Job Description

Rainmaker is pioneering a modern cloud seeding system to solve water scarcity and inclement weather problems. We develop and incorporate radar validation, weather-resistant UAS, numerical weather modeling, and sustainable cloud seeds into an effective precipitation enhancement solution.

We're seeking a full-time, dedicated numerical weather prediction modeling specialist whose primary focus will be supporting our precipitation enhancement programs OR an experimentalist observationalist who will aid in experimental design of field campaigns and laboratory studies. This position will focus on convective cloud seeding research including aerosol invigoration of convection.

• Model Configuration and Development: Configure and maintain model setups in different domains. Simulate both convective processes in warm cloud systems, focusing on convective seeding to enhance precipitation through droplet growth and coalescence, examining ice nucleation and crystal growth dynamics to evaluate precipitation enhancement and cloud microphysics. 
• Data Assimilation and Initialization: Design and implement data assimilation strategies using multiple data sources (surface observations, radiosondes, dropsondes, radar, satellite). Develop preprocessing workflows to ingest and quality-control observational data. Create automated procedures for model initialization and boundary condition updates.
• Model Analysis and Verification: Conduct comprehensive analysis of model output focusing on cloud properties, precipitation processes, atmospheric stability, and QPE. Perform systematic model verification against observational data, and inform future measurement principles to improve model accuracy and confidence.
• Precipitation Enhancement Applications: Validate and support precipitation enhancement operations by providing advanced forecasting models for convective storm systems at high spatial and temporal resolution.
• Experimental Design of Field Campaigns: Conceive of and aid in planning experimental field campaigns and laboratory studies to probe the effects of cloud seeding on convective systems and aerosol invigoration of convection.
• Process and analyze observational data and effectively communicate the findings to the greater scientific and engineering teams.

• Master's degree or Ph.D. in meteorology, atmospheric science, physics, or a related field.
• Demonstrated success in modeling convective storm system development.
• Strong understanding of atmospheric kinematics, electro and thermodynamics, and computation principles and meteorological processes OR demonstrated success as an observationalist who has studied convective systems, aerosol-cloud interactions, or aerosol invigoration of convection.
• Experience with data acquisition, processing, and analysis of large datasets. This involves distributed computing methods, database management systems, data partitioning, vectorizing operations, and GPU acceleration.
• Experience with experimental design and data interpretation
• Experience with Amazon Web Services cloud computing for external data sources, and internal instance management.
• Proficiency in modeling, data analysis tools, and programming languages (e.g., Fortran, Python, MATLAB, R, C++).
• Knowledge of machine learning and deep learning techniques, for modeling applications.
• Previous experience working in both a research and operational environment.

• Preferred Education: PhD degree in atmospheric science, chemistry, physics or other relevant fields
• Preferred Experience: 5-10 years of research experience post PhD
• Preferred Field of Expertise: Convection, aerosol-cloud interactions, cloud microphysics, atmospheric science, aerosol invigoration of convection, ice nucleation

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