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optimization models for electric vehicle fleet charging planning. Activities: • Apply operations research methods (linear and mixed-integer programming, dynamic optimization, stochastic optimization) • Integrate
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groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative projects with other group members and our
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theoretically, in tight collaboration with experimental groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative
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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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, with a background in information theory and stochastic physics applied to biological data. Further requirements include past experience with: Teaching and advising undergraduates. Experimental
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and Gaussian state formalism. Quantum information theory and entanglement theory. Theory of spin-mechanical systems. Open quantum systems, continuous quantum measurement and feedback, and stochastic
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 4 hours ago
stochastic methods. Build 3D geologic and petrophysical models of oil and gas reservoirs using well logs, core, seismic, and completion data. Integrate machine-learning and data-driven techniques for reservoir
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. Methodological Areas of Interest Applicants with experience in the following areas are especially encouraged to apply: Optimization (deterministic, stochastic, robust, reinforcement learning–based) Systems