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) Experience working across the XR system stack, including lower-level components such as sensing, networking, systems optimization, or edge/cloud integration Experience incorporating machine learning
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and GPU-accelerated tools for circuit and system design optimization, addressing challenges in physical design, timing analysis, and large-scale hardware design automation. The researcher will
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publications. Responsibilities include: Development of new experimental approaches and implementation, optimization, and modification of existing laboratory procedures and protocols to address research
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implements multi-agent systems to optimize clinical decision support and patient monitoring. Rigorous testing of AI safety protocols ensures the reliability and ethical deployment of these autonomous models
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for their regulatory activity. However, how DELLAs achieve interaction specificity and act as transcriptional coactivators or corepressors at distinct genes remains unclear. This project uses structural, biochemical
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molecular, cellular, biochemical and immunological analyses. · Optimize and troubleshoot experimental protocols and equipment. · Design, execute and document experiments with sufficient detail to understand
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statistical modeling, including latent growth curve models, multi-group structural equation modeling, latent trajectory analyses, and hierarchical linear modeling to support project research objectives
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uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments. • Collaborate with mathematical modelers and experimentalists in
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. Maintain accurate and comprehensive laboratory records, which remain Duke property. Training & Professional Development Receive structured mentorship to help prepare for a long-term academic or research
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(qPCR, western blot, histology). • Evaluate adeno-associated viral-mediated gene therapy approaches for respiratory dysfunction. • Optimize and troubleshoot protocols, reagents, and equipment