Data Assimilation Scientist - 128082

UCSD Layoff from Career Appointment: Apply by 02/13/2024 for consideration with preference for rehire. All layoff applicants should contact their Employment Advisor.

Special Selection Applicants: Apply by 02/22/2024. Eligible Special Selection clients should contact their Disability Counselor for assistance.

THIS POSITION REQUIRES U.S. CITIZENSHIP OR U.S. Permanent Residency.

The Center for Western Weather and Water Extremes (CW3E) is leading the development and implementation of new research and applications capabilities focused on extreme weather and climate events in the US and abroad. CW3E is developing and implementing weather and climate observations, numerical models and decision support tools focused on atmospheric and land-surface conditions related to extreme events and their impacts. CW3E is an interface between UCSD departments, other universities and local, state, and federal agencies, in the operation, utilization and expansion of a new state-of-the-art weather observing network recently deployed in California. Efforts by CW3E include scientific research, technology development, numerical model development and testing, and development/deployment of smart tools that aid decision makers affected by extreme weather, water and climate events. CW3E carries out its goals with a diverse network of research and operational partners at several other institutions across the U.S. and internationally. Individuals will be joining a group of existing Postdoctoral scholars and graduate students, and several experienced faculty, researchers, and staff at Scripps who are involved with CW3E.

CW3E is developing an experimental weather prediction system in the JEDI-MPAS framework for the prediction of atmospheric rivers (AR) and other extreme precipitation events (e.g., tropical cyclones). We seek a motivated, interdisciplinary staff researcher with a background in data assimilation or numerical weather prediction or applied mathematical and computational science to develop novel data assimilation methodology and execute computational research studies in order to assess and improve the prediction skill of this research system. The goal of the initial appointment is twofold - 1) developing a research prediction system for high-resolution regional simulations of extreme precipitation in the Western United States in the JEDI-MPAS framework; and 2) developing and optimizing the data assimilation capabilities of this system in order to maximize the benefits of assimilating unique observation types including radio occultation reconnaissance data from the Atmospheric River Reconnaissance (AR-Recon) Program, led by CW3E. The candidate will play a central role in the team working to optimize modeling and assimilation techniques in order to improve the forecast skill of high-impact precipitation events. The candidate will publish these results in leading journals and will present their work at relevant meetings. CW3E is committed to transferring research to operation, and the candidate will further be encouraged to operationalize their results.

A successful applicant will have demonstrated understanding of data assimilation and numerical weather prediction and demonstrated programming experience and experience working on high-performance computing platforms. Experience using operational data assimilation libraries, using the Model for Prediction Across Scales (MPAS) and / or using Joint Effort for Data assimilation Integration (JEDI) framework is desirable. Applicants should be comfortable working independently with large code libraries and databases, utilizing observations for the atmosphere and the ocean, and producing visualizations as well as working within a team framework.

• Bachelor's degree in related area and / or equivalent experience / training.Master degree or PhD in meteorology, atmospheric sciences, climate science, computer science, applied mathematics and computational science or related field is preferred.

• Thorough knowledge of research function. Use atmospheric data assimilation and statistical techniques to evaluate and analyze large datasets to improve model performance, for deterministic or probabilistic predictions.

• Working knowledge of Atmospheric and/or Earth system modeling.

• Experience with large scale computational implementations for scientific applications.

• Experience with object oriented computing, workflow software development utilizing Github, Python, xarray, pandas and other code libraries for machine learning and large data applications.

• Research skills at a level to evaluate alternate solutions and develop recommendations. This includes proposing new ML techniques, analyses, use of new datasets, new conceptual ideas, or new workflow recommendations.

• Thorough skills associated with statistical analysis and systems programming. Experience with ensemble data assimilation and Kalman filtering techniques.

• Skills to communicate complex information in a clear and concise manner both verbally and in writing. Skills in visualization and graphical representation. Experienced in preparation of scientific articles, posters, and presentations at conferences.

• Project management experience. Ability to work independently and within a team framework. Can prioritize tasks. Meets deadlines

• Ability to supervise, train, delegate work to and or collaborate with junior scientists with diverse backgrounds.

• US Citizenship or Green Card is required.

• Job offer is contingent upon satisfactory clearance based on Background Check results.

Pay Transparency Act

Annual Full Pay Range: $82,500 - $151,500 (will be prorated if the appointment percentage is less than 100%)

Hourly Equivalent: $39.51 - $72.56

Factors in determining the appropriate compensation for a role include experience, skills, knowledge, abilities, education, licensure and certifications, and other business and organizational needs. The Hiring Pay Scale referenced in the job posting is the budgeted salary or hourly range that the University reasonably expects to pay for this position. The Annual Full Pay Range may be broader than what the University anticipates to pay for this position, based on internal equity, budget, and collective bargaining agreements (when applicable).

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