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approaches, including Low Impact Development (LID) practices (e.g., green roofs, rain gardens), with a specific focus on urban catchments. The research will place a strong emphasis on machine learning
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experiments. Data & Analysis: • Collaborate with data scientists to analyze host and microbial data using statistical, bioinformatic, or machine learning approaches. • Contribute to the integration of spatial
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-dimensional variable selection, longitudinal and survival analysis, machine/deep learning, bioinformatics methods in -omics data are preferred. Demonstrated evidence of excellent programmin g, collaboration
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, methods will include video- and machine-learning supported behavioral studies in mice, mouse genetics, fluorescent imaging, electrophysiology, pharmacological studies of irritant and thermosensory receptors
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, creativity, rigor, ownership, and excitement to push research in TRL forward. Theoretical knowledge of, or experience with, machine learning such as representation and generative learning, data management, and
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of Amsterdam. Interested in developing fundamental machine learning techniques for tabular data to democratize insights from high-value structured data? Then this fully-funded 4-year PhD position starting Fall
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Associate The Responsive Apparel Design (RAD) Lab at Cornell University is seeking a highly motivated and talented postdoctoral researcher to join a collaborative As part of Cornell University, a world-class
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Post Doc Associate The Responsive Apparel Design (RAD) Lab at Cornell University is seeking a highly motivated and talented postdoctoral researcher to join a collaborative The Responsive Apparel
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Post Doc Associate The Responsive Apparel Design (RAD) Lab at Cornell University is seeking a highly motivated and talented postdoctoral researcher to join a collaborative team focused on