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manufacturing tools. Given the massive production scale, the AMHS must handle tens of thousands of transports requests every day, ensuring timely and reliable delivery of wafers to the correct tools. Our research
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 28 days ago
plasma physics, MHD stability, or fusion energy research; familiarity with large-scale data management, curation, FAIR data principles, and machine learning; experience conducting original scientific
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construction activities that are associated with the disciplined allocation of capital to large-scale infrastructure projects by corporations. The analysis is expected to identify key development
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University of California, Los Angeles | Los Angeles, California | United States | about 24 hours ago
-personnel-programs/_files/2025-26/represented-oct-2025-scales/t23.pdf ]. A reasonable estimate for this position is $69,073-$82,836 Application Window Open date: October 23, 2025 Next review date: Friday, Dec
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thereafter) for a period of two years. Lithium-ion batteries are a cornerstone of the green transition, powering technologies from electric vehicles to large-scale energy storage. However, charging processes
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functional theory (DFT)-based approaches, coupled with effective continuum and/or tight-binding models derived from first-principles calculations. The project is part of a large, multi-institution
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; experience with plasma physics, MHD stability, or fusion energy research; familiarity with large-scale data management, curation, FAIR data principles, and machine learning; experience conducting original
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these forwards in a rigorous, efficient and timely manner. This involves small scale project management, to co-ordinate multiple aspects of work to meet deadlines. You will be responsible for adapting existing and
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models. Experience in large-scale deep learning systems and/or large foundation model, and the ability to train models using GPU/TPU parallelization. Experience in multi-modality data analysis (e.g., image
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for conducting large-scale experiments. Knowledge of emerging AI security threats including prompt injection, jailbreaking, model inversion, membership inference, and poisoning attacks against foundation models