316 postdoc-distributed-algorithms uni jobs at University of Michigan in United States
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Distribution department Provides direct supervision of staff including interviewing, hiring, scheduling, training, orientation, evaluation, adherence to mandatory training requirements, delivery schedules
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Apply Now Job Summary The Student Research Assistant will support a faculty-led research project examining how algorithmic bias affects social equity in areas such as healthcare, hiring, and
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algorithms, data sources and reporting processes. Conceptualize and develop cross-functional client/unit strategic objectives, business processes, and initiatives that drive or increase organizational value
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are senior undergraduate, graduate, or postdoc students, including those interested in gaining experience in AI and cybersecurity. Responsibilities* Design and implement machine learning techniques for web
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(e.g. transcriptomics, metabolomics) Knowledge of machine learning/deep learning algorithms Knowledge of systems biology approaches (e.g. genome-scale modeling) Proficient with R, Python or MATLAB Modes
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or improvement. The intern will analyze the performance of AI models by comparing model predictions against established benchmarks. They will contribute insights on how to optimize algorithms and improve
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, objectives, and operating cadence of committees. This will also include setting up technology for hybrid meetings, preparing and distributing meeting agendas, organizing materials for distribution at meetings
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chiller plants including: control systems; pump distribution; chillers; cooling towers; condenser water systems; water treatment; refrigerant flow devices; control systems; fan systems, and terminal
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and intermediate level, with a focus on programming control, perception, planning, and algorithmic functions for robots. Topics will include data representation, memory concepts, debugging, recursion
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. Learn, utilize, and maintain Charge Master data in FinThrive and in the Epic EAP master file. Set hospital rates following department policy, using standardized pricing algorithms, available benchmarking