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participation, and dissemination of research results. Adhere to requirements for protecting proprietary or sensitive information and follow ORNL cybersecurity policies and guidelines. Basic Qualifications: Ph.D
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. Excellent analytical skills with high attention to detail. Experience with geospatial data visualization tools such as ArcGIS, Cesium, or similar. Familiarity with urban-scale building energy modeling
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for Computational Sciences. They will collaborate with leading computer and computational scientists at ORNL and external collaborators in the development and application of new computational techniques specifically
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analysis and technoeconomic analysis without significant direction from ORNL staff Leverage primary equipment data from both within ORNL and from industrial partners from across the U.S. to quantify costs
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/Responsibilities: Design and implement a modular ROS 2 software architecture for onboard sensing, autonomy, mapping, data logging, launch management, and configuration management. Develop and integrate ROS 2 drivers
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Compartmented Information (SCI) clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement
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chemistry, specifically x-ray photoelectron spectroscopy. Electrochemistry background, specifically time-resolved impedance. Candidates must show proficiency in developing techniques and data. An excellent
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data analytics, and manufacturing process optimization. Develop and apply models, algorithms, or data analysis workflows to support machining process understanding, machine tool characterization, process
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characterization using advanced analytical tools, such as synchrotron, neutron, and laboratory equipment. Experience in data analytics and modeling tools. Special Requirements: Applicants cannot have received
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responses to current or imposed environmental conditions. Research may leverage: Laboratory, growth chamber and field experimental data, and/or new measurements to quantify molecular to ecosystem scale