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candidate will contribute to projects involving participants with implanted intracranial electrodes and wearable non-invasive sensors, with a focus on memory consolidation, spatial navigation, and neural
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Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and
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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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mapping the critical gene and cellular networks by which the Xist lncRNA ribonucleoprotein particles (RNPs) promote autoimmune diseases (see Dou et al., Cell 2024 , for more background). This work will
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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