Lawrence Livermore National Laboratory (LLNL) is dedicated to strengthening the United States’ security through innovative research and solutions. The Applied Statistics Postdoctoral Researcher will engage in cutting edge research and statistical methods to solve important decision and detection problems, collaborating with multidisciplinary teams and contributing to significant projects.
Responsibilities
- Conduct independent, as well as participate in team-based research in and development of one or more of the following areas: physical process modeling, image and video analysis, uncertainty quantification, calibration, design of computer experiments, large-scale model architectures
- Design, implement, and analyze techniques in one or more of the above areas
- Contribute to and actively participate with project scientists and engineers in the scope, planning, and formulating modeling/simulation efforts for physical, engineering, and computational systems in the areas of physics, cyber security, biological and environmental threat detection, uncertainty quantification, and others
- Develop, implement, validate, and document specialized analysis software tools and models as required, including preparing complex and detailed progress reports, written analyses, and verbal briefings to support project needs and deadlines
- Collaborate with others in a multidisciplinary team environment to accomplish research goals including industrial and academic partners
- Organize, analyze and publish research results in peer-reviewed scientific or technical journals and present results at external conferences seminars and/or technical meetings
- Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory
- Travel as needed to coordinate with research collaborators and to attend external meetings and conferences
- Perform other duties as assigned
Skills
- Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship
- PhD degree in Statistics or related technical or scientific field
- Fundamental knowledge and/or experience developing and applying statistical/machine learning models and algorithms for one or more of the following settings: calibration, uncertainty quantification, surrogate modeling, design of experiments, classification, clustering, anomaly detection
- Effective initiative and interpersonal skills and ability to work in a collaborative, multidisciplinary team environment, including demonstrated desire and ability to obtain substantial domain knowledge in fields of application
- Proficient verbal and written communication skills to collaborate effectively in a team environment, present and explain technical information, and effectively communicate with subject matter experts
- Fundamental knowledge of and experience applying programming skills using at least one prototyping language Python/R/Matlab, as well as one of C/C++/Java to enable high performance statistical computation
- Ability to develop independent research projects as demonstrated through publication of peer-reviewed literature
Benefits
- Flexible Benefits Package
- 401(k)
- Relocation Assistance
- Education Reimbursement Program
- Flexible schedules ( depending on project needs)
Company Overview
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