9 days old

Uncertainty Quantification Postdoctoral Researcher

Lawrence Livermore National Laboratory
Livermore, CA 94550

We have an opening for a Postdoctoral Researcher to perform research in Uncertainty Quantification (UQ), Statistics and Data Science, to advance the discipline as well as to apply cutting edge tools and techniques to high dimensional data stemming from applications that involve complex multi-physics codes that embody a large spectrum of uncertainties across the coupled physics modules. You will work in a multi-disciplinary team together with statisticians, machine learning experts, data science practitioners, and domain scientists in areas such as high energy density physics, material science, nuclear data and weapon physics and design. You will also have the opportunity to engage in a variety of related research projects in computational physics, high-performance computing and data analysis. This position is in the Center for Applied Scientific Computing (CASC) within the Computing Directorate.

In this role you will

  • Research and develop advanced estimation, validation and uncertainty quantification methodology using state-of-the-art statistical methods, machine learning, and/or multi-fidelity modeling.
  • Develop prototype software utilizing high-performance computing to evaluate novel UQ and address model form uncertainty.
  • Publish research results in external peer-reviewed scientific journals and participate in conferences and workshops.
  • Present formal and informal overviews of research progress at group meetings.
  • Contribute to grant proposals and collaborate with others in a multidisciplinary team environment to accomplish research goals.
  • Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
  • Perform other duties as assigned.

  • Ph.D. in Statistics, Computer Science, or related field.
  • Experience in developing, implementing, and applying uncertainty quantification, Bayesian and other statistical inference methods and algorithms.
  • Demonstrates ability and desire to obtain substantial domain knowledge in fields of application and ability to communicate effectively with domain scientists.
  • Experience programming in Python/R/Julia, C/C++ or similar languages, and in a Unix/Linux environment.
  • Demonstrates ability to conduct high quality research and to develop implementations of sophisticated algorithms to evaluate the results.
  • Demonstrates publication record in peer-reviewed journals and/or conferences.
  • Analytical and problem-solving skills necessary to craft creative solutions to independently solve complex problems.
  • Proficient verbal and written communication skills to effectively collaborate in a team environment, present and explain technical information to technical as well as non-technical audiences, document work and write research papers.

Qualifications We Desire

  • Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods.

Why Lawrence Livermore National Laboratory?

  • Included in 2021 Best Places to Work by Glassdoor!
  • Work for a premier innovative national Laboratory
  • Comprehensive Benefits Package
  • Flexible schedules (*depending on project needs)
  • Collaborative, creative, inclusive, and fun team environment

Learn more about our company, selection process, position types and security clearances by visiting our Career site.

COVID-19 Vaccination Mandate

LLNL demonstrates its commitment to public safety by requiring that all new Laboratory employees be immunized against COVID-19 unless granted an accommodation under applicable state or federal law. This requirement will apply to all new hires including those who will be working on site, as well as those who will be teleworking.

Pre-Employment Drug Test

External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Security Clearance

LLNL is a Department of Energy (DOE) and National Nuclear Security Administration (NNSA) Laboratory. Some positions will require a DOE L or Q clearance (please reference Security Clearance requirement above). If you are selected and a clearance is required, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. In addition, all L or Q cleared employees are subject to random drug testing. An L or Q clearance requires U.S. citizenship. For additional information please see DOE Order 472.2.

Equal Employment Opportunity

LLNL is an affirmative action and equal opportunity employer that values and hires a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

LLNS is committed to offering reasonable accommodations during the application and recruiting processes due to a disability. If you need assistance or an accommodation due to a disability, please submit a request via our online form.

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The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.


Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States' security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are looking for individuals that demonstrate an understanding of working in partnership with team peers, who engage, advocate, and contribute to building an inclusive culture, and provide expertise to solve challenging problems.

"},"jobDescription":{"title":"Job Description","text":"

We have an opening for a Postdoctoral Researcher to perform research in Uncertainty Quantification (UQ), Statistics and Data Science, to advance the discipline as well as to apply cutting edge tools and techniques to high dimensional data stemming from applications that involve complex multi-physics codes that embody a large spectrum of uncertainties across the coupled physics modules. You will work in a multi-disciplinary team together with statisticians, machine learning experts, data science practitioners, and domain scientists in areas such as high energy density physics, material science, nuclear data and weapon physics and design. You will also have the opportunity to engage in a variety of related research projects in computational physics, high-performance computing and data analysis. This position is in the Center for Applied Scientific Computing (CASC) within the Computing Directorate.

In this role you will

  • Research and develop advanced estimation, validation and uncertainty quantification methodology using state-of-the-art statistical methods, machine learning, and/or multi-fidelity modeling.
  • Develop prototype software utilizing high-performance computing to evaluate novel UQ and address model form uncertainty.
  • Publish research results in external peer-reviewed scientific journals and participate in conferences and workshops.
  • Present formal and informal overviews of research progress at group meetings.
  • Contribute to grant proposals and collaborate with others in a multidisciplinary team environment to accomplish research goals.
  • Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
  • Perform other duties as assigned.
"},"qualifications":{"title":"Qualifications","text":"
  • Ph.D. in Statistics, Computer Science, or related field.
  • Experience in developing, implementing, and applying uncertainty quantification, Bayesian and other statistical inference methods and algorithms.
  • Demonstrates ability and desire to obtain substantial domain knowledge in fields of application and ability to communicate effectively with domain scientists.
  • Experience programming in Python/R/Julia, C/C++ or similar languages, and in a Unix/Linux environment.
  • Demonstrates ability to conduct high quality research and to develop implementations of sophisticated algorithms to evaluate the results.
  • Demonstrates publication record in peer-reviewed journals and/or conferences.
  • Analytical and problem-solving skills necessary to craft creative solutions to independently solve complex problems.
  • Proficient verbal and written communication skills to effectively collaborate in a team environment, present and explain technical information to technical as well as non-technical audiences, document work and write research papers.

Qualifications We Desire

  • Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods.

Categories

Posted: 2021-11-25 Expires: 2021-12-25

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Uncertainty Quantification Postdoctoral Researcher

Lawrence Livermore National Laboratory
Livermore, CA 94550

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