Aug. 6, 2021 10:30 am
Sep. 30, 2021 5:00 pm
The Atmospheric Sciences and Global Change Division at Pacific Northwest National Laboratory (PNNL) seeks research scientists to apply artificial intelligence (AI) and machine learning (ML) approaches to address key challenges in climate science. The incumbents will use AI and ML techniques in conjunction with Earth system models, high-resolution models, parameterizations, atmospheric measurements and observational datasets to improve understanding and modeling of the Earth system. The ability to analyze large observational (long-term monitoring or short-term field campaign) data sets for model evaluation is desirable. The incumbents will work in close collaboration with a team of Earth system modelers, atmospheric scientists, computational, and data scientists at PNNL and other DOE national laboratories and universities to address critical science questions.
When applying please include the following in a single document:
- Cover letter describing your research experience and interests;
- Curriculum vitae with list of publications in refereed journals;
- Names and addresses of three references.
The hiring level will be determined based on the education, experience and skill set of the successful candidate based on the following:
Level 2: Receives guidance on new assignments, making preliminary selections on technical alternatives; independently completes recurring assignments. Defines and leads project work at a small task/project level, reporting results on time and on budget. Contributes to proposals. Embraces expectations for quality, safety, and security. Communicates the importance within the work team.
Level 3: Selects and develops technical approaches on assignments with occasional oversight on complex problems. Principal investigator or co-PI on projects or tasks, while integrating capabilities of work team members. Supports scoping, scheduling, and budgeting at a project or major task level. Generates new ideas for proposals and business development opportunities while leading development of technical section of small to medium proposals. Demonstrates ability to acquire funding for self with programmatic impact at the sector and division level. Serves as a role model for quality, safety, and security.