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). The successful candidate will contribute to the modeling, simulation, and co-design of next-generation Quantum-HPC (QHPC) architectures, with particular emphasis on integration of quantum and HPC distributed
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Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system
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AI/ML surrogate models for inverse design of new materials and processes, incorporating simulated and experimental multi-modal datasets. Develop AI/ML approaches to bridge length- and time-scales in
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Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system
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, including some or all the following: steady-state and depletion core analysis, fuel cycle analysis and evaluations, research reactor design and analysis, characterization of isotopic content of nuclear
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frameworks, sampler configuration and performance, convergence diagnostics, and posterior predictive checking. Contribute to the design, implementation, testing, and documentation of open-source scientific
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to design and implement experiments, perform data analyses, and interpret experimental results. Excellent interpersonal, oral, and written communication skills. Preferred Qualifications: Demonstrated
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-assisted model calibration, or pattern detection in large observational datasets) to improve nutrient-cycling representation and reduce predictive uncertainty in models. Collaborate with an interdisciplinary
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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral
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separation and recovery methods for Gallium and Germanium. Major Duties/Responsibilities: Design and synthesize organic ligands, functionalization of resins, polymers. Design and execute adsorption based solid