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bargaining agreements (when applicable). If employed by the University of California, you will be required to comply with our Policy on Vaccination Programs, which may be amended or revised from time to time
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the University anticipates to pay for this position, based on internal equity, budget, and collective bargaining agreements (when applicable). If employed by the University of California, you will be required
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, qualifications, and experience. Dr. Sebastian Calonico in the Graduate School of Management at the University of California, Davis, wishes to employ a 100%-time Postdoc who will contribute to several projects
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). If employed by the University of California, you will be required to comply with our Policy on Vaccination Programs, which may be amended or revised from time to time. Federal, state, or local public health
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the University anticipates to pay for this position, based on internal equity, budget, and collective bargaining agreements (when applicable). If employed by the University of California, you will be required
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). If employed by the University of California, you will be required to comply with our Policy on Vaccination Programs, which may be amended or revised from time to time. Federal, state, or local public health
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Analysis and apply today! This work will advance novel research focused on sensor-based in-situ process monitoring, data correlation to end part quality, data driven machine parameterization, and data
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agreements (when applicable). If employed by the University of California, you will be required to comply with our Policy on Vaccination Programs, which may be amended or revised from time to time. Federal
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for motion control, and monitoring sensors. Job Requirements BS in Electrical and Electronic Engineering, Mechanical Engineering, computer engineering, or related field 4-year research experience in related
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 3 months ago
. Duties/Responsibilities Analysis (50%) Develop machine learning algorithms to analyze ground magnetic field perturbations Analyze the results using machine learning interpretability techniques