-
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
-
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
-
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
-
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
-
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
-
, 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
-
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
-
: 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
-
: 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
-
. 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