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research in radiochemical separations and advanced aqueous recycling of used nuclear fuel (UNF). The successful candidate will contribute to the development and optimization of advanced aqueous recycling
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at the nexus of AI, operations research and decision making and their applications to workforce policy and reskilling. The project builds on ongoing work using optimization-based models to predict
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, and related fields. Preferred Qualifications: Experience in optimization methods and/or efficiency analysis (DEA, stochastic frontier, dynamic optimization). Experience with production function
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, and related fields. Preferred Qualifications: Experience in optimization methods and/or efficiency analysis (DEA, stochastic frontier, dynamic optimization). Experience with production function
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design knowledge in the development and optimization of quantum technology and quantum photonics systems. Job Requirements: PhD in Electrical Engineering or Quantum Engineering. Familiarity with quantum
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design knowledge in the development and optimization of quantum technology and quantum photonics systems. Job Requirements: PhD in Electrical Engineering or Quantum Engineering. Familiarity with quantum
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design knowledge in the development and optimization of quantum technology and quantum photonics systems. Job Requirements: PhD in Electrical Engineering or Quantum Engineering. Familiarity with quantum
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modeling, and process optimization. In this role, you will leverage large-scale, heterogeneous datasets to develop and deploy AI-driven methods for: Real-time quality monitoring and control of
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emphasis on the Membrane-Based Processes. The successful candidate will contribute to the development, optimization, and scale-up of advanced pretreatment solutions for seawater desalination. The
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examination and optimization of alternative functionalization pathways for monolayer formation and thorough characterization of the resulting monolayer. More advanced applications include formation and