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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
with potentiometric sensors, amperometric enzyme-based sensors, chronoamperometric assay development, reference electrode integration, and sensor calibration in biological or complex media is highly
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systems, predictive modeling, or optimization problems related to packaging or mechanical systems. • Background in logistics optimization, supply chain modeling, or distribution network analysis
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this project we are rethinking the structures, actuators, sensors, and control systems used in morphing winged UAVs. We focus on embodying mechanical intelligence in structures through experiments ranging from
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-resolved cryo-EM. Together, these approaches are establishing a new framework for dynamic structural biophysics. Current Research Our current biological focus is thermoTRP ion channels – molecular sensors
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, audio, pose, sensor, or behavioral data. Experience developing machine learning models for human behavior analysis. Interest in autism research, developmental science, digital health, or behavioral
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of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and six centers and institutes that focus
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fixtures, pressure chambers, tool housings, and other mechanical components. Install and integrate sensors, instrumentation, data-acquisition, and experimental control components. Contribute to technical
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studies in the area of machine learning for wireless communications. Develop and implement machine learning techniques for communication systems, with a strong emphasis on producing high-quality research
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to understand how design and planning decisions affect health and wellbeing. Key Responsibilities are to design and test a measurement protocol combining wearable sensors, environmental data, and imagery-based
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include, but are not limited to: Responsibilities Design, build, and integrate robotic and automated systems, including end-effectors, manipulators, and sensor-actuator networks. Lead mechanical, electrical