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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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, the project relies on a multidisciplinary methodology, gathering knowledge in human perception, haptics, virtual reality mechanics and 3D interactions. PHD Topic Within the context of ADVHANDTURE, the goal
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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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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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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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, 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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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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approaches to improving health system productivity Forecasting the impact of AI, robotics, and demographic trends on GDP, employment, and public finances Skills Required PhD (or expected 2026) in Economics or
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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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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