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, developing groundbreaking algorithms and systems that mimic natural processes to elevate the capabilities of robotic systems. In this role, you will engage in transformative projects that utilize bio-inspired
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efficient algorithms with provable statistical guarantees, using tools from: high-dimensional statistics, optimization, probability theory, etc. These positions would be especially relevant for those with a
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Fellow in Autonomous Systems and Control to design and implement efficient, performance‑guaranteed distributed control approaches, leveraging cutting‑edge learning algorithms and AI strategies
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. The position will focus on developing and optimizing control algorithms for exoskeleton robotic systems, aimed at improving human mobility and assisting individuals for lifestyle physical activities. The ideal
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work on a project to conduct research for human robotic teaming, in particular: Perform optimization on complex system subject to various constraints. Design and develop real-time algorithms. Simulate
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, or a related field of thermal nanophotonics. Excellent publication records will be preferred. Experience in matlab, MEEP, RCWA and other softwares and algorithms. Excellent publication track records
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, quantum machine learning, quantum algorithms from well-established universities/institutes. The candidates must be highly motivated in multidisciplinary research. He/she must have proven experience in
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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Digital Twin for electric vehicle applications . The role will focus on utilizing novel machine learning models, large language models, and data science algorithms to develop battery models, optimization