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. Responsibilities* Design, implement, and evaluate LiDAR-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using LiDAR sensors. Help
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Description CEE575: Sensors & Data This course addresses the emergence of sensors and ?smart? systems. We will learn how sensors, internet-connected devices and real-time data are being used to build ?smart
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with specialized expertise in sensor interfacing and Data Engineering to join our technical team. This role combines traditional system administration responsibilities with hands-on work in sensor
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- Reinforcement Learning Algorithms COURSE SCHEDULE: April 1, 2026 - April 28, 2026 Number of available GSI positions: 1 position at .25 fraction, pending enrollment Number of positions reserved for PhD Students as
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interests, including both scientific topics and algorithm/software development; Potential synergies with ongoing research at the University of Michigan with at least 2 professors on campus applying
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with partners to secure external funding and translate prototypes into reliable tools for clinical and public-health impact. Projects use multimodal data sources (including EHR, imaging, textual, sensor
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sources including electronic health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians
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actively seeking enthusiastic and innovative early-career researchers to join our Algorithm Core team. The successful candidate will engage in cutting-edge research in applied mathematics, focusing
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algorithms, and in collaboration with PFCs as needed. Prioritize patient placement from multiple in-coming locations, i.e., home, clinic, outside hospital transfers, PACU, and emergency departments from all
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) that will make use of various machine learning algorithms for attack vectors and vulnerabilities, such as intrusion detection, malware analysis, spam filters, anomaly detection, etc. Supervised, unsupervised