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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 16 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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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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, qualifications, experience, education, licenses, specialty, training and internal pay comparison. The above hiring range represents the University's good faith and reasonable estimate of the range of possible
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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 16 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
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focuses on hybrid traffic flow modelling such as Physics inspired Neural Nets (PiNNs) or “ML inspired” traffic models. PhD2 focuses on data assimilation and estimating start and boundary conditions such as
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) for dynamic 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