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of architectures for robust and scalable quantum information processing. These projects will involve a combination of analytical and numerical approaches and will connect closely with ongoing
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maintains a robust and expanding research portfolio, currently spanning nine sponsored projects, with additional proposals in progress. The lab uniquely integrates wet lab and computational expertise and is a
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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
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encouraged to apply: • Optimization (deterministic, stochastic, robust, reinforcement learning–based) • Systems architecture and design for complex socio-technical systems • Graph theory, network science, and
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modelling tools are required. Robust modelling and programming abilities (e.g., Python) are essential prerequisites. Experience with VIC (or similar hydrologic models), GIS, and large-scale computing