Lawrence Livermore National Laboratory · 2 months ago
Applied Statistics Postdoctoral Researcher
Lawrence Livermore National Laboratory (LLNL) is dedicated to strengthening the United States’ security through innovative research. The Applied Statistics Postdoctoral Researcher will engage in cutting-edge research, design, and deployment of statistical methods to solve important decision and detection problems, contributing to various projects within the Computational Engineering Division.
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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
Qualification
Required
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
Lawrence Livermore National Laboratory
Lawrence Livermore National Laboratory, a national security laboratory, provides transformational solutions to national security challenges.
Funding
Current Stage
Late StageTotal Funding
$11.4MKey Investors
ARPA-EUS Department of EnergyDARPA
2023-11-21Grant
2023-08-14Grant
2022-09-19Grant
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