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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 6 hours ago
, construction, commissioning, and operations to deliver predictable, high-performing assets. Focus areas include integrated project delivery; project planning, controls, and risk management; and innovative supply
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the UW Facilities web page for more information: https://facilities.uw.edu/. Maintenance & Construction (M&C) is responsible for general maintenance, repair, and renovations of all University of Washington
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performed is approved or reviewed by the quality control technologist, chief technologist or radiologist. The Radiologic Technologist will comply and adhere to department protocols, UCDH Policies and
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; the inspection and diagnosis of information contributing to preventive and predictive maintenance scheduling; accurate collection, and the entry, and analysis of information. The position will assist the Zone
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; the inspection and diagnosis of information contributing to preventive and predictive maintenance scheduling; accurate collection, and the entry, and analysis of information. The position will assist the Zone
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works closely with the Dean to develop and coordinate the College’s annual academic and operating budget planning process, forecasts and predicts resource requirements for new and current programs and
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for clinical data Conduct statistical and machine learning analyses on large, complex healthcare datasets Clean, transform, and prepare high-quality analytic datasets for research Build and validate predictive
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the Finance & Administration group. Please visit the UW Facilities web page for more information: https://facilities.uw.edu/ . Maintenance & Construction (M&C) is responsible for general maintenance
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points. Understanding these impacts is critical for predicting landscape change and resilience. The Research Data Coordinator will work with the principle investigator Prof. Isla Myers-Smith to coordinate
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We are seeking a highly motivated doctoral student to develop ship physics-integrated machine learning models for real-time prediction and optimization of wind-assisted ship propulsion systems