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terms of universal computational skills. We encourage you to describe your work using broader technical terms—such as "statistical data analysis," "workflow automation," or "algorithm optimization"—rather
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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artifacts, and developing an independent research agenda in AI for science. Core responsibilities include: Leading research on foundation models, including problem formulation, algorithmic development, and
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High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms
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electron beams, advanced beam-manipulation for precise electron-beam shaping, and ML for accelerator science. Responsibilities Develop and deploy ML algorithms for autonomous operations and optimization
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technologies, control algorithms and powertrain architectures with focus on advanced technologies. The candidate will assist on projects to benchmark next generation vehicle systems, identify opportunities
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beyond traditional error estimators, creating physics-based adaptation algorithms that intelligently predict where refinement will be most beneficial for smarter, more efficient simulations. We seek
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detectors while also having flexibility to pursue your own research interests. Research Focus Participate in a detector R&D program aimed at developing superconducting nanowire sensors to enable