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This is an opportunity for a knowledgeable and creative individual to be part of a team developing advanced humanoid and dexterous robotic capabilities for scientific use-cases. Recent progress has
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or robotic systems Knowledge of system integration, instrument control, workflow automation, and data acquisition Experience developing and applying AI/ML methods, including predictive modeling, active
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crystal growth and structure–property relationship discovery. The successful candidate will join a highly collaborative research environment that integrates robotic experimentation, advanced
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for experiments, or uncertainty quantification Experience with autonomous, self-driving, or robotic laboratory platforms Background in electronic polymers, conjugated polymers, organic semiconductors, soft
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at the University of Chicago, automating screening protocols in partnership with Argonne National Laboratory Drive research at the intersection of automation, robotics, generative AI, and computational simulations