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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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, repair and maintain other field devices including sensors, airflow stations, water flow stations, freezestats, and other field devices to make a complete control system. Inspect, test and analyze
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-Directed Medical Therapy following a centralized algorithm and under the direct supervision of a site nephrology principal investigator. Required Qualifications* A Bachelor's degree in Pharmacy is necessary
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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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- 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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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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) 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
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, file system implementations, I/O, deadlocks, distributed systems, synchronization, distributed file systems, case studies. Graded ABCDE CSC 575 - Algorithm and Complexity Analysis Graduate standing. (4
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Experience with NGS analysis pipelines, algorithms, and workflows, including bulk DNA/RNA-Seq and single-cell analysis Exposure to clinical data standards (HL7, FHIR, OMOP, DICOM) and experience working with