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transfer. Preferred Qualifications: Experience with building energy modeling and simulation tools such as EnergyPlus, or similar platforms for energy simulation and analysis, including model development
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manufacturing datasets, including sensor streams, in-process signals, post-process characterization data, simulation outputs, and digital twin data. Develop, integrate, and evaluate AI/ML models for anomaly
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techniques capable of maintaining relationships between data and metadata. Collaborate on innovative solutions to automate and optimize the interplay between large scientific simulations, data ingestion, and
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: Familiarity with architectural simulators (e.g., Gem5, SST) or HDLs. Quantum / Analog Computing: Exposure to quantum programming models (e.g., QIR, Q#, Qiskit, Cirq) or analog/neuromorphic systems; interest in
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analysis by integrating diverse datasets (e.g., in situ observations, remote sensing products, model simulations) to inform model development, calibration, and validation. Collaborate with a
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, LeafWeb, Sapfluxnet, PSInet) to translate trait variation into model parameter priors and functional constraints, and to explore parameter relationships with environmental conditions Hybrid modeling
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program: Contribute to the LEGEND-200 data analysis and the development of advanced analysis routines Contribute to the R&D on advanced instrumentation, design, and simulations of the next generation LEGEND
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in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
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performance tools Study the performance, resiliency, power, and efficiency of modern and future high-performance computing systems under various workload characteristics through measurement, modeling, and