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Field
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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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-dimensional datasets (EHR, claims, environmental/socioeconomic data, sensor data) • Contributing to translational research that tightens the loop between engineering innovation and clinical practice
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platforms such as Cornell TEAM-Cities, CATChain, uTECH, etc. • Working with geospatial and mobility datasets (GPS trajectories, transit feeds, sensor data, demographic/socioeconomic data) • Co-designing tools
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Requisition Id 15553 Overview: We are seeking a Postdoctoral researcher in data quality assessment and control and sensor network optimization who will focus on R&D of sensor network design. This
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tackles multidisciplinary topics from signal processing to machine learning to algorithm design with a focus on sensor systems. ARL is an authorized DoD SkillBridge partner and welcomes all transitioning
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, and autonomy. You will join cross-disciplinary research teams working on prototype systems that integrate acoustic modems, sensor arrays, signal processing algorithms, and AI-enabled control
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place technologies and to develop digital twin algorithms to assist clinicians in developing treatment plans for patients with chronic diseases. Analyzes complex sensor data, works with a
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and collaborative research focused on incorporating sensing technology in the early childhood education space. “Sensing technology” refers to tools that use sensors to acquire information about human
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algorithms using Monte Carlo simulation and Bayesian inference to distinguish normal tritium losses from suspicious discrepancies during transport, and to develop statistical thresholds that balance detection
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or related fields past experience with Machine Learning algorithms and systems past experience with robot control and operation programming experience with ROS, C/C++, Python and/or PyTorch experience in