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collaborative, multidisciplinary environment that brings together expertise in quantum information science, computer systems, networking, high-performance computing, and scientific applications. The scientist
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applying artificial intelligence (AI) and machine learning (ML) methods for the autonomous, self-driving synthesis of nanoscale and quantum materials. This is an exciting opportunity to help shape a new
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catalyst design. This role involves conducting multiscale modeling, spectroscopy simulations, and the development of machine learning methods and automated workflows for multi-fidelity, multiscale, and
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, postdocs, and students. May be required to perform other duties as assigned. Position Requirements Ph.D. in Physics, Accelerator Science, Electrical/Computer Engineering, or a closely related field and 4
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independently conducting machine studies to diagnose and resolve operational issues. Support APS performance improvements by conducting accelerator experiments, processing and analyzing data, and performing
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a related field completed in the past five years, or soon-to-be completed. Skill in devising and performing experiments to acquire identified data, using and maintaining research equipment, compiling
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models, reinforcement learning, and agent-based approaches to streamline experimentation and accelerate discovery Integration of HPC, data infrastructure, and ML pipelines for data-driven and autonomous