Requisition Id8548

Overview and Purpose:
The Computational Earth Sciences Group (CESG) in the Computational Sciences and Engineering Division (CSED) is seeking a Senior Computational Scientist in Earth System Science. The candidate will develop and apply analytical workflow and data management tools and methods including artificial intelligence (AI)/machine learning (ML) approaches for data from Earth system models and observations for the next generation Earth System Grid Federation (ESGF2) project. CSED focuses on transdisciplinary computational science and analytics at scale to enable scientific discovery across the physical sciences engineered systems and biomedicine and health. It develops community applications data assets and technologies and provides assurance to build knowledge and impact in novel crosscut-science outcomes.

The candidate will be a senior staff scientist within the CESG of the Advanced Computing Methods for Physical Sciences Section in CSED. The CESG is focused on the conduct of world-class research and development in Earth system modeling; model-data integration large scale data management analytics and machine learning; and model benchmarking at the US Department of Energys (DOEs) Leadership Computing Facilities (LCFs) and its National Energy Research Scientific Computing Center (NERSC). The CESG has specific strengths in numerical methods simulation and analysis focused on terrestrial hydrology and biogeochemistry atmospheric and ocean dynamics aerosols regional climate ice sheets and sea level rise and the global carbon cycle.

Major Duties/Responsibilities:

• Conceive and lead the development of Earth system science data management tools and workflows metadata standards and conventions and value-added products for the next generation Earth System Grid Federation international infrastructure project.
• Lead the design of simulation protocols and data management approaches for community model intercomparison projects.
• Work with the research community to lead the design and development of model evaluation metrics and to synthesize benchmark datasets for model evaluation and benchmarking for multiple components of the Earth system.
• Design AI/ML approaches for Earth system science data analytics value-added product generation and data management.
• Conduct global and regional simulations post-processing and analyses of Earth system models for specific scenario protocols on various high performance computing platforms.
• Collaborate with a diverse team of Earth system and computational scientists both within CESG and across DOE Labs partner universities and other federal agency sponsors in pursuit of new science activities program development and new funding opportunities.
• Publish research in peer-reviewed journals and federal agency and international assessment reports and present results at national and international conferences.
• Develop research proposals to internal and external funding agencies that solicit new and ongoing research and development programs and projects.
• Mentor junior staff postdoctoral associates and students.

Basic Qualifications:

• Ph.D. degree in computational science Earth system science atmospheric science oceanography environmental engineering geography or a related field.
• A minimum of 6 years of relevant experience in modeldata integration model diagnosis and analytics or model evaluation and benchmarking outside of the Ph.D.

Preferred Qualifications:

• Significant research experience with ESMs and performing model diagnosis intercomparison analysis and benchmarking.
• Knowledge of and experience with World Climate Research Programme (WCRP) activities the Coupled Model Intercomparison Projects (CMIPs) and the Earth System Grid Federation (ESGF).
• Proven leadership in contributing to community coordinated infrastructure or research activities related to ESM development evaluation or archival and distribution.
• Familiarity with existing global observational data and relevant observational platforms.
• Experience with FORTRAN C/C++ and Python languages and Linux Git and LaTeX.
• Knowledge of commonly used data file formats and conventions (e.g. CF netCDF HDF) and experience with data and metadata collection encoding and management.
• Experience with high performance computing advanced statistical and machine learning methods and visual data analytics.
• Knowledge of global Earth system processes and interactions across atmosphere ocean land sea ice and land ice components and their representations in ESMs.
• Strong motivation to conduct or support cutting-edge Earth system studies within multi-disciplinary teams.
• Ability to report regular progress and publicize results through contributions to manuscripts reports and conference presentations.
• Excellent verbal and written communication skills.

Relocation:

Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview be sure to ask your Recruiter (Talent Acquisition Partner) for details.
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This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

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ORNL is an equal opportunity employer. All qualified applicants including individuals with disabilities and protected veterans are encouraged to apply. UT-Battelle is an E-Verify employer.