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to execute autonomous experiments, and advance laboratory autonomy and robotics. RPL develops the open-source Modular Autonomous Discovery for Science (MADSci) software framework for the orchestration
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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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to execute autonomous experiments, and advance laboratory autonomy and robotics. RPL develops the open-source Modular Autonomous Discovery for Science (MADSci) software framework for the orchestration
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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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Experimental control and orchestration frameworks such as ROS, Bluesky, or EPICS Laboratory automation and robotic synthesis platforms Generative models, reinforcement learning, or agentic AI approaches
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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