Postdoctoral Research Associate

University of Colorado Boulder • Boulder, CO

42d • $71,000

About The Position

The Atmospheric and Oceanic Sciences department at CU Boulder encourages applications for a Postdoctoral Research Associate! This position will develop and evaluate machine learning (ML) emulators of climate model components, with a focus on generalization across diverse climate scenarios. CU is an Equal Opportunity Employer and complies with all applicable federal, state, and local laws governing nondiscrimination in employment. We are committed to creating a workplace where all individuals are treated with respect and dignity, and we encourage individuals from all backgrounds to apply, including protected veterans and individuals with disabilities. The Department of Atmospheric and Oceanic Sciences (ATOC) provides a world-class, interdisciplinary research and educational environment to examine the dynamical, physical, and chemical processes that occur in the atmosphere and ocean. A major theme is the establishment of a physical basis for observing, modeling, and understanding climate and global change. The University of Colorado Boulder is located in a region having the greatest concentration of geophysical researchers in the nation and perhaps the world. The proximity of ATOC to this atmospheric and oceanic science excellence is the foundation of our unique philosophy and vision, which elevates our department to one of worldwide prominence. The guiding principle of ATOC is to be the focal point for atmospheric and oceanic science education and research training in this geographic region of world-renowned excellence. The University of Colorado, Boulder was ranked number one in atmospheric science in Shanghai Ranking's 2018, 2019, 2020, 2021, and 2022 Global Ranking of Academic Subjects.

Requirements

• Ph.D. In Atmospheric/Oceanic science with experience in Machine Learning OR Computer Science Ph.D.

Responsibilities

• Implement and test coupled systems linking atmospheric and ocean emulators (e.g., CAMulator, Sumadra) and compare results against physics-based dynamic ocean models (e.g., POP2) to assess emergent biases.
• Advance innovative ML techniques for Earth system modeling, contribute to the integration of a fully coupled emulator or hybrid ML-physics system, and produce open-source tools and peer-reviewed research that align with the M2lines mission.

Benefits

• medical
• dental
• retirement plans
• generous paid time off
• tuition assistance for you and your dependents
• ECO Pass for local transit

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Industry: Educational Services
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees