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Field
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infrastructure monitoring, as well as connected autonomous vehicles Integrating multi-modal sensor data with physics-based models Developing robust and adaptive methods for real-time parameter and state estimation
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of this collaborative project of the university hospital Zurich, ETH Zurich, and the university of Groningen is to facilitate personalization of OSA therapy by introducing unobtrusive sensors (microphones
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and sensors. This is a part-time position, working 19.5 hours per week. What you need to know Schedule: May have to work on the weekend and/or after normal hours. This is a part-time position, working
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required. Qualifications Required Education and Experience: Appropriate PhD in neuroscience, neurophysiology, or a related field. Preferred Qualifications: Expertise in software /data analysis such as
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of agricultural water use. Specific focus areas include applying AI/ML to analyze remote sensing and sensor data for predicting crop water requirements, advancing irrigation scheduling, and supporting real-time
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position is embedded in a vibrant research environment that includes several PhD students and postdoctoral researchers. The project is a close collaboration between the Computer Vision Group at Chalmers
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neurological function, including in rugby and snow sports. You should hold or be near completion of a PhD/DPhil in Biomedical, Electrical or Information Engineering or other relevant disciplines, and possess
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will deploy moored sensors (e.g. acoustic Doppler current profilers - ADCPs) in a series of submarine canyons in the Gulf of Mexico and along the US East Coast. Time-lapse bathymetric surveys and
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sensor data, public databases, and GIS. Predictive Modeling:Design predictive models to evaluate the impact of urban and environmental policies on public health. Interdisciplinary Collaboration:Collaborate
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needs. Tasks may involve CAD design, machining, and integration of sensors and control systems. Collaboration and Mentorship 5% Work collaboratively with faculty, graduate students, and other postdoctoral