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learning, Computer vision, and Autonomous Robots is desired. The successful applicant will work on various projects on robotics and computer vision, controls, and machine learning and their security
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for building energy-efficient and robust brain-inspired, autonomous, and cognitive systems and intelligent vision systems, including efficient learning and inference of complex AI/ML algorithms, specialized
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custom experimental systems. These instruments may combine optical components, laser and spectroscopic methods, spin-control or magnetic-resonance techniques, electronics, data-acquisition hardware, and
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and developing a machine perfusion system to improve organ preservation. The candidate will work in a dynamic, multidisciplinary environment alongside PhD-level engineers and scientists, graduate
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. Kyriakopoulos seeks to improve the autonomy of Field Robotic systems by fusing control theoretic and machine intelligence approaches. Formal models are directly applied in real experimental facilities. Marine
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and intelligent vision systems, including efficient learning and inference of complex AI/ML algorithms, specialized neural processing hardware and design tools, and ML security, and their applications