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Field
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of Artificial Intelligence and Robotics at NYU Abu Dhabi the group of Prof. Kostas J. Kyriakopoulos seeks to improve the autonomy of Field Robotic systems by fusing control theoretic and machine intelligence
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well as collaborate with PhD candidates. You'll design experiments using our robotic platform, analyze tactile data patterns, implement real-time control algorithms, and validate performance across diverse scenarios
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areas like healthcare, education, neuro-robotics, and/or assistive technologies. Prior experience in physiological signal processing (e.g., EMG, EEG, ECG) is an advantage. Familiarity with HCI principles
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, sustainable agriculture, climate change, clean energy, and robotics in an era of artificial intelligence. EIT blends groundbreaking research with practical applications to deliver lasting results. A cornerstone
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with robotics researchers and interdisciplinary team members Maintain detailed experimental records and ensure reproducible research practices Required Qualifications A PhD degree in Neuroscience
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to other organoid and tissue models Your Profile: PhD in electrical engineering, automation, robotics, computer science, or a related field, with evidence of innovative and impactful research Demonstrated
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blend theoretical approaches with hands-on experimentation, as well as collaborate with PhD candidates. You'll design experiments using our robotic platform, analyze tactile data patterns, implement real
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, operating systems and security. Job Description The successful candidate will investigate robot learning methods for control and decision-making on edge robotic platforms. Research will focus on reinforcement
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science. The research of the focuses on soft matter (colloids, polymers, liquid crystals, granular matter, thin sheets...), active matter (self-propelled colloids, swimming droplets, walking grains, swarms of robots
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candidate will investigate robot learning methods for control and decision-making on edge robotic platforms. Research will focus on reinforcement learning, imitation learning, and the integration of large