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for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section
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system integration, as well as embedded controller development. Experience in modeling converter topologies and distribution grids, developing control algorithms, and implementing controller code is
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prediction and assessment. Design algorithms integrating geophysical principles with explainable and interpretable AI techniques to enhance model interpretability and uncertainty quantification. Contribute
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and automated fault detection and diagnosis (AFDD) algorithms to buildings Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork
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. Eventually, we aim to map these algorithms on to energy-efficient emerging devices. In addition, you may also explore applying LLMs to drive multimodal models in scientific domains towards deep reasoning. As a
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on circular economy research Experience in working in the genetic algorithm and artificial neural networks is preferred. Experience in manufacturing process modeling of advanced manufacturing technologies
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Research. We are seeking applications from researchers in the broad domain of computational and applied mathematics, including algorithm analysis, artificial intelligence, combinatorial scientific computing
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geometries and advancing to multimodal damage assessment capabilities. The group conducts cutting edge research and publishes on novel ML breakthrough algorithms for large scale geospatial application
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uniting national laboratories, academic institutions and industry partners, the QSC is endeavoring to advance American innovation and global leadership by enhancing the computational robustness, algorithmic
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timing distribution. Experience with PCB schematic capture & layout tools such as Cadence, Mentor Graphics, Altium, or KiCAD. Experience implementing DSP algorithms on FPGAs. Experience with Vivado High