Rainmaker Fellow, Radar Science

Rainmaker Technology Corporation· El Segundo, CA· lever· publisert 24.07.2026
Må ha:PythonCloudAIRemote

Examples of the Work Fellowship projects change with Rainmaker's research and operational priorities. Examples of the work our radar team may pursue include:

Creating a radar-aircraft collocation atlas to investigate which radar structures and dual-polarization features contain useful information about measured supercooled liquid water.

Extending and validating an MRMS/MESH hail-event catalog and storm-object tracker.

Developing a benchmark for hail-core growth, motion, splitting, and decay.

Building a carefully controlled radar evaluation framework for cloud-seeding or hail-suppression operations.

Automating an existing radar-analysis workflow used by Rainmaker scientists and operators.

What You'll Do Build quality-controlled radar datasets aligned with aircraft, UAS, satellite, model, surface, or operational observations.

Implement and validate radar-processing, feature-extraction, retrieval, storm-tracking, or statistical-analysis methods.

Investigate how results vary with storm type, range, terrain, temperature regime, observing geometry, and data quality.

Develop honest baselines and quantify uncertainty, false detections, selection effects, and failure modes.

Create case visualizations and scientific analyses that domain experts can inspect.

Avoid overstating what radar observations can establish about seedability or intervention effects.

Produce clear, reusable code and documentation.

Present findings to Rainmaker's radar scientists, meteorologists, operators, and technical leadership.

Deliver a final artifact such as a validated dataset, case atlas, tracking system, retrieval candidate, operational product, analysis protocol, or research paper.

What We're Looking For 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 radar meteorology, atmospheric science, signal processing, remote sensing, image analysis, geospatial data, or a closely related field.

Ability to formulate a scientific question, implement an analysis, and validate the result carefully.

Comfort working with large, imperfect 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.

Particularly Relevant Experience Weather radar, polarimetric radar, MRMS, NEXRAD, quantitative precipitation estimation, storm-object tracking, cloud radar, or radar retrievals.

Scientific Python, xarray, geospatial processing, visualization, statistical modeling, or ML for physical data.

Cloud microphysics, mixed-phase clouds, hail, severe convection, or weather modification.

Aircraft, UAS, field-campaign, or instrument-validation data.

What Success Looks Like By the end of the fellowship, you will have answered a clearly defined scientific or operational question and delivered a result the radar team can continue using. Depending on the project, that might be a validated dataset, case atlas, retrieval, tracking system, analysis framework, or automated operational workflow.

Success means producing a scientifically defensible result with clear quality controls, uncertainty, and attribution boundaries—not forcing a conclusion that the data cannot support.

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.

Attached directly to Rainmaker's radar-science group with a named mentor.

Possible consideration for future full-time roles, without any promise or expectation of conversion.

Publication may be supported 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