Rainmaker Fellow, Satellite Remote Sensing
Job description
About the role
The Rainmaker Satellite Remote Sensing Fellowship is a paid, full-time research appointment for exceptional undergraduate and graduate students, postdoctoral researchers, recent graduates, and other early-career researchers. You will join Rainmaker's satellite remote-sensing group and work alongside our researchers on a scoped project drawn from the team's current research priorities and defined in close collaboration with your research lead or mentor. Project matching will consider available data, mentor capacity, team needs, and your background. You will take responsibility for a concrete computational workstream while contributing to ongoing retrieval, validation, automation, and operational-support work across the team. Examples of the work fellowship projects change with Rainmaker's research and operational priorities and may include benchmarking and improving microwave-sounder retrievals using Rainmaker in-cloud measurements, radar, geostationary imagery, and model fields; fusing intermittent polar-orbiting observations with frequent geostationary imagery to track cloud properties between overpasses; automating an existing manual satellite-analysis workflow used by Rainmaker scientists or operators; validating cloud-phase, cloud-top, precipitation, moisture, temperature, or related satellite products against Rainmaker observations; or developing a bounded retrieval or satellite data product for research or operational use.
What you'll do
You will acquire, process, collocate, and quality-control microwave, polar-orbiting, and geostationary satellite observations. You will reproduce an existing retrieval or operational baseline before testing targeted improvements under scientific guidance. You will validate satellite products against radar, numerical weather prediction, soundings, surface observations, and Rainmaker aircraft, UAS, or in-situ measurements. You will quantify detection skill, bias, uncertainty, spatial representativeness, latency, coverage, and failure modes by meteorological regime. You will implement physically motivated, statistical, or machine learning retrieval improvements when justified by the project and data availability. You will build documented, reproducible workflows that other Rainmaker scientists can run and extend for ongoing operations. You will present interim and final findings to satellite scientists, radar scientists, meteorologists, operators, and technical leadership. You will deliver a final artifact such as a collocation dataset, retrieval benchmark, automated data product, error analysis, fusion prototype, or research paper that remains useful after the fellowship.
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, is required. Experience with atmospheric remote sensing, satellite meteorology, physics, applied mathematics, electrical engineering, computer science, or a related field is required. Interest in microwave sounders, polar-orbiting observations, geostationary imagery, retrieval methods, or scientific data products is required. You must be able to implement a scientific method, establish a baseline, and validate the result carefully. You must be comfortable working with large, imperfect, multidimensional observational datasets. You must demonstrate high agency and the ability to take responsibility for a bounded workstream while collaborating with experienced researchers. Clear written and verbal communication is required. Availability for full-time, on-site work in El Segundo for the agreed appointment is required.
What success looks like
By the end of the fellowship, you will have answered a clearly defined scientific or operational question and delivered a trusted computational result the satellite remote-sensing team can continue using. Depending on the project, that might be a quality-controlled validation dataset, retrieval benchmark or improvement, error analysis, fusion prototype, automated data product, or operational workflow. Success does not require a positive result. A rigorous conclusion about what the available observations can and cannot support can be as valuable as an improved retrieval.
Fellowship details
Paid, full-time, and on-site in El Segundo. Three-to-six-month appointment, with four months as the standard duration. Rolling applications and project-specific start dates. You will be attached directly to Rainmaker's satellite-science group with a named mentor. Consideration for future full-time roles may be provided when it does not compromise Rainmaker intellectual property or operational know-how.
Compensation and benefits
$8,000 per month. 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.