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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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in the cleanroom at the Center for Nanoscale Materials. The candidate will work in a collaborative environment including a network of leading researchers. Position Requirements Recent or soon-to-be
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Laboratory’s Biosciences Division, allowing for seamless computational and experimental research integration Position Requirements A recent or soon to be completed PhD within the last 0-5 years Computational
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to assess evolving risks in coastal-urban regions. Other key responsibilities include: Mesh design and high-resolution data utilization. Develop and refine high-resolution barotropic ocean meshes along U.S
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, including communication, networking, and leadership. Position Requirements To perform the essential functions of this position successful applicants must provide proof of U.S. citizenship, which is required
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, networking, and leadership. Position Requirements This level of knowledge is typically achieved through a formal education in economics, operations research, public policy, environmental science, engineering