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.
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Pay Range
$148650.00- $190932.00 Annually for the SES.3 level
Please note that the pay range information is a general guideline only. Many factors are taken into consideration when setting starting pay including education experience the external labor market and internal equity.
Job Description
We have an opening for a Computational Chemist to independently work on the modeling of sorption reaction and transport of species such as gases vapors and solvents outgassing from materials. You will be an integral member of an interdisciplinary team responsible for conducting and supporting research to model and simulate sorption reaction and transport properties of materials in component-scale simulations. This position is in the Computational Materials Science group of the Materials Science Division.
You will
Develop a complete database of experimental and numerical results for sorption reaction and transport of relevant components.
Execute large-scale simulations on supercomputers using capabilities developed at LLNL.
Analyze numerical results from large-scale simulations.
Determine optimal parameters calibrated from experimental data.
Handle a large set of numerical data and establish an efficient method to sort them.
Actively participate in concept development of experiments to capture data needed for computational and machine learning model development.
Develop and present written analyses and verbal briefings that capture and communicate research results as well as periodic progress reports.
Publish research results in peer-reviewed scientific or technical journals and present results at external conferences seminars and/or technical meetings.
Perform other duties as assigned.
Qualifications
This position requires an active Department of Energy (DOE) Q-level clearance.
Ph.D. in Materials Science Computational Geoscience or a related field or the equivalent combination of education and related experience.
Significant experience in big data analytics and machine learning methods as applied to sorption reaction and/or multiphase flow.
Significant experience in the processing of numerical simulation results.
Advanced knowledge of multiphase flow demonstrated through publication.
Demonstrated ability to create complex 2D/3D visualization and develop databases.
Advanced written and verbal communication skills necessary to deliver presentations and prepare written reports explain technical information and provide advice to management.
Advanced interpersonal skills necessary to interact with a diverse set of scientists engineers and other technical and administrative staff within a collaborative research environment.
Qualifications We Desire
Experience in executing analyzing large and complex sets of data.
Knowledge of python MATLAB HTML JavaScript programming languages for web development.
Additional Information
All your information will be kept confidential according to EEO guidelines.
Position Information
This is a Career Indefinite position open to Lab employees and external candidates.
This position requires an active Department of Energy (DOE) Q-level clearance or active Top Secret clearance issued by another U.S. government agency at time of hire.
Pre-Employment Drug Test
External applicant(s) selected for this position must 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.
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