Requisition Id 1001
The Computational Earth Sciences Group (CESG) and the Climate Change Science Institute (CCSI; https://ccsi.ornl.gov/ ) at the Oak Ridge National Laboratory (ORNL) are seeking a qualified postdoctoral candidate in the field of Computational Earth Sciences. ORNL’s CESG conducts world-class research and development in Earth system modeling, model-data integration, large scale data analytics and machine learning, and model benchmarking at the US Department of Energy’s (DOE’s) Leadership Class Computing Facilities (LCFs).
- Conduct regional and global Earth system model (ESM) simulations, focusing on analyzing land-atmosphere and land ice-atmosphere interactions.
- Collaborate with a diverse team of Earth system and computational scientists, both within the CESG and across DOE Labs and partner universities, to apply validation, uncertainty quantification, and machine learning methods aimed at enhancing predictive understanding of the Earth system.
- Analyze model simulation results to understand land-atmosphere, land ice-atmosphere interactions, ice sheet responses and ecosystem responses to global change.
- Work with the research community to develop validation analyses, and use machine learning methods to build effective surrogate models based on ESM simulations and to construct purely data-driven models based on available observation data.
- Develop tools to run large-scale ESMs efficiently in ensemble mode on LCF machines, develop multi-fidelity approaches, and develop verification and validation procedures for these ensembles.
- Publish research in peer-reviewed journals and present results at national and international conferences.
For more information, contact Dan Lu email@example.com and Joseph H. Kennedy
- A Ph.D. degree in Earth system science, atmospheric sciences, computational physics or a related field;
- Previous research experience with land surface models (e.g., CLM, ELM), land-atmosphere and/or land ice-atmosphere coupling, and climate prediction
- Knowledge of uncertainty quantification and reduction methods and machine learning algorithms;
- Familiarity with data file formats and conventions (e.g., CF, netCDF, HDF);
- Experience with data manipulation and analysis packages (e.g., Python, R, NCL, NCO, Matlab);
- Experience with the Linux operating system, LaTeX, Git, Python, and Fortran and/or C/C++;
- Collaborative research capabilities as demonstrated by existing peer-reviewed publications and technical proposals;
- Strongly motivated to perform and publish leading edge research;
- Experience with high performance computing, advanced statistical and machine learning methods, and visual data analytics approaches;
- Knowledge of terrestrial ecosystem processes, land-atmosphere interactions, land
ice-atmosphere interactions, and ice sheet processes and their representations in ESMs;
- Excellent verbal and written communication skills.
Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.
ORNL Ethics and Conduct:
As a member of the ORNL scientific community, you will be expected to commit to ORNL's Research Code of Conduct. Our full code of conduct, and a statement by the Lab Director's office can be found here: https://www.ornl.gov/content/research-integrity
Benefits at ORNL:
UT Battelle offers an exceptional benefits package to include matching 401K, Pension Plan, Paid Vacation and Medical / Dental plan. Onsite amenities include Credit Union, Medical Clinic and free Fitness facilities.
UT Battelle offers a wide range of relocation benefits for individuals and families to make it easier to come and work here. If you are invited to interview, please ask your Recruiter about relocating with ORNL.
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.
We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.
If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.
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.
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