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• Enhancing and deploying computational platforms such as Cornell TEAM-Cities, CATChain, uTECH, etc. • Working with geospatial and mobility datasets (GPS trajectories, transit feeds, sensor data, demographic
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or applying machine learning or automated detection methods. Experience working with passive acoustic monitoring data; familiarity with other sensor-based data (e.g., camera traps, remote sensing) is also
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during food processing and storage. Chemical Food Safety : Appropriate research areas may include but are not limited to: Development and utilization of rapid, inexpensive, and/or in situ sensors for real
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or applying machine learning or automated detection methods. Experience working with passive acoustic monitoring data; familiarity with other sensor-based data (e.g., camera traps, remote sensing) is also
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/socioeconomic data, sensor data) Contributing to translational research that tightens the loop between engineering innovation and clinical practice Disseminating findings through high-impact journals, conferences
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, administrators, or patients • Integrating multi-source, high-dimensional datasets (EHR, claims, environmental/socioeconomic data, sensor data) • Contributing to translational research that tightens the loop
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. Working with geospatial and mobility datasets (GPS trajectories, transit feeds, sensor data, demographic/socioeconomic data) Co-designing tools and analyses with municipal and MPO clients, including
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water pressure observations. This postdoc will work with Dr. Grace Barcheck and lead the passive seismic part of the project, including field deployment of sensors, detecting and locating icequakes
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limited to: Development and utilization of rapid, inexpensive, and/or in situ sensors for real-time detection of chemical hazards e.g., allergens, heavy metals, or mycotoxins during manufacturing and