August 2019
Message 80

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[Met-jobs] Postdoctoral Researcher - Analysis of Precipitation in Global Models

From "Lee, Jiwoo" <>
To "" <>
Date Thu, 22 Aug 2019 23:57:13 +0000

Analysis of Precipitation in Global Models - Postdoctoral Researcher


Location:  Lawrence Livermore National Laboratory (LLNL), Livermore, CA, USA

Category:  Post Docs

Organization:  Physical and Life Sciences

Posting Requirement:  External Posting

Job ID: 105955

Job Code: Post-Dr Research Staff 1 (PDS.1)

Date Posted: August 20 2019



Join us and make YOUR mark on the World!

Come join Lawrence Livermore National Laboratory (LLNL) where we apply science and technology to make the world a safer place; now one of 2019 Best Places to Work by Glassdoor!

We have an opening for a Postdoctoral Researcher to conduct research involving the analysis of precipitation in Earth System Models (ESMs).  You will use available observations to evaluate state-of-the-art ESMs, developing performance metrics to gauge the strengths and weaknesses of different models, and quantify improvements across ESM generations.  This position is in the Climate Modeling and Analysis group within the Atmospheric, Earth & Energy Division.

Essential Duties
- Conduct creative research on methods to compare model simulations with observations.
- Conduct creative research addressing observational uncertainty in model evaluation.
- Design and develop software to be used in the evaluation of simulated precipitation.
- Publish papers in peer-reviewed journals, and present technical results within the Department of Energy (DOE) community and at scientific conferences.
- Collaborate with others in a multidisciplinary team environment to accomplish research goals.
- Perform other duties as assigned.

- Recent PhD in atmospheric science, or a closely related discipline.
- Experience in one or more of the following areas: climatology, modeling, observations, or atmospheric processes.
- Experience handling and extracting critical information from large datasets from atmospheric models, and/or reanalyzes, and/or observations.
- Proficient in at least one scientific programming language for data analysis (e.g., Python, C++, Fortran), and at least one program for data visualization (eg, Python, VisIt).
- Ability to effectively perform independent research.
- Ability to travel as required to collaborate with colleagues and sponsors. 
- Proficient verbal and written communication skills, as evidenced by published results and presentations.
- Experience collaborating effectively with a team of scientists of diverse backgrounds.
Desired Qualifications
- Experience with UNIX/LINUX.
- Experience with Python, GitHub, and Anaconda.
- Experience in statistics and model evaluation.

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:  None required.

Note:   This is a 2 year Postdoctoral appointment with the possibility of extension to a maximum of 3 years.  Eligible candidates are recent PhDs within five years of the month of the degree award at time of hire date.

About Us

Lawrence Livermore National Laboratory (LLNL), located in the San Francisco Bay Area (East Bay), is a premier applied science laboratory that is part of the National Nuclear Security Administration (NNSA) within the Department of Energy (DOE).  LLNL's mission is strengthening national security by developing and applying cutting-edge science, technology, and engineering that respond with vision, quality, integrity, and technical excellence to scientific issues of national importance.  The Laboratory has a current annual budget of about $2.1 billion, employing approximately 6,800 employees.

LLNL is an affirmative action/ equal opportunity employer. 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, protected veteran status, age, citizenship, or any other characteristic protected by law.




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