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Machine learning in Climate Science - Postdoctoral Researcher

Entry Level | Full-time
Postdoctoral/Fellowship | livermore, CA | 11/08/2021

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Company Description

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.

Job Description

We have an opening for a Machine learning in Climate Science - Postdoctoral Researcher who will engage in cutting edge research combining statistical methods and machine learning to better understand the impact of climate change and extremes on California.  You will work with a multidisciplinary team of experts in machine learning, separation of climate signals and noise, downscaling methods for climate data, pattern recognition, Bayesian modeling, and spatio-temporal models. This position will be in the Atmospheric, Earth & Energy Division.

 

In this role you will

  • Conduct research on the role of climate variability and change and their impact on energy security, society, and the economy.
  • Design, implement, and analyze techniques in data science and machine learning to improve our understanding of climate variability.
  • Participate with project scientists and engineers in formulating models for climate change and resilience.
  • Develop, implement, validate, and document specialized analysis tools and models.
  • Collaborate with other researchers in a diverse, multidisciplinary team environment to accomplish research goals intended to enhance climate resilience.
  • Publish research results in peer-reviewed scientific or technical journals and present results at external conferences and seminars.
  • Travel as required.
  • Perform other duties as assigned.

Qualifications

  • PhD in atmospheric science, climate science, water cycle or related field.
  • Experience developing and applying advanced statistical/machine learning models and algorithms for one or more of the following settings: classification, regression, detection, and attribution of climate phenomena and/or pattern recognition.
  • Experience in at least one programming language used in data science (e.g., Python (preferred), R, or Matlab).
  • Ability to perform independent research, as demonstrated through peer-reviewed publications.
  • Proficient verbal and written communication skills.
  • Ability to work effectively in a collaborative, multidisciplinary team environment.
  • Ability to travel as required.

 

Qualifications We Desire

  • Ability to manipulate large, complex, and multivariate climate datasets and experience with machine learning tools for classification and regression.
  • Familiarity with downscaling techniques for climate projections at local and regional scales from coarsely resolved model and observational data.
  • Familiarity with spatio-temporal statistical models for variability analysis and with statistical fingerprinting methods.

Additional Information

Why Lawrence Livermore National Laboratory?

  • Included in 2020 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

Security Clearance

LLNL is a Department of Energy (DOE) and National Nuclear Security Administration (NNSA) Laboratory.  Most positions will require a DOE L or Q clearance (please reference Security Clearance requirement).  If you are selected, 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.  If you hold multiple citizenships (U.S. and another country), you may be required to renounce your non-U.S. citizenship before a DOE L or Q clearance will be processed/granted.  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.

If you need assistance and/or a reasonable accommodation during the application or the recruiting process, please submit a request via our online form

California Privacy Notice

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.

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