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systems with unknown but measurable performance functions. Experience in system identification and online time-varying parameter estimation algorithms. Programming skills in MATLAB/Simulink, C/C++ and
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. Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other related definitions. Knowledge of federated learning SOTA algorithms. Knowledge of distributed
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Calibration, Validation, and Uncertainty Quantification: The Postdoctoral Associate will develop and implement approaches for parameter estimation, calibration, validation, sensitivity analysis, and uncertainty
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or ready to stay in Belgium during the research The following expertise is considered an advantage but is not mandatory: Experience with kinetic modelling, reaction network development, parameter estimation
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 2 months ago
application to gas hydrate system to develop efficient key parameter estimation tools and large-scale 3D geologic model for gas hydrate reservoir. Learning opportunities will be given on the area of laboratory
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 12 hours ago
migration in porous media under in situ conditions, and • Machine learning application to gas hydrate system to develop efficient key parameter estimation tools and large-scale 3D geologic model for gas
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Electrical & Computer Engineering Work Location EPIC and Grigg Vacancy Open To All Candidates Position Designation Post Doc Employment Type Temporary - Full-time Hours per week 40 Work Schedule Pay Rate
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 12 hours ago
, increased storage) Apply geostatistical methods (e.g., kriging) to characterize the spatial heterogeneity of key reservoir parameters (e.g., porosity, permeability) and quantify subsurface uncertainty through
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Neural Nets (PiNNs) or “ML inspired” traffic models. PhD2 focuses on data assimilation and estimating start and boundary conditions such as path-flows, and other key parameters and inputs. In your role as
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availability, for instance due to load balancing requirements. Model parameters will be continuously updated using measured and estimated data from the physical pilot plant, providing a foundation for