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Field
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advanced control strategies (e.g., model predictive control, adaptive control, feedback/feedforward control, ML-based controls) for thermal system optimization Integrate real-time sensor data and telemetry
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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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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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) and contribute to LU-PCG’s research under the U.S. Department of Energy’s (DOE) GENESIS Mission. Research will involve developing fast neural surrogate models, state estimators/virtual sensors, multi
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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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and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core Responsibilities: Understanding
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the holistic understanding of space and its broader societal, ethical, and environmental impacts. Through responsible, multi-disciplinary research, including novel sensors, environment modelling
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hardware development using sensors and microcontroller systems is an advantage. Strong scientific skills and experience in real life experiments, as well as effective communication skills, written and orally