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(DOE), the Department of Transportation (DOT), and other federal agencies in developing solutions to national transportation problems. TADS researchers conduct spatial and statistical analyses, build
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– in how we treat one another, work together, and measure success. Job Requirements: BS/BA degree in Human Resources, Statistics, Data Science, Information Technology, or related field. A minimum of five
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well as the ability to foster positive customer relations, are essential Experience with the following systems is a plus: Vehicle Costing System (VCS), GSA Drive-thru, and Federal Automotive Statistical Tool (FAST
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Qualifications: Exceptional teamwork, statistical skills, and a positive, meticulous nature with a penchant for detail and precision are required attributes. Experience in leading developing, revising and
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the following preferred qualifications, though none are required: Extensive experience and fluency in Python and R computer languages. Background in statistics and data analytics. Previous experience in
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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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: 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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: 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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research emphasizes models for the distribution and characterization of populations with respect to the built environment and human activity spaces. Additional focus areas include developing statistical