10 structural-engineering-"https:" "https:" "https:" "https:" "https:" positions at University of Texas at Arlington
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Position Information Posting Number F00700P Position Title Assistant/Associate Professor - Structures MAE Department Mech and Aero Engineering Location Arlington Job Family Faculty Position Status
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a robust research enterprise in the areas of construction engineering and management; environmental engineering; geotechnical engineering; infrastructure system engineering and management; structural
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to support research in the areas of interest, with state-of-the-art fabrication facilities at the Shimadzu Institute Nanotechnology Research Center (https://www.uta.edu/academics/schools-colleges/engineering
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demonstrated expertise in one or more areas of space propulsion; spacecraft structures; guidance, navigation, and control; space robotics; spacecraft systems engineering; and orbital assembly and manufacturing
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the areas of construction engineering and management; environmental engineering; geotechnical engineering; infrastructure system engineering and management; structural engineering and mechanics
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be found at: https://www.uta.edu/academics/schools-colleges/business College of Engineering: Areas of priority include biomedical engineering, bioinformatics, health informatics, and public health
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recognized program known for cutting-edge research and strong industry partnerships. With leading expertise across advanced construction materials, structural engineering, transportation and water resources
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students in UTA’s Center for Advanced Construction Materials. Required Qualifications Ph.D. in Civil Engineering, Materials Science and Engineering, or a closely related field, conferred by the start date
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machines, cooling towers, compressors, pumps and related equipment. Reads and records pressures, temperatures, fluid levels and other operating conditions. Maintains engineering logs and equipment status
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of results, as well as supporting new grant and contract opportunities. The focus of the research is on Multiphysics structural modeling and physics-informed machine learning (PIML) for performance prediction