A novel method to design data-driven, fixed-structure controllers with H2 and H∞ performance objectives is presented. The control design problem is transformed into a convex optimization problem with linear matrix inequality constraints, which can be solved efficiently with standard solvers. The method is used to design a data-driven controller for an atomic-force microscope. The closed-loop performance of the calculated controller is validated on a real setup.