This position will focus on foundational and applied research in computational social science. You will be working as part of an interdisciplinary team to provide research, data analysis, and simulation for social science applications. You should have familiarity with machine learning, data analysis, system dynamics simulation, and/or agent-based simulation. Other topics that support computational social science research, such and complexity metrics and causal inference, are also likely to be integrated into the research and experience with or interest in such topics is desired. SNL Job Title: Computer Science.

Qualifications We Require

• Advanced degree in Computer Science, Computer Engineering, Statistics, Machine Learning, or related field plus a bachelor’s in science, technology, engineering or mathematics, or equivalent combination of relevant education and experience
• Your experience includes machine learning, data analysis, system dynamics simulation, and/or agent-based simulation
• You are able to obtain and maintain a DOE Q-level security clearance

Qualifications We Desire

• PhD in Computer Science, Computer Engineering, Statistics, Machine Learning, or related field
• Experience with simulation, including system dynamics modeling
• Experience with data analysis and machine learning
• Interest in working on social science topics
• Excellent written and oral communication skills
• Ability to work in an interdisciplinary teaming environment
• Ability to be self-directed and lead research projects
• Strong organizational and critical thinking skills

About Our Team

The Machine Intelligence department focuses on cutting-edge research in machine learning and artificial intelligence for national security applications. Our mission is to research, develop, and deploy methods that are credible, robust, and help decision makers in a variety of domains. Specific focus areas include rigorous uncertainty quantification for machine learning, computational social science, geospatial analytics, open-source analytics, and open cyber research.

For more information, contact Asmeret Naugle: abier [at] sandia.gov