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interpretable deep neural networks is required. Candidate must have published in top journal and conference at least one scientific paper in interpretable machine learning (not explanations of black boxes) among
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pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental
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microbial community behaviors. We seek to understand and engineer the spatiotemporal behaviors of biological networks using tools from systems and synthetic biology. A major goal is to design novel strategies
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national networking opportunities within Duke and in the broader scientific community. This is a full time, grant funded position, eligible for all Duke benefits (https://hr.duke.edu/benefits ) with