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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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., GSAS, GSAS-II, VDRIVE). Experience in alloy fabrication and processing (e.g., arc melting, thermomechanical processing, additive manufacturing). Knowledge of deformation mechanisms such as dislocation
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, including design of experiments and the use of mechanical systems and instrumentation. Knowledge in thermodynamics, fluid dynamics, and heat and mass transfer, with experience in heating, ventilation, and air
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Qualifications: Extensive experience with twisted materials fabrication and characterization. Knowledge of correlated-electron physics. Experience with spin-polarized scanning tunneling microscopy and quantum
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
. Major Duties/Responsibilities: Develop and validate AI/ML models that can be used for knowledge extraction (e.g. discovery of governing equations; correlative analysis across length/time-scales etc.) from