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optimization under uncertainty, constrained query evaluation, or the design of efficient, explainable, and scalable query engines. The successful applicant will help design and build novel systems and algorithms
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in hand by the time of the appointment. Strong background in distributed control, optimization, or multi-agent systems. Proven track record of high-quality publications. Proficiency in programming (e.g
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related field in hand by the time of the appointment. Strong background in distributed control, optimization, or multi-agent systems. Proven track record of high-quality publications. Proficiency in
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. They come in various configurations, from simple, conceptual lumped models to more complex, distributed ones. Their low input data requirements and flexible application make them widely used by water managers
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Navier-Stokes equations at a macroscopic level, the LB method considers the fluid at a kinetic level. Capturing the dynamics of collections of fluid particles distributed over a lattice is here preferred
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development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section
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the U.S. achieve energy goals. ESIA develops, deploy, and advances grid technologies that ensures a robust and secure U.S. grid transmission and distribution system. ESIA also collaborates with government
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researcher in algorithmic game theory and/or online learning, working with Prof. Celli at BIDSA and the Department of Computing Sciences. The project studies how multiple machine learning algorithms interact
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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for the concept of optimal transport for inverse problems. Optimal transport is concerned with the mathematical problem of comparing and interpolating distributions of mass, for example probability distributions