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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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high-resolution, quantitative time-lapse soil property measurements using high-performance, parallel computing. Together with our existing rich dataset, we will inform a soil-plant digital twin, enabling
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training