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Requisition Id 11879 Overview: ORNL is searching for a group leader to lead the newly formed Spatial Statistics group. This group focuses on developing and applying advanced statistical and
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mechanical systems and controls is desirable. Possess the capability to perform techno-economic analysis, interpret data, conduct statistical analysis of datasets, visualize spatial data, deliver presentations
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Qualifications: PhD in physics, nuclear engineering, mathematics, statistics, or a related field with a minimum of 2 years of research or laboratory experience Demonstrated capabilities and experience in data
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researching or using hydrological and nutrient transport processes, statistical methods in hydrology/environmental sciences, basin scale modelling experience using process-based hydrologic models Experience
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wide range of fields that include expertise in data science, statistics, nuclear engineering, and scientific computing to deliver high impact nonproliferation research, release relevant open source
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: Familiarity with numerical calculations and statistical data analysis Ability to work creatively and cooperatively as a member of an interdisciplinary research team Strong interpersonal and communication skills
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. Analysts then break down the problem into its various parts using statistical and database software and analytical techniques, such as forecasting, data mining, regression analysis, apparent and root cause
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savings performance contracts, heating and cooling technologies, and mechanical systems and controls is desired. Familiarity with numerical calculation and statistical data analysis techniques is desired
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, statistical, probabilistic, or algorithmic solutions to address real world problems in the healthcare and biomedical research using DOE leadership computing resources. Major Duties and Responsibilities: As a
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to the built environment and human activity spaces. Major Duties/Responsibilities: Develop new and existing population and geodemographic models through statistical or computational methods for improvements