Context. How do biological organisms know how to transport matter and information exactly where they are needed? Many, like the slime mold rely on active flow networks. These systems are governed by the principles of active matter, in which the medium is set in motion locally. Remarkably, these local flows self-organize into transport that reaches the right place at the right time. While these highly effective transport networks are widely observed across nature, the physical mechanisms that allow them to self-organize and direct flows remain poorly understood. In this internship, we will design and study a novel artificial system to recreate these active flow networks and uncover the physical rules governing them. This internship will experimentally recreate active flow in channel networks and model how such flow leads to self-organized functional transport. The student will work together with PhD students and postdocs and use experimental facilities to characterize the flow rate and pressure gradient produced by active pumps. Working with Electrohydrodynamic (EHD) pumping, the student will gain practical experience using our microcontroller-based (Arduino) setup to map how flow and pressure gradients adapt to varying channel configurations. The results will open the way to innovative solutions for adaptive cooling and water management technologies in networks that can easily be disassembled and reused. The internship can be followed by a PhD grant.