with either a strong mammalian genetics background that wants to learn cutting-edge bacterial genetics