Overview
CIWRO at the University of Oklahoma is hiring a Research Scientist/Associate to advance precipitation estimation within the Multi-Radar Multi-Sensor (MRMS) system using AI and machine learning. This collaborative role with NOAA's National Severe Storms Laboratory offers the opportunity to develop cutting-edge algorithms that integrate data from multiple sources to improve weather radar applications and quantitative precipitation estimations.
Job Description
CIWRO at the University of Oklahoma is seeking a Research Associate or Research Scientist to advance precipitation estimation science within the Multi-Radar Multi-Sensor (MRMS) system through the use of artificial intelligence (AI) and machine learning (ML). The MRMS system consists of fully-automated algorithms that quickly and intelligently integrate data streams from multiple radars, surface and upper air observations, lightning detection systems, satellite observations, and forecast models. This collaborative work with NOAA's National Severe Storms Laboratory (NSSL) presents an exciting opportunity to shape the future of weather radar applications and contribute to cutting-edge research and development of quantitative precipitation estimations (QPEs).
Key responsibilities include designing, implementing, and testing AI/ML algorithms to improve the coverage and accuracy of QPEs across all MRMS domains; acquiring knowledge to support and update MRMS system codes and techniques; working with an interdisciplinary team of scientists and engineers to design, develop, and implement QPE-based enhancements; attending meetings and professional conferences to present research results; and providing support through reports and peer-reviewed publications.
Required: Ph.D. (Research Scientist) or M.S. (Research Associate) in a STEM field; strong knowledge of AI/ML; proficiency in high-level programming languages; ability to independently research and resolve problems; excellent oral and written communication skills. Preferred: expertise in precipitation estimation, atmospheric processes/variables, and/or radar data/variables; proficiency in C++, Perl, and/or Python; experience in Linux environments; proficiency in AWS or other cloud computing platforms.
Application deadline: October 8, 2026.