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acquisition, instrument control, and data analysis in Python or similar languages Knowledge of quantum optics measurements such as photon correlation functions or photon-number-resolved detection Familiarity
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workflows, and immersive or experimental interfaces Integrate LLM-based and agentic AI systems with scientific visualization frameworks, in situ pipelines, and data analysis workflows Prototype and evaluate
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: Proficiency in machine learning, statistical modeling, and quantitative methods for multi-omics data analysis Molecular Simulations: Expertise with molecular simulation tools like OpenMM, AMBER, Gromacs, and
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will receive full consideration. Key Responsibilities AI-ready data and analysis for the ePIC Barrel Imaging Calorimeter and our Jefferson Lab program Support for the PRad-II and X17 experiments
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-completed PhD with strong background in Materials Science or Physics (within the last 5 years) Considerable experience in understanding magnetic-domain physics in thin film and/or nanostructured materials