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Theoretical Quantum Many-body Physics and Quantum Sensing at Indiana University Bloomington Fields: Quantum many-body theory, AMO–condensed matter interfaces, advanced numerical simulations, quantum sensing
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policy. Dr. Kang’s research laboratory is focused in personalized testing pathways, translation of diagnostic innovations, and cancer screening. We develop predictive models, simulation frameworks, and AI
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling Large-scale computing, cloud-native analytics workflows, and data engineering for mobility platforms AI/ML
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 days ago
assimilation Integration (JEDI) framework for atmospheric data assimilation Develop machine learning foundation models based on simulated observations from high fidelity atmospheric simulations for developing
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-physics TCAD simulations aimed at efficiently modeling charge transport, Joule heating mechanical deformations and ion migration in electronic devices such as MOS transistors and NAND memories
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–water coupling. What you’ll do – Modeling Simulations You will design and run high resolution simulations that bring the lake to life in the model world. Starting with large eddy simulation hindcasts
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Postdoctoral Fellow Position in Quantum Optical Physics: Theoretical, Simulation, Modeling for Experimental Design Title: Postdoctoral Fellow, physics Appointment Status: Non-tenure track Department: Department
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methods for multiphase flow models Integrate experimental, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase
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Simulations (INMA, Zaragoza) Build and maintain software infrastructure for modeling quantum systems with machine learning tools. Investigate neural-network-based representations of many-body quantum states