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, Robotics, Computer Science, Statistics, or related discipline. Strong background in Machine Learning and Control Theory. Demonstrated experience in research projects with industrial partners. Excellent
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) Developing machine-learning based exoskeleton controllers to work across tasks 2) Designing and validating new robotic lower-limb prostheses 3) Exploring other high-risk high-reward research areas related
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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students driving innovation across marine, energy, robotics, and materials engineering. With world-class facilities and strong industrial partnerships, we tackle real-world challenges through high-impact
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the intersection of control theory, robotics, artificial intelligence, and signal processing, and is a key enabler of future intelligent infrastructure.This project will focus on the development of novel control
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, at the University of Cambridge, UK. The Postdoc will work together with a team of students and research collaborators on the development of learning-based discovery of robot task/environment designs