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detection algorithms for cracks, chokage, deformation, corrosion, etc. Establish datasets, annotation standards, training pipelines, and benchmarking protocols for ML models. Integrate uncertainty estimation
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projects, as well as in multiagent systems, including computational game theory, security games, machine learning in multiagent settings, automated planning under uncertainty, social networks and others
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. Managing uncertainties associated with emerging low-carbon materials, including variability in by-product sources (e.g., steel slag), performance consistency, and acceptance by industry stakeholders. Job
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | 3 days ago
data, bias analysis and minimization, performance metrics and uncertainty quantification, evaluation of continuously learning algorithms, and post-market monitoring. Learning Objectives: Under
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estimation with quantified uncertainties. The central aim is to increase the efficiency and accuracy of near-field prediction of physical and biological conditions for marine operations including marine carbon
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. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations of reactor transients and quantify how surrogate uncertainties propagate
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. Long-horizon and safety-aware planning under uncertainty. Function 2 2. Learning-Based Perception and Control Multi-modal and foundation-model-based approaches for robotics, including: Multi-modal
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Applications for a research fellow position are invited to advance research on emerging problems in the advances of sequential making under uncertainty. The candidate will conduct research under
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for optimization, history matching, decision making, uncertainty quantification, etc Conduct geothermal assessments, as this is a hot field (> 150 C) The candidate can also suggest other objectives / research
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Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks (ICLR’20), Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach, Code: https