Quick overview
Job description
What You Will Get To Do
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Formulate the active perception problem for inspection and a broad range of robot behaviors
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Develop viewpoint planning policies for active information gathering
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Research calibrated confidence and abstention for vision-language reasoning on the robot
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Own the research and development work through to the real-world experiments that prove feasibility and deployability
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Investigate and shape the technical roadmap, aligning real-world needs with technical development
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Mentor junior team members and collaborators
What You Have
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PhD in robotics, computer science, electrical engineering, aerospace engineering, mechanical engineering, or a related field, with publications at top venues such as RSS, CoRL, ICRA, IROS, T-FR, T-RO, CVPR, NeurIPS, or similar.
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Research experience in active perception, informative path planning, vision-language models, or semantic mapping for exploration.
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Hands-on work with vision-language or foundation models for robot perception, plus the physical principles governing them.
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Fluency in Python and the ability to run your methods on real robots with C++ and ROS 2.
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A principled fluency with uncertainty: Bayesian or information-theoretic planning, calibration, and conformal methods
What Will Set You Apart
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Real-robot experience in the wild
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Work on metric-semantic scene graphs, open-vocabulary mapping, or spatio-temporal scene representations.
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Experience fine-tuning or deploying compact VLMs on edge computers
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Exposure to robotic industrial inspection workflows
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