327 distributed-algorithms-"Prof" positions 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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Communication Lab, Prof. Jennifer Coon, jlcoon@umich.edu Background Screening The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third
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. Race and Organizations (Prof. Davon Norris) This course introduces students to the array of ways in which race and racism influence organizational structures and how organizational processes then shape
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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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University of Michigan, Dept of Statistics Position ID: UniversityofMichigan -PROF [#26790] Position Title: Position Type: Open Rank Position Location: Ann Arbor, Michigan 48109
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, assignments and other tasks. The position is limited to 30 hours total and will be under the supervision of Prof. Antonios M. Koumpias. Required Qualifications* Preference for a student majoring in Economics
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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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Apply Now Responsibilities* Conduct research focused on designing and implementing algorithms related to cryo-electron microscopy (cryo-EM) data collection in a lab that focuses on the structural
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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