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interest in candidates working with sensors, instrumentation, and electronic measurement systems, as well as electronic technologies for healthcare and medical applications, industrial systems, energy
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on innovation in semiconductors, biology, machine learning, and material science toward an intelligent closed-loop system of non- or minimally invasive sensors and actuators enabling personalized and periodic
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multimodal sensor data (video, LiDAR, BIM). • Assist in the deployment and acceleration of deep learning models (e.g., TensorRT, ONNX) onto edge computing devices on the robot. • Develop interactive web
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techniques including behavior cloning, reinforcement learning, and VLA reasoning Train models that are robust to real-world challenges such as sensor noise, partial observability, contact dynamics, and
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Develop principled approaches to robustness challenges such as sensor noise, partial observability, contact dynamics, and environment variability Oversee the research pipeline from data collection strategy
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ideas to understand how design shapes behaviour and experience. Students are introduced to key tools and platforms such as Arduino and sensors, TouchDesigner, and introductory Python programming
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such as stretch, durability, porosity, comfort, and transduction performance. Collaborate with electronic engineers to ensure knitted structures are compatible with sensor integration, signal acquisition
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of new sensors, platforms, and sensing paradigms to answer fundamental questions in oceanography and to advance the use of autonomous underwater vehicles. Specifically, the research will advance the use
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collaboration with the Department of Advanced Computer Science and the Sensor Engineering group, creating a highly interdisciplinary research environment at the intersection of plant science, engineering, and
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suites across the software stack Building and improving a hardware-in-the-loop (HIL) test bench for systems interfacing with sensors and spinal cord stimulators Defining and executing test strategies (unit