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Science and Artificial Intelligence. The lab models, simulates, and analyzes social phenomena using computational, experimental, and theoretical methods. We pursue consequential questions
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include: expertise in programming and coding (preferably using Python and C++) and GUI development; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory
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prior research and specific work, methods, datasets, systems, or research questions pursued by our lab The applicant’s personal intellectual and technical contribution to the submitted publications
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interdisciplinary-science venues. The successful candidate will be expected to formulate research questions, lead empirical projects, develop rigorous computational or experimental methods, publish in highly
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extensive experience in the application of molecular dynamics simulations to molecular systems, ideally in both methods and applications. Experience in biomolecular simulations particularly nucleic acid
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or quantitative methods. We are open to a range of methodological backgrounds, including digital trace data analysis, natural language processing, machine learning, experimental design, causal inference, and
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computational methods for the control, optimization, and coordination of complex dynamical systems. The work will emphasize applications to multi-agent systems, including robotics, autonomous systems, and
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characterization, and computational modeling. Prior experience with solid-state NMR spectroscopy, including magic-angle spinning experiments, multinuclear NMR, quadrupolar nuclei, or two-dimensional NMR methods, is
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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magic-angle spinning experiments, multinuclear NMR, quadrupolar nuclei, or two-dimensional NMR methods, is highly desirable. Experience with computational methods such as density functional theory