Computational Physics Intern (Spring 2027)
Zipline · South San Francisco, California, USA
About this role
## About Zipline Zipline is the world’s largest and most experienced drone delivery service. We’re on a mission to serve all humans equally by ensuring access to food, medicine, and essential goods anytime, anywhere. We design, build, and operate the world’s largest autonomous logistics system—delivering critical supplies quickly and reliably. Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products. ## About the Systems Modeling Team The Systems Modeling Team has tremendous power to shape Zipline’s products. We develop physics-based models and use them to architect our aircraft and the supporting logistics system. Using simulation, we rapidly explore a wide range of designs to optimize future products and find ways to improve performance in existing products. We bring together diverse fields (e.g., electrical, thermal, mechanical, aerodynamics, battery chemistry, controls, fleet operations, economics) to gain new insights. We translate technical conversations into rigorously framed engineering problems, and we value asking pertinent questions and generating coherent answers. ## The Role (Computational Physics Intern — Spring 2027) Leading the way in drone delivery requires pushing the limits of individual component technologies—and carefully orchestrating which ones we put together to optimize the performance of the complete vehicle. You’ll help answer system-level questions such as: - How much benefit from a larger motor is offset by its aerodynamic penalty? - How much range are we willing to trade for increased payload capacity? - How do we optimally control battery charging (electrically and thermally) to balance turnaround time with battery longevity? Answering these questions requires high-caliber computational tools. Zipline is seeking an engineering intern who can understand system-level problem statements, appreciate the tradeoffs between accuracy and computational efficiency, and architect elegant code tools.
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