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theory, multi-objective optimization and machine learning. The specific project aims to understand the multiscale interactions shaping human gut bacteria and human gut pathogens. The project will combine
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environment at Duke is ideal for our translational research efforts. Applicants must : 1. Hold a PhD with relevant skillsets in programming (including Python) and machine learning methods for image
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recent Ph.D. in microbiology, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative
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developing and applying advanced statistical models, machine learning, and deep learning approaches. As such, we seek applicants with strong quantitative backgrounds in remote sensing and time series analysis
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, ChIP-seq, and ATAC-seq, CRISPR and RNAi perturbation screens 3. Ability to build predictive statistical and machine learning models that integrate multiple data types, including linear and nonlinear ML
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interested in applicants that have experience in one or more of the following areas: satellite remote sensing, energy balance modeling, and machine learning. In addition to scientific expertise, the successful
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, spanning machine learning, wearables, and physics-based models. The applicant must be detail-oriented, independent, proactive, well-organized, and able to manage multiple and changing priorities as needed