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-efficiency to realized efficient Embodied/Edge-AI implementations. A key focus will be on investigating novel methods with strong theoretical foundations as well as their full-system deployment in real-world
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methods, provides the ideal environment for research on programming with formal guarantees — a topic of increasing practical importance. About us The Department of Computer Science and Engineering , a joint
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, uncertainty-aware parameter estimation, surrogate modeling, and reduced-order modeling where relevant. The scientific emphasis is mechanics-first: we are looking for someone with strong foundations in nonlinear
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 17 hours ago
infrastructure such wells and reservoirs. The selected participant will conduct research in close conjunction with NETL federal and contract staff to: (1) test and validate open-source methods for extracting
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, transitions of control, driver awareness, and the communication of system capabilities and limitations. The project brings together expertise from human-computer interaction, AI, human factors, cognitive
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, and research method innovation. The collaborative expertise of the postdoctoral associate cohort, using both qualitative and quantitative methods, will contribute to, for example, foundational research
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studies using qualitative, quantitative, and mixed-methods approaches, including surveys, interviews, observations, social network analysis, and analysis of digital trace data. Collaborating with industry
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 17 hours ago
to identify strategies for maximizing desired subsurface outcomes (e.g., recovery efficiency, increased storage) Apply geostatistical methods (e.g., kriging) to characterize the spatial heterogeneity of key
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. You will design and optimize resilience mechanisms that estimate disruption risk and proactively reconfigure the transport network to enable autonomous recovery, self-healing, and graceful degradation
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. You will design and optimize resilience mechanisms that estimate disruption risk and proactively reconfigure the transport network to enable autonomous recovery, self-healing, and graceful degradation