Rainmaker Fellow, Satellite Remote Sensing

This is a paid, full-time research fellowship in Rainmaker's satellite remote-sensing group. The fellow will work on a scoped project, taking responsibility for a computational workstream involving satellite data acquisition, processing, validation, and improvement of retrievals. The role involves collaborating with researchers and delivering a concrete artifact such as a dataset or benchmark.

Responsibilities

• Acquire, process, collocate, and quality-control microwave, polar-orbiting, and geostationary satellite observations.
• Reproduce an existing retrieval or operational baseline before testing improvements.
• Validate satellite products against radar, NWP, soundings, surface observations, and Rainmaker aircraft, UAS, or in-situ measurements.
• Quantify detection skill, bias, uncertainty, spatial representativeness, latency, coverage, and failure modes by meteorological regime.
• Implement physically motivated, statistical, or ML retrieval improvements when justified by the project and data.
• Build documented, reproducible workflows that other Rainmaker scientists can run and extend.
• Present findings to satellite scientists, radar scientists, meteorologists, operators, and technical leadership.
• Deliver a final artifact such as a collocation dataset, retrieval benchmark, automated data product, error analysis, fusion prototype, or research paper.

Requirements

• Current undergraduate, master's, or PhD students; postdoctoral researchers; recent graduates; and other early-career researchers are all eligible.
• Strong quantitative and programming ability, preferably in Python.
• Experience with atmospheric remote sensing, satellite meteorology, physics, applied mathematics, electrical engineering, computer science, or a related field.
• Interest in microwave sounders, polar-orbiting observations, geostationary imagery, retrieval methods, or scientific data products.
• Ability to implement a scientific method, establish a baseline, and validate the result carefully.
• Comfort working with large, imperfect, multidimensional observational datasets.
• High agency and the ability to take responsibility for a bounded workstream while collaborating with experienced researchers.
• Clear written and verbal communication.
• Availability for full-time, on-site work in El Segundo for the agreed appointment.

Benefits

• Full health coverage (medical, dental, and vision insurance)
• Lunch provided when working in-office and a fully stocked kitchenette
• Free EV charging at the HQ